Energy Independent Community. an evaluation for

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1 Energy Independent Community an evaluation for

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3 Energy Independent Community An evaluation for the Algona Municipal Utilities, Iowa Conducted by The Iowa Association of Municipal Utilities Wind Utility Consulting, PC Thomas A. Wind, PE and Joel Logan, IAMU Energy Services Engineer Bob Haug, IAMU Special Projects Project Manager Anne Kimber, IAMU Director of Energy Services Funded in part by a grant from the Iowa Economic Development Authority 2014

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5 Energy Independent Community Evaluation for the City of Algona, Iowa Page i Contents Executive Summary... 1 Section 1 - Projected Future Electricity Needs... 9 Section 2 Power Supply Cost Projections Section 3 Wind Generation Options Section 4 Solar PV Generation Options Section 5 Other Generation Options Section 6 Energy Efficiency Programs Section 7 Direct Load Controls Section 8 Use of Existing Diesel Power Plant Section 9 Projection of Future Hourly Loads Section 10 Financial Impacts of Energy Efficiency on the Utility and Customers Section 11 Financial Impacts of the Low Renewables Scenario Section 12 Financial Impacts of the Medium Renewables Scenario Section 13 Financial Impacts of the High Renewables Scenario Section 14 Summary and Comparison of Results Section 15 Uncertainties and Limitations Section 16 Observations Section 17 Other Considerations Appendices Appendix 1 Energy Efficiency Program Economic Evaluations

6 Energy Independent Community Evaluation for the City of Algona, Iowa Page 1 Executive Summary This study looked at the technical and financial feasibility of the City of Algona (City) becoming more energy independent. Could the City s utility, Algona Municipal Utilities (AMU) obtain a significant share of its energy needs from local resources, given the declining cost of solar and wind power? Since AMU does not serve natural gas in the community, there is little that it can do to affect the natural gas energy that is used in the city. Unlike natural gas, it is technically feasible for AMU and its customers to use local energy resources to become independent in terms of electric use. However, AMU owns an 18.9 megawatt (MW) share of the large Neal 4 coal-fired power plant near Sioux City, Iowa. It has used this power plant share to provide nearly all of its energy needs for the last 30 years. Therefore, in a sense it has been energy independent for many years. However, this study considers whether local energy resources can effectively and economically reduce AMU s reliance on Neal 4 and other remote coal-fired power plants. The results of this study will help AMU decide how it will meet the Clean Power Plan recently proposed by the US Environmental Protection Agency. Residential, Commercial & Industrial MWh 120, ,000 80,000 60,000 40,000 20,000 FIGURE ES-1 Algona Electric Sales Forecast by Customer Class < History Future > < Commercial / Industrial < Resale < Residential Interdepartmental > Public Authorities > 0 Lighting > Year 12,000 10,000 8,000 6,000 4,000 2,000 0 Interdepartmental, Public Authority & LIghting MWh Residential 0.8% Com/Ind 1.1% Resale Interdepartmental Public Athor. Lighting Since this is a forward-looking study, it was necessary to project AMU s electricity needs into the future, based on a Business As Usual (BAU) scenario. The consultants correlated the Algona Municipal Utility s historic electricity sales to its customers with local economic, demographic, and weather data to develop statistically based models for future electricity needs. Figure Executive Summary-1 (ES-1) above shows the resulting projection of electricity usage for the

7 Energy Independent Community Evaluation for the City of Algona, Iowa Page 2 residential customers, the combined group of commercial and industrial customers, and the other smaller sectors. Note that the forecasts for the smaller sectors use a different vertical scale on the right side of the graph. The forecast predicts average annual growth of about 1.0% in the commercial/industrial customer usage and only about 0.8% growth in residential usage. With typical daily peaks of less than 18 MW, Algona s 18.9 MW share of the Neal 4 power plant has provided the bulk of its power needs for many years. Under a 2010 contract with the North Iowa Municipal Electric Cooperative Association (NIMECA), Algona now shares its generating resources with the resources of other municipal utilities in northern Iowa. NIMECA has also contracted purchases from the 225 MW Whelan #2 coal-fired power plant near Hastings, Nebraska. This contract provides an economical source of base-load and peaking energy. AMU also owns 16 MW of diesel peaking capacity in a power plant on the west side of the city, which includes both oil-fired and dual-fueled engine generators. Algona is a part owner and is the designated operator of a three-turbine wind farm near Algona called the Iowa Distributed Wind Generation Project (IDWGP). Although Algona only owns a small share of the 2 MW wind farm, it buys all of the wind power from the other owners and uses the wind power for its customers. IDWGP typically generates 4,500 megawatt-hours (MWh) per year.

8 Energy Independent Community Evaluation for the City of Algona, Iowa Page 3 Five different strategies or scenarios were developed, evaluated, and compared to the Business As Usual (BAU) scenario as part of a process of becoming more energy independent over time. A description of these strategies and goals is shown in Table ES-1. TABLE ES-1 Summary of Strategies Developed and Evaluated to Become More Energy Independent # Name Description Goal Local Generation Added 1 BAU Business as usual Status Quo None 2 EE 3 DLC Low RE Medium RE High RE Implement a comprehensive set of Energy Efficiency (EE) programs to reduce electricity usage as much as economically practical. Install Direct Load Control (DLC) equipment that intermittently interrupts central air conditioning compressors and electric water heaters during peak load periods. Contract with companies to install, operate, maintain, and sell power to AMU from solar photovoltaic (PV) arrays and wind generation in and adjacent to the City, so as to use much more Renewable Energy (RE). Like Scenario 5, but with more solar power and wind generation Like Scenarios 5 and 6, but with even more solar PV and wind generation Reduce electricity usage gradually over a ten-year implementation period by 14%. Reduce summer peak loads & transmission delivery charges, and increase peaking capacity sales to NIMECA members. Reduce electricity usage and increase locally generated electricity to reduce net electricity needs from Neal 4 and NIMECA by 27% compared to BAU. Reduce electricity usage and increase locally generated electricity to reduce net electricity purchases by 41% compared to BAU, and meet the Clean Power Plan CO 2 emissions requirements. Reduce electricity usage and increase locally generated electricity to reduce net electricity purchases by 50% compared to BAU, which more than meets the Clean Power Plan requirements. None None Use power from 3.4 MW DC of solar power installed over a 15- year period and 3.4 MW of wind generation. Use power from 9.6 MW DC of solar power installed over a 15- year period, and 6.8 MW of wind generation. Use power from 14.3 MW DC of solar power installed over a 15- year period, and 8.5 MW of wind generation.

9 Energy Independent Community Evaluation for the City of Algona, Iowa Page 4 As Table ES-1 indicates, the purpose of the strategies is to make AMU s consumers of electricity as energy efficient as possible, by implementing a comprehensive set of energy efficiency programs over a 10-year period. These programs reduce customers power bills as well as AMU s need for power. As this strategy is implemented, the use of local renewable energy (RE) sources is the next most economical strategy to become more energy independent. Scenarios 4, 5 and 6 evaluate the economics of reducing outside energy usage from Neal 4 and NIMECA by 27%, 41%, and 50% respectively over a 15-year period. At the 50% reduction level AMU will either save or use enough locally produced renewable energy to offset 50% of the energy it would have used for the BAU scenario. Figure ES-2 depicts the amount of wind and solar photovoltaic generation capacity in the Low, Medium, and High Renewables scenarios. FIGURE ES-2 Renewable Energy AC Generating Capacity Used in Scenarios by Years Generating Capacity in kw AC 12,000 10,000 8,000 6,000 4,000 2,000 0 Wind Solar PV High Renewables Scenario Medium Renewables Scenario Low Renewables Scenario The use of biodigesters, geothermal energy, and energy storage batteries were also evaluated. Although these technologies will likely be cost effective for certain applications, more in-depth evaluations would be required to determine the amount and cost of these resources. Because of their smaller anticipated financial impact on the study results, they were not included in these strategies. If more in-depth evaluations show their cost effectiveness, then including them would hopefully reduce the cost of becoming energy independent. The technical analysis included hourly load and generation simulations for the 15-year period that determined what renewable energy resources might be reasonably expected to be available to serve AMU s load at any specific hour, based on historical wind patterns and solar insolation levels. From this simulation, the amount of Neal 4 and NIMECA power that was needed to serve the remaining load was calculated. A financial model for AMU s electric utility was developed, so that the financial impact of implementing these strategies, as well as selling fewer kilowatt-hours (kwhs) to customers, could be evaluated. This evaluation determined the amount of revenue and needed electric rate increases to maintain a reasonable operating margin. The costs to both AMU s utility and its electric customers were determined for each of the five strategies and compared to the BAU scenario.

10 Energy Independent Community Evaluation for the City of Algona, Iowa Page 5 The graph in Figure ES-3 illustrates how the energy savings and new local energy resources collectively achieve the 27%, 41%, and 50% self-sufficiency goals. 160,000 FIGURE ES-3 Sources of MWh Savings for Each Scenario for the Year ,000 Needed for BAU Annual MWh Needed 120, ,000 80,000 60,000 40,000 20,000 Neal 4 & NIMECA Purchases 27 % 41 % 50 % Neal 4 / NIMECA Solar Wind EE 0 BAU EE Low RE Medium RE High RE

11 Energy Independent Community Evaluation for the City of Algona, Iowa Page 6 Figure ES-4 depicts the average historical and projected amount of all retail customers monthly electric bills for the BAU and five alternative strategy scenarios over the next 15 years. FIGURE ES-4 Algona's Average Monthly Power Bills Average of Residential, Commercial and Industrial Customers Monthly Average Power Bills in Dollars $400 $350 $300 $250 $200 $150 < History Future > BAU BAU Medium RE EE + DLC Low RE High RE EE Only $ As the graph suggests, the electric customers would expect to generally pay lower power bills in the long-term future for all of the five alternative strategies compared to the BAU scenario. Table ES-2 on page 5 provides a summary and comparison of the results of the financial analysis of all six scenarios. It provides the results from both the utility s perspective (green shading) and the customers perspective (yellow shading). From the utility s perspective, its operating costs are lower than the BAU scenario for all five of the alternative scenarios, primarily because it needs to generate or purchase less power. These operating costs include all of the utility s operating costs to generate and buy power, and to operate and maintain the complete electric system. Electric rate increases would be implemented in the future to maintain a $1.5 million annual operating margin for all six scenarios. From the customers perspective, they save money for all of the five alternative scenarios over the 15-year period compared to the BAU scenario. Nearly all of the savings emanate from the implementation of the additional energy efficiency programs.

12 Energy Independent Community Evaluation for the City of Algona, Iowa Page 7 TABLE ES-2 Summary of Results from Financial Analysis of All Seven Scenarios Scenario Number Description Results from the Utility's Perspective Results from the Customers' Perspective Average Cost Over 15 Year Study Period Residential, Commercial and Industrial Customer Total Utility Operating Neal 4, Power Bills Over the 15 Year Period Costs Energy NIMECA, Solar PV Wind 15 Year Savings Monthly Bill Efficiency Diesels & Power Power Cumulative Total Compared to Savings Programs Total Savings Transmission of All Power Bills BAU Compared to BAU $1,000's $1,000's / kwh /kwh /kwh /kwh $1,000's $1,000's $ per Month Column Number Business As Usual (BAU) $ 196,260 $ $ 216,240 Reference Reference 2 Energy Efficiency (EE) Programs $ 187,970 $ 8, (EE Only) $ 204,920 $ 11,320 $16 (5.2%) 3 EE + Direct Load Controls $ 188,420 $ 7, (EE+DLC) $ 205,120 $ 11,120 $16 (5.1%) 4 EE Programs + Low RE (3.4 MW Solar PV MW Wind) $ 188,750 $ 7, (EE Only) $ 205,520 $ 10,720 $16 (4.9%) 5 EE Programs + Medium RE (9.6 MW Solar PV MW Wind) $ 189,650 $ 6, (EE Only) $ 206,270 $ 9,970 $14 (4.6%) 6 EE Programs + Low RE (14.3 MW Solar PV MW Wind) $ 190,380 $ 5, (EE Only) $ 206,910 $ 9,330 $14 (4.3%) Notes: The cost per kwh in Column 6 does not include the fixed ownership costs for Neal 4, such as bond payments, property taxes and depreciation. Columns 9, 10, and 11 do not include any out of pocket costs the customers would pay for energy efficiency improvements. These costs would average 19% of the savings.

13 Energy Independent Community Evaluation for the City of Algona, Iowa Page 8 The results of this study clearly indicate that starting an aggressive energy efficiency program will save utility customers money. Furthermore, it appears that adding various levels of renewable energy along with the energy efficiency programs also saves customers money in the long run. If the renewable energy is added without implementing the energy efficiency programs, then customers bills would be $1 to $5 per month higher than the BAU scenario. There is no doubt that any of these alternative strategies can be accomplished. Of course, some further evaluation and planning would be required to implement these strategies. The implementation of these strategies would result in more local jobs and business due to the energy efficiency programs. Furthermore, the installation of the wind and solar power generation for the 50% self-sufficiency would result in about $50 million of solar and wind power investment in the community, which would bring additional construction, operation, and maintenance jobs. Although nearly all utilities in Iowa have energy efficiency programs and some renewable energy in their power supply, no Iowa or Midwest utility has yet attempted to get a majority of its needs from a combination of aggressive energy efficiency programs coupled with solar and wind power. Comprehensive planning would be required, and the key to accomplishing this goal will be having a core group of community leaders that can motivate the community to achieve these goals. Thomas A. Wind, Wind Utility Consulting, PC Joel Logan, Iowa Association of Municipal Utilities Bob Haug, Iowa Association of Municipal Utilities August 29, 2014

14 Energy Independent Community Evaluation for the City of Algona, Iowa Page 9 Section 1 - Projected Future Electricity Needs An econometric-based electric load forecast was made to project the future electricity requirements for AMU s customers. This load forecast methodology used a multiple regression statistical analysis to determine what demographic, economic, and weather factors have influenced AMU s electricity needs over the past 21 years. Historical and projected demographic and economic data for Kossuth County were purchased from Woods and Poole Economics, Inc. Weather data was obtained from the US National Oceanic and Atmospheric Administration (NOAA). Based on those past relationships between the demographic data, economic data, weather data, and customer electricity sales, statistical models were developed for projecting these factors into the future. The impact of Algona s current energy efficiency programs was also taken into consideration in the statistical analysis. Four models were developed for AMU. 1) Residential Electric Sales The statistical analysis found that residential sales in the past were correlated to the U.S. Personal Consumption Expenditures (PCE) index, heating degree days, and cooling degree days. The model could account for about 97% of the growth and variability in the historical residential sales. 2) Commercial and Industrial Sales The analysis found that the combination of commercial and industrial sales was well correlated to the earnings of employees of manufacturers in the county, mean county household income, heating degree days, and cooling degree days. This model accounted for 92% of the growth and variability. 3) Summer Peak Demand The summer peak load was largely determined by the total annual energy sales, the maximum temperature on the summer peak day, and the dew point from the prior day. 4) Winter Peak Demand The winter peak was determined by the annual energy sales, plus the minimum temperature the night before the peak. Simple forecasts were made for the public authorities, public lighting, and interdepartmental sales. The distribution system losses and unaccounted for energy were also projected into the future, again using a simple trend model.

15 Energy Independent Community Evaluation for the City of Algona, Iowa Page 10 Figure 1 depicts both the historical and projected electric sales in megawatt-hours (MWh) by customer class out through the year This graph is based on normal weather; and the graph indicates that the Commercial/Industrial sales will likely have more growth, as indicated by the 1.1% average annual growth rate shown in the legend. The residential sector has a little less growth averaging 0.8% annually. FIGURE 1 Residential, Commercial & Industrial MWh 120, ,000 80,000 60,000 40,000 20,000 Algona Electric Sales Forecast by Customer Class < History Future > < Commercial / Industrial < Resale < Residential Interdepartmental > Public Authorities > 0 Lighting > Year 12,000 10,000 8,000 6,000 4,000 2,000 0 Interdepartmental, Public Authority & LIghting MWh Residential 0.8% Com/Ind 1.1% Resale Interdepartmental Public Athor. Lighting

16 Energy Independent Community Evaluation for the City of Algona, Iowa Page 11 Figure 2 shows the total system energy in MWh, which include all of the sales to the customers and the losses. The median or base forecast is shown by the blue circles, and has an annual average growth rate of 1% per year over the forecast period. This forecast is based on a Business As Usual (BAU) scenario, where AMU does not make any significant initiatives to adopt more energy efficiency or peak load control programs. Since there is always some uncertainty in any projection of the future, alternative high and low projections were made for the demographic and economic projections made by Woods and Poole. The upper and lower lines (depicted by the green triangles) provide some measure of the uncertainties in the forecast. Furthermore, a hot summer and cold winter, along with more optimistic demographic and economic projections, could provide sales even higher than shown by the top line of green triangles. The median or base forecast (shown by the blue dots) is used as a starting point for the analysis in this report. The median projected system energy in 2014 is 124,000 MWh. 200,000 FIGURE 2 Algona Total System Energy Forecast - Business As Ususal 180, , , ,000 MWh 100,000 80,000 60,000 40,000 20, Year History High Growth 1.30% Base Growth 0.98% Low Growth 0.64%

17 Energy Independent Community Evaluation for the City of Algona, Iowa Page 12 Figure 3 illustrates both the summer and winter peak load forecasts. Both of these forecasts indicate a modest upward trend averaging 0.4% per year for the summer peak, and 0.8% for the winter peak. The 2014 summer peak forecast for normal weather is projected to be 25 MW. Very hot and humid conditions could increase the peak to 26.5 MW, as shown by the upper red line. Conversely, a mild summer could have a peak as low as 23.5 MW. The median winter peak is projected to be 19 MW. FIGURE Algona Summer and Winter Peak Forecast - Business As Usual Summer Peak Forecasts 25 MW Winter Peak Forecasts Year History High Weather High Growth Base Growth Low Weather Low Growth Electric sales for a small community like Algona can vary a lot due to the expansion or closure of a large industrial facility. Since these events can t be predicted, there is always some uncertainty in projections of future energy sales and peak loads.

18 Energy Independent Community Evaluation for the City of Algona, Iowa Page 13 Section 2 Power Supply Cost Projections AMU is a member of the North Iowa Municipal Electric Cooperative Association (NIMECA), with headquarters in Humboldt, Iowa. NIMECA is a municipal joint action agency serving 13 municipal electric utilities, including Algona. NIMECA has a unique arrangement where its members share their generating resources to collectively meet every member s load. The association with NIMECA allows the Issuer to share resources with other municipal electric utility members of NIMECA helping to mitigate risks and diversify supply by spreading energy over multiple generation units and purchased power contracts. AMU, as a member of NIMECA, became a Class B member of Basin Electric Power Cooperative ( Basin Electric ) for generation, transmission dispatching, and supplemental energy sales and purchases along with ancillary services. Currently, AMU sells excess power to Basin Electric on a short term basis through NIMECA and also purchases supplemental power from Basin Electric through NIMECA. Algona is a little unique in that it owns an 18.9 megawatts (MW) share of the 644 MW large Neal 4 coal-fired power plant near Sioux City, Iowa. This is a very large amount for a utility the size of Algona. The NIMECA contract results in all members pooling their generating resources for the combined financial benefit of all. NIMECA members also get power from the 790 MW Walter Scott coal-fired unit near Council Bluffs, Iowa, and the 225 MW Whelan #2 unit near Hastings, Nebraska. Although the NIMECA contract gives Algona credit for the power that its share of Neal 4 generates, Algona receives a blend of power from all of the power plants owned by the NIMECA members. Therefore, Algona receives almost all of its power through the NIMECA contract. It also receives a small amount of power from the 2 MW Iowa Distributed Wind Generation Project (IDWGP) and from its local diesel electric generators. Last year Algona received 96% of its energy through the NIMECA contract. Nearly all of this energy is from coal-fired generation. The NIMECA contract also considers the cost of having adequate peaking capacity for each member. Those members who have more generating capacity than required to meet their reserve requirement receive payments for the extra capacity. Due to Algona s extra capacity, it has received payments in the past, and if Algona reduces its peak load due to energy efficiency programs and local solar and wind power, then it would receive even more payments. If Algona reduces its monthly and annual peak loads, then it will also reduce the cost of the transmission services. It pays for services from Corn Belt Power Cooperative, from the Western Area Power Administration (WAPA), and from the Integrated Transmission System used by Basin Electric and other regional transmission owners in the Dakotas. The amount of reductions will depend in part upon the coincidence of Algona s peak load with other municipal and cooperative utilities in northwest Iowa and in the Dakotas. Although there is some uncertainty in the amount of these reductions, assumptions were made in the power supply model to reflect the general costs and their relationship to Algona s monthly and annual peak loads. The average cost of transmission over the 15-year study period is estimated to be $7.54 per kw-month. This does not include the cost of the dedicated transmission path for Neal 4 power. In order to project Algona s future power supply costs, a detailed model showing how the NIMECA contract allocates and shares the members generation resources was developed, based

19 Energy Independent Community Evaluation for the City of Algona, Iowa Page 14 on NIMECA s Excel billing spreadsheet. The detailed model predicted the allocation and sharing for the next 15 years. The allocation of the members base-load capacity was based on the relative energy needs of its members. Some members are expected to show little growth over that period, while others may grow as much as 3% per year. Algona s needs were projected to grow about 1% per year for the Business As Usual (BAU) scenario. Based on discussions with NIMECA s executive director, a reference base case was developed for the next 15 years. It was assumed that if Algona saves energy through energy efficiency programs (or if it purchases solar or wind power from local sources), then its remaining energy needs from NIMECA would decline, as would its net peak load. The cost per kwh for these base-load resources was also projected into the future, based on various sources of information. Generally, coal prices and O&M costs were projected to escalate between 2% and 3% per year. Figure 4 depicts the amount of energy Algona is projected to receive through the NIMECA contract and its cost over the next 15 years for the Business As Usual (BAU) scenario. FIGURE 4 MWh and Cost of Power With NIMECA Ccntract Cost of Power per Year Millions $12 $10 $8 $6 $4 $2 Cost per Year (Left Scale) MWh per Year (Right Scale) 160, , , ,000 80,000 60,000 40,000 20,000 $ MWh per Year The cost trends assumed in the BAU scenario were used for all other scenarios that were evaluated in this study. Costs could be higher or lower, depending upon a number of factors. However, these costs are largely rooted in coal costs, operation and maintenance (O&M) costs, and fixed financing costs. Algona recently invested about $10 million in the Neal 4 power plant for a scrubber and other improvements. The fixed financing costs for these improvements are not included in the above costs. The bump in cost in 2017 is due to a lengthy expected outage of the Neal 4 power plant.

20 Energy Independent Community Evaluation for the City of Algona, Iowa Page 15 Section 3 Wind Generation Options The initial evaluations of both wind generation and solar photovoltaic (PV) generation options indicate that they both can be economically viable for AMU, based on the projected wholesale power costs. However, their economic viability depends in large part upon the projects qualifying for the federal and state income tax benefits. This means that they cannot be owned by AMU, at least initially, since AMU s ownership would preclude the projects from receiving the income tax benefits. Therefore, this study assumes that all renewable energy projects would be privately owned, either by local area residents or by outside parties. Figure 5 is a wind speed map showing the average annual wind speed at 80 meters above ground, which is the typical height of a wind turbine nacelle. The orange areas in the region encircled by the dashed black line indicate potential places where one or two large wind turbines could be installed. A more detailed evaluation would be needed to determine the availability of land and the minimum acceptable distance from the airport. FIGURE 5

21 Energy Independent Community Evaluation for the City of Algona, Iowa Page 16 Based on the wind speeds shown in Figure 5, it has been estimated that a small privately-owned wind turbine farm very near to Algona could potentially offer wind power to AMU for a Power Purchase Agreement (PPA) rate of 4.25 per kwh, with a 1% annual escalation in the rate. This estimated rate is based on the receipt of the typical federal income tax benefits and Iowa s Section 476C state production tax credit that is available for community-owned wind farms like this. The cost of wind power from large utility-scale wind turbines has generally been declining over time, due to better wind turbine technology and larger wind turbines. Figure 6 illustrates the general trend in the contract cost of power from large wind farms in the US since The purple circles show the PPA rates for large wind farms selling their power. Larger circles represent larger wind farms. As of 2013, the typical PPA rates for wind farms in the upper Midwest averaged about $22 per MWh, or 2.2 per kwh. This represents a significant drop in wind power prices since 2009, primarily due to longer blades being used on the same size of wind turbines, and a more adequate supply of wind turbines. FIGURE 6

22 Energy Independent Community Evaluation for the City of Algona, Iowa Page 17 The average wind power cost in Iowa from large wind farms is likely around 3 per kwh in areas where transmission capacity is available. This is based on the continuation of the federal Production Tax Credit (PTC) of 2.3 per kwh. The 4.25 estimated cost for one or two turbines at Algona is higher due to lower wind speeds at Algona, and only having a few turbines (compared to 50 or more turbines at a large wind farm). The Iowa 476C 1.5 state tax credit enables such a small project to have a PPA price of 4.25 per kwh. Three years ago this PPA price would likely have been 6 per kwh. In this study, it has been assumed that the initial PPA price for wind power would be 4.25 in 2015, and would decline by 2% per year thereafter. In other words, AMU would pay less for energy from turbines installed after 2015, assuming the federal and state tax credits are still in effect. Once a PPA contract has been executed, the PPA rate in subsequent years of the contract was assumed to escalate 1% per year, to provide a small hedge against operating cost inflation for the wind turbine owners. Again, the 4.25 rate is predicated on the continuation of the federal PTC incentive. If the federal PTC is not available, the PPA rate would likely be around 6 per kwh.

23 Energy Independent Community Evaluation for the City of Algona, Iowa Page 18 Section 4 Solar PV Generation Options The solar energy resources at Algona are about average for the state as a whole; and Iowa ranks below average when compared to other states, as illustrated in Figure 7. Nevertheless, using solar energy in Iowa is now becoming economically viable. FIGURE 7 Iowa Association of Municipal Utilities & Wind Utility Consulting, PC August 29, 2014

24 Energy Independent Community Evaluation for the City of Algona, Iowa Page 19 There has been a long downward march in the cost of solar photovoltaic (PV) generation costs since the PV effect was discovered at Bell labs in Figure 8 from a DOE study depicts the price trends from 1998 through 2012 for smaller PV systems less than 10 kw. The top green line shows that the cost in 2012 was $5.25 per direct current (DC) watt of panel rated capacity. Now, the majority of the costs of PV systems are not in the hardware costs, but in the soft costs. Soft costs include installation labor, permitting, inspection, interconnection, customer acquisition, financing costs, and installer/integrator margins. PV costs in Germany were half of those in the US, because they have much lower soft costs. This suggests that the cost of PV systems will continue to fall as soft costs come down. FIGURE 8 PV prices are even lower today. Furthermore, larger utility-scale PV systems have even lower costs compared to commercial systems. Today in Iowa, utility-scale PV systems of 500 kw in size cost less than $2.50 per watt DC. This is still 100% more than the Department of Energy s (DOE) goal of $1.25 per watt DC for larger commercial-scale systems, and $1.00 per watt DC for utility-scale projects in the year Therefore, PV system prices will likely continue to decline for some time.

25 Energy Independent Community Evaluation for the City of Algona, Iowa Page 20 Figure 9 portrays the projected PPA prices for 3 types of solar PV installations in Algona used in this study. For example, the average cost of all solar PV installations is projected to need a PPA rate of 9.5 per kwh for installation in 2015 (as depicted by the red line in Figure 9). This rate is based on receiving the federal income tax incentive, which now equals 30% of the project s capital cost. If the same project is implemented in 2020, the initial PPA rate is projected to be 8.2 per kwh with continuation of the federal tax incentive, because it has been assumed that the PV initial PPA prices will fall about 3% per year. In both cases, once the project is built, the PPA rate for that project is assumed to increase 1% per year thereafter. Therefore, a project built in 2020 would start out with an 8.2 PPA rate, which would escalate to 8.9 in 10 years. The amount of kwh generated by a PV system was assumed to decline by 0.8% per year, because of panel degradation. This long slow degradation also increases the cost of PV power per kwh, since fewer kwh are generated over time. Therefore the average cost of PV power over the 10- year period in the above example would be about 8.9 per kwh. Again, all of these PPA price projections are based on the continuation of the 30% federal investment tax incentives. FIGURE 9 Initial PPA Rate for Solar PV and Wind Power Projects by Vintage Solar PV Wind Power Cents per kwh DOE Price Goal for Utility Scale PV in Note: After a PPA contract is executed for a project, the initial PPA rate is assumed to increase 1% per year thereafter for that project. Three types of PV systems were assumed to be installed in this study. The first type is a large scale ground mounted system with a fixed 30 tilt. The second type is a large PV system with a single-axis tracker that tilts the panels around one axis to follow the sun during the day. This PV system with a 30 southward tilt generates about 26% more kwh over the course of the day, since it is better oriented toward the sun, especially in the early morning and late afternoon. This additional power in the morning and afternoon allows the PV system to better match the utility s daily load curves, which in turn reduces the net summer peak demands. In this study it was assumed the single-axis tracker systems cost 0.5 per kwh more than the fixed-tilt systems. However, they may be more cost effective for the utility, because they reduce the summer peak demands. A dual-axis tracking system would deliver 32% more kwh than the fixed-tilt system.

26 Energy Independent Community Evaluation for the City of Algona, Iowa Page 21 This type of system was not considered in this study, because of the additional complexity and costs of those systems. The third type of PV system used in this study is a roof-mounted system that utility customers would install on their roofs. In this study it was assumed that the utility would have a contract with its customers to pay 10.0 per kwh rate for all kwh produced by the rooftop PV system. This would be in lieu of having a net metering tariff. Therefore, the customer with the rooftop PV system would continue to buy all of its power from the utility at the normal rate, and then it would receive a credit on its bill for 10 per kwh for all kwh generated by the PV system. Of course, the utility could implement a net metering tariff if so desired. In either case, it would need to allow customers to connect any rooftop PV system behind their meter if they so choose. For the purposes of this study it does not make much difference which way the rooftop systems are handled by the utility. Again, it was assumed that the federal 30% investment tax credit would continue into the future. Table 1 summarizes the initial, long-term, and average annual generation per 1 kw DC of panel rating at Algona that were assumed for this study. For example a 1 kw 30 fixed-tilt PV system would generate 1,074 kw per year the first year, and 922 kwh after 20 years. The average over 20 years would be TABLE 1 Average Annual kwh Output from 1 kw DC PV Systems Initial In 20 Average Years Years Fixed Tilt & Rooftop 1, Single-Axis Tracker 1,353 1,162 1,258 about 1,000 kwh per 1 kw of rating. The peak output of the system will depend upon a number of factors, such as the tilt angle, the month, the relative size of the inverters compared to the DC panel ratings, and the actual design of the PV system. In this analysis, a 1 kw DC PV 30 fixedtilt system would typically generate a maximum of about 0.70 kw AC, with only about 100 hours per year that it would generate above that amount. The absolute maximum output would be 0.87 kw AC assuming the inverter is sized to achieve that. When the PV system is generating, it averages 0.26 kw AC and the system will generate at least some small amount of power for 47% of the hours during the year. In this study it was further assumed that the solar PV arrays would be designed to have a maximum AC output that would be 75% of the DC panel ratings. Therefore, to convert a kw DC PV array rating to a kw AC array capacity, multiply the DC rating by 75%. This percentage multiplier can vary from around 70% to 100% and it depends upon various economic factors and the goals of the owner. Based on the assumptions made in this study, changing this percentage has little impact on the results of this study.

27 Energy Independent Community Evaluation for the City of Algona, Iowa Page 22 Because a 30 single-axis tracker follows the sun throughout the day, it generates about 26% more energy during the year for the same identical panels. It would also have more hours with high output. Figure 10 compares the output of a 100 kw DC 30 fixed-tilt system and a 100 kw DC single-axis tracker tilted at 30 on a sunny day in early July in Algona. The single-axis tracker generates considerably more power in the early morning and late afternoon. For example, at an hour ending 8:00 AM (standard time), the single-axis tracker had generated 53 kwh versus 23 kwh, which is 2.3 times as much. Likewise at an hour ending 5:00 PM, the single-axis tracker had generated 57 kwh versus 30 kwh, or 1.9 times as much for the same hour. FIGURE Comparison of kw Output Between Fixed Tilt and Single-Axis Tracker PV Arrays both a 100 kwdc AC Output in kw Fixed 30 Degree Tilt Single-Axis Tracker at 30 Degree Tilt 0 12:00 AM 1:00 AM 2:00 AM 3:00 AM 4:00 AM 5:00 AM 6:00 AM 7:00 AM 8:00 AM 9:00 AM 10:00 AM 11:00 AM 12:00 PM 1:00 PM 2:00 PM 3:00 PM 4:00 PM 5:00 PM 6:00 PM 7:00 PM 8:00 PM 9:00 PM 10:00 PM 11:00 PM 12:00 AM Although PV systems with single-axis trackers cost more, they generate more energy and generate more during the mornings and evenings, which better matches the utility s needs. In this study, it was assumed that any solar PV generation would be comprised of a combination of 1/3 having a 30 fixed tilt construction, 1/3 with single-axis trackers placed at a 30 tilt toward the south, and 1/3 on rooftops (again at a 30 fixed tilt).

28 Energy Independent Community Evaluation for the City of Algona, Iowa Page 23 Section 5 Other Generation Options Micro-Turbines Micro-turbines use natural gas or diesel fuel to generate electricity. They are often supplied with waste heat boilers to provide hot water for facility heating, and can be outfitted with absorption chillers to provide air conditioning. Operating in this Combined Heat and Power (CHP) mode increases the overall thermal efficiency up to 80%. Figure 11 shows a picture of a Capstone 65 kw micro-turbine with a waste heat boiler. There are probably several locations in Algona where a micro-turbine may be economically attractive, however a more thorough evaluation would be needed to determine this. The electrical generation from the micro-turbine would reduce the utility s monthly and annual peak demands. FIGURE 11 In this study, a micro-turbine designed for CHP was assumed to cost $3,500 per kw of electrical capacity and have an average annual heat rate of 13,500 BTU per kwh. A credit of 3 per kwh generated was given for the value of the heat provided by the waste heat boiler. Since a more detailed analysis was not done, no micro-turbines were assumed to be installed in this study. Battery Energy Storage Commercial-scale Battery Energy Storage (BES) is now available, but it is expensive. BES systems can be economical where demand charges and daytime energy are very high and nighttime energy costs are low. The price of energy that AMU pays is essentially the same day or night under the NIMECA contract. Therefore, BES systems at current prices would not be competitive with other systems for load shifting and reducing peak demands. The cost of a BES system was assumed to be $3,000 per kw of capacity with a 4-hour discharge capacity at full rating. The round-trip efficiency was estimated to be 80%. The capital cost of BES systems is projected to continue to decline as battery technology advances, while the performance of batteries will continue to improve. If AMU eventually depends heavily on renewable energy, then BES systems may be economically feasible under the right conditions, depending upon future market prices and the structure of the NIMECA contract in the future. Biodigester Generation Where there are sufficient quantities of biomass in the form of crop residue, animal waste, food processing waste, or other biomass waste streams, advances in anaerobic digesters make it possible to convert these wastes to methane. Methane may be burned to produce heat or used as

29 Energy Independent Community Evaluation for the City of Algona, Iowa Page 24 a fuel for engine-powered electric generators. Among advantages of this technology is the possibility of the short-term storage of the gas, so that electricity can be produced to balance intermittent output of wind and solar generators, or for shaving the peak. Another advantage is that the combustion of methane reduces greenhouse gas, since the natural decay of the biomass would produce methane. In the future there may be a dollar value for reducing methane emissions. An evaluation of Algona s waste treatment plant facility could be done to determine the cost effectiveness of adding an engine generator or micro-turbine generator at that location. Geothermal Energy Geothermal energy systems in the Midwest do not generate any electricity, but they use electricity to convert low-grade heat from the earth to a higher temperature, which is more useful for heating. Converting gas-fired heating systems for homes and businesses to geothermal energy heating systems greatly reduces the amount of natural gas used for heating. If the electricity used by the geothermal heating systems is produced by local renewable energy systems, then this helps the community become more energy independent. The cost effectiveness of this strategy for home and business owners depends upon the availability of a low-cost electric rate for geothermal energy systems. Since AMU does not have a low-cost rate option for this, it would need to develop this rate. This might be a good strategy for increasing electric revenue to offset the decline in revenue due to energy efficiency programs. Although this study did not consider any significant conversion from gas heat to electrically powered geothermal heat, it is likely that this type of conversion program would not cause electric rates to increase, and could possibly lower electric rates, depending upon how it was structured. This type of program would fit well with an overall goal of making AMU more energy independent.

30 Energy Independent Community Evaluation for the City of Algona, Iowa Page 25 Section 6 Energy Efficiency Programs Energy efficiency (EE) programs are the most cost-effective way to lower customer power bills and keep more dollars in the pockets of Algona residents and businesses by creating jobs and economic activity. Energy efficiency programs run by Iowa s municipal utilities have been avoiding the need to buy or generate power for as little as a few cents per kwh. This is usually less expensive than generating or buying wholesale power. Using the results of other utilities, an analysis was performed, based on a study conducted for IAMU by the Energy Center of Wisconsin. The study looked at a broad range of energy efficiency programs that were designed for residential, commercial, and industrial customers. The results of that study were evaluated for the Algona study to determine which programs would be cost effective for Algona s electric customers, based on AMU s wholesale power costs and other demographic data. A total of 44 energy efficiency programs designed for residential customers, and over 100 programs for commercial and industrial customers, were considered. Of these programs, the analysis indicated that about 15 residential programs and 46 commercial and industrial customer programs could be cost effective and worthwhile over the long run for AMU. Collectively the 61 different programs could save the utility about 20,000,000 kwh per year when they are all fully implemented, which is about 15% of Algona s future annual projected electricity needs. The analysis indicated that residential customers could achieve a 20% reduction in electricity usage, while the commercial and industrial customers could achieve a 13% reduction. Based on this initial evaluation it was determined that the energy efficiency programs would be very beneficial to the electric customers, and would save the utility enough power costs to more than pay for implementing the energy efficiency programs. Therefore in this study it was assumed that AMU will gradually implement all of the cost-effective energy efficiency programs over a 10-year period. This would require hiring one to two full-time employees to administer the programs. These programs will result in a significant amount of work for businesses to provide the products and services called for in the energy efficiency programs. After the 10-year period, it was assumed that at least one utility employee would continue to implement energy efficiency programs using new products and technologies that will undoubtedly develop over the 10-year phase-in period. This continuation of the energy efficiency programs ensures the continued savings in energy over the longer term. Since Algona has a modest-sized utility, the administrative cost for implementing the energy efficiency programs was conservatively assumed to be 50% higher than for the same programs in larger communities, on a per customer basis. This upward adjustment in administration costs also accounts for having to administer and aggressively market a broader range of energy efficiency programs than typically done in a small community.

31 Energy Independent Community Evaluation for the City of Algona, Iowa Page 26 Table 2 presents the results of the analysis of implementing the full complement of energy efficiency programs that are gradually phased in over a 10-year period starting in The information in the table shows all of the energy efficiency program costs and all of the resulting energy savings over the 15-year study period. The green shaded row indicates that from the customers perspective, the energy efficiency programs will save them about $9.1 million over the 15-year period. This net savings considers the extra out-of-pocket costs they will incur for purchasing more efficient appliances and improving their homes and businesses. The yellow shaded row shows that from the perspective of the utility, the energy efficiency programs will provide a net savings of $8.3 million for the utility. The blue shaded row points out that the cost to save 1 kwh is $0.021 on average over the 15-year period. The pink shaded row indicates that it only costs about one-third as much to save 1 kwh as it does for the utility to generate or purchase 1 kwh of power. As discussed previously, the cost of saving energy is much less than the cost of buying or generating energy. Therefore, it is very cost effective for both the customers and the utility to implement a comprehensive set of energy efficiency programs. TABLE 2 Comprehensive Energy Efficiency Program Energy Savings and Program Costs All Numbers are Cumulative Totals Over 15 Years Specifically for Algona Residential Commercial / Total for All Industrial Customers Energy Saved, including Losses, in kwh 73,300, ,100, ,400,000 Average Percentage Saved Over 15 Years 14% 10% 11% Percentage Saved After Programs Fully Implemented 20% 14% 15% Customer Power Bill Savings Compared to BAU $ 6,574,754 $ 4,746,309 $ 11,321,062 Extra Out of Pocket EE Costs for Customers $ (588,000) $ (1,584,000) $ (2,172,000) Net Savings to Customers Who Use Programs $ 5,986,754 $ 3,162,309 $ 9,149,062 Utility Savings in Neal 4 & NIMECA Power Costs $ 12,720,238 Utility Cost for Running All Energy Efficiency Programs $ (4,437,000) Net Savings to Utility for Implementing the Energy Efficiency Programs $ 8,283,238 Total Projected Cost to Utility for All EE Programs for Next 15 Years $ 4,437,000 Total Projected Energy Saved by All EE Programs over the Next 15 Years, in kwh 204,400,000 Projected Total Average Cost to Utility to Save 1 kwh with EE Programs $0.022 BAU Projected Average Cost of Neal 4 and NIMECA Power for Next 15 Years in $/kwh $0.064 Cost to Save 1 kwh Compared to the Cost to Buy 1 kwh 34% Note: If the EE costs to the customer are included, then the cost to save 1 kwh increases to $0.031 / kwh

32 Energy Independent Community Evaluation for the City of Algona, Iowa Page 27 The only downside to implementing energy efficiency programs is that the cost per kwh will be a little higher, because the utility would be selling fewer kwhs. Although the utility s operating expenses will go down because it is generating less wholesale power, many of its other operating expenses will continue to rise with inflation, which is assumed to be 3% annually. Therefore the utility s total operating expenses do not go down as much as its retail sales revenue goes down. Therefore the average rate per kwh must go up more than it would for the Business As Usual (BAU) scenario. Based on this analysis, electric rates would average about 0.8 per kwh higher than the BAU scenario. Although rates are a little higher, customers power bills will be on average about 4.5% less with the energy efficiency programs. Therefore, both the customers and the utility will save money with the energy efficiency programs. Figure 12 illustrates the amount of energy savings that customers would obtain over time if this set of aggressive energy efficiency programs was implemented. The dashed lines indicate the lower consumption with the energy efficiency programs. 120,000 FIGURE 12 MWh Sales With and Without Additional EE Programs 100,000 80,000 60,000 40,000 Comm / Ind. MWh Sales With Additn'l EE Programs Residential MWh Sales With Additn'l EE Programs 20, In this cost analysis, it was conservatively assumed that the utility would pay a 50% rebate for the out-of-pocket cost the customer would have to pay for the more efficient appliances, insulation, or other items. The cost of this 50% rebate adds to the program costs for the utility, which tends to raise rates. However, one alternative to providing a rebate is to have the utility pay for the upfront cost the customer would otherwise have to pay for energy efficiency improvements. The utility would then add an extra amount to the customer s bill every month to recoup all or most of the upfront cost. This method of having the utility finance the energy

33 Energy Independent Community Evaluation for the City of Algona, Iowa Page 28 efficiency improvements through the customer s electric bill makes it extremely easy for the customer, since the customer has no upfront cost to pay. Furthermore, the amount added to the customer s bill would be calculated so that the bill would still be less than it would have been without the energy efficiency improvements. If the customer doesn t have to pay any upfront costs and is essentially guaranteed a reduction in the monthly electric bill, then the participation rate will be higher. The cost for doing this on bill financing is likely less than providing a 50% rebate, even if some smaller rebate is built into the arrangement. If this on-bill financing is used by AMU, then the overall cost savings from the energy efficiency program will be a little higher than estimated in this study. If some customers don t take advantage of any of the energy efficiency programs, their power bills will be higher than they would be under a BAU scenario. Therefore, it is important to get as many people to participate as possible. There may also be instances where low-income residents simply do not participate for other reasons. If this becomes a concern, then special provisions could be allowed for them to ensure that they receive the benefits of the energy efficiency programs. Appendix 1 shows the energy efficiency programs that were projected to be cost effective to implement. It should be noted that the list represents an aggressive approach to energy efficiency. It is unlikely that any other utility in Iowa has made this type of commitment to saving energy.

34 Energy Independent Community Evaluation for the City of Algona, Iowa Page 29 Section 7 Direct Load Controls One method to reduce dependency on the electric grid is to reduce the peak demand of the utility. If a utility has peak demand charges above about $8-10 per kw-month, then a Direct Load Control (DLC) system is likely a very cost-effective option for reducing the utility s wholesale power demand charges. In this study a radio-based DLC program that controlled both residential and commercial central air conditioners and electric water heaters was evaluated. When triggered to control the peak demand, the DLC system would interrupt the central air conditioner compressor s 24 volt control signal to turn off the compressor for 20 minutes every hour. The DLC system would interrupt the 240 volt power circuit to the water heater continuously during the control period. The DLC system would also use special smart thermostats that would change the temperature setting slightly when a load control radio signal was received. Table 3 summarizes the number of air conditioners and electric water heaters that were assumed to be controlled by which type of customer. TABLE 3 Direct Load Control Program Cost and Performance Assumptions Central Air Conditioner Electric Water Heater Smart Thermostat Controls Controls Controls Residential Commercial Residential Commercial Residential Commercial Number of Customers Target % of Customers for DLC 27% 29% 13% 15% 17% 15% Target Number of Customers for DLC Peak Demand Savings per DLC Control, kw Peak Demand Savings by Group, kw Peak Demand Savings by Type, kw 1, Summer Peak Demand Savings for All Controls, kw 1,991 Capital Cost per Control Point $325 Total Capital Cost of DLC System $647,000 Total Annual Operational & Maintenance Costs $19,900 The table indicates that the DLC system will reduce the utility s summer peak demand by about 2,000 kw. Although not used in this study, the winter peak demand could be trimmed by the using the electric water heater controls, which would total about 375 kw. Based on a detailed analysis of how the DLC system would affect Algona s future power supply costs, it was concluded that cost of implementing, operating and maintaining the DLC system over the 15-year study period was just barely offset by the savings in the power supply costs over the 15-year period. Therefore, implementing the DLC system does not save Algona any money and is likely not cost effective at this time. If the credit for extra diesel peaking capacity significantly increases in the NIMECA contract, then the DLC system may become cost effective.

35 Energy Independent Community Evaluation for the City of Algona, Iowa Page 30 Section 8 Use of Existing Diesel Power Plant The existing diesel electric power plant has 2 oil-fired diesels with an accredited capacity of 8,600 kw and two dual-fueled diesels totaling 7,100 kw. All engines are in good operating condition and are well maintained. The diesel power plant is a valuable asset for the City for two reasons. If the transmission system that brings power into the City is damaged by a storm or ice, AMU s power plant can be started to restore power. In a worst-case ice storm lasting several days, having a local power plant can save city residents millions of dollars in lost business, added expenses, and inconvenience; plus it can maintain essential services that ensure public safety. Having a local power plant is like having a top of the line insurance policy (with no deductibles) against natural disasters. Secondly, having a local power plant can provide a hedge or credit against higher power costs caused by a regional shortage of generating capacity. Although this value varies over time due to market conditions and is difficult to quantify, it is probably worth at least $500,000 per year on average over the long term just for these two key benefits alone. The NIMECA contract requires AMU to run its diesel power plant when requested by NIMECA or its wholesale suppliers. This arrangement minimizes the number of times and the amount of hours the diesels run, because they are only run when the regional power market has high prices. Because of adequate supplies of power in the region over the last 5 years, the diesels were rarely called to run. As the regional economy continues to grow and thousands of megawatts of smaller old coal-fired power plants are retired due to their higher air emissions, the balance between regional supply and demand will tighten. Although there have been many large wind farms constructed every year in the region, the need for power during summer peak periods and some winter peak periods will only grow, since wind farm output is typically not high during many of those periods. This need for power during peak periods will only increase the value of AMU s local power plant. For the purposes of this study it was assumed that Algona would continue being a member of NIMECA for the next 15 years. Based on the historic needs to run the diesels, it was assumed they would only generate an average of 120 MWh per year in the future. If the regional grid does have a shortage, then they would of course be run more. However, it is unlikely the added cost of the diesel generation would be large enough to affect the results and conclusions of this study.

36 Energy Independent Community Evaluation for the City of Algona, Iowa Page 31 Section 9 Projection of Future Hourly Loads A detailed analysis was done on an hour-by-hour basis to determine how the various options for becoming more energy independent would affect the utility s wholesale power purchases over time. The analysis started with 15 years of hourly load data from Algona s system covering the years 1999 through A simple multiplier was developed to increase the hourly loads up to a level where the annual energy equaled the projected amounts in the econometric load forecast. This simple multiplication resulted in an annual peak load that was typically higher than the projected summer peak load. Therefore a second adjustment was then made to the hours with high loads to reduce the loads, so that the highest hourly load for the year matched the projected summer peak for Algona. Making these two adjustments resulted in hourly load projections that gave the same total annual kwh and summer peak as the load forecast projected. Since this study looks out 15 years into the future, and since 15 different years of historical hourly load data were available from Algona, the hourly load projections for each future year used a different historical year of data as a starting point. Therefore, the projected load patterns changed a little from year to year, just like actual loads do. This procedure for estimating the hourly loads is not perfect, but the procedure does provide some variability in the load profile from one year to the next, which is a natural feature of utility loads.

37 Energy Independent Community Evaluation for the City of Algona, Iowa Page 32 Figure 13 depicts two different weeks of projected hourly loads in the year The load patterns were taken from Algona s actual hourly loads for the year The peak in that year occurred on a Monday afternoon at 2:00 PM in the middle week of July. The Algona hourly loads were adjusted upward to the level projected in the energy forecast for Algona. The peak in Figure 13 is also shown on a Monday at 2:00 PM at a value of 25,879 kw, which is the value in the peak load forecast. The solid red line depicts the hourly loads for the peak week in the year The peaks on Monday through Wednesday may be a little sharper and more pointed than Algona s actual peaks are, because of the non-linearity of the extrapolation process used for projecting future hourly loads. The dotted red line right below the solid red line depicts the projected loads if all of the energy efficiency programs are implemented. The load reductions from the energy efficiency programs were estimated from the data from the Energy Center of Wisconsin analysis, which projected the amount of load reduction and the hours that each of the various energy efficiency programs would trim the load. For example, using higher efficiency air conditioners primarily reduces load during the summer on-peak period, whereas higher efficiency refrigeration equipment would save energy year round. FIGURE 13 Hourly Load in kw 30,000 25,000 20,000 15,000 10,000 5,000 Hourly Load Projections for Two Weeks in 2024 Suumer Peak Week in Middle Week of July Dashed Lines are After EE Programs Tick Mark is Noon Minimum Load Week in Early May Noon Noon Noon Noon Noon Noon Noon Monday Tuesday Wednesday Thursday Friday Saturday Sunday The minimum load for 2024 is projected to be 8329 kw at 4:00 AM Sunday morning in the first week of May. The solid blue line shows the projected loads for that week, whereas the dotted blue line shows the loads if all of the energy efficiency programs were implemented. Hourly loads were projected in a similar manner for every hour for the 15-year study period. However, each year had a different load pattern based on the actual recorded hourly loads from Algona for one of the years between 1999 and This provided a good range of variability in the load patterns for analyzing the impact of solar and wind generation on Algona s load.

38 Energy Independent Community Evaluation for the City of Algona, Iowa Page 33 Section 10 Financial Impacts of Energy Efficiency on the Utility and Customers A detailed hourly simulation was done for all of the various options that are available for the City to become more energy independent. This simulation provided information on how much power AMU had to use from Neal 4 and NIMECA. A financial model of the utility was developed to project how much revenue the utility would need each year through the year This revenue requirement was based on setting an annual target operating margin of $1.5 million. The resulting calculated revenue requirement would then determine how much electric rates would need to be increased to try to obtain the target margin. Electric rates were adjusted each year in the study to meet the target margin, so that the financial impact of the addition of energy efficiency programs, direct load controls, micro-turbines, and renewable energy could be more accurately determined and compared to not doing anything, or the Business As Usual (BAU) scenario. The BAU scenario simply assumes that none of the programs discussed in the previous sections are implemented, nor is any locally generated renewable energy purchased and used. One important factor for Algona is that because of its shared ownership in the Neal 4 coal-fired power plant, Algona must address the Environmental Protection Agency s proposed Clean Power Plan which sets greenhouse gas emission requirements for existing power plants. The Clean Power Plan s proposed goal for Iowa is 1,301 pounds of CO 2 per MWh of generation. Under the NIMECA contract, essentially all of Algona s power comes from large base-load units similar to Neal 4, which has an emission rate of about 2,200 pounds per MWh. The proposed EPA rules allow credits for energy efficiency and renewable energy by using this formula: Adjusted Emission Rate = Pounds of CO2 from Affected Units MWh from Affected Units + MWh RE + MWh EE The abbreviations RE means renewable energy and EE means energy efficiency. Although there is some uncertainty how the final adopted EPA rules will affect Algona in the overall state implementation plan, it has been assumed that Algona would need to abide by the rules and that the above formula would be applicable. Assuming that Algona and NIMECA s coal-fired generation has an average emission rate of 2,200 pounds per MWh, Algona s emission rate was calculated over the 15-year study period. Algona s purchase of all of IDWGP s wind power was counted as credit in the above formula, which reduces the rate by 70 pounds per MWh. The IDWGP wind farm was assumed to be retired after 20 years, which is at the end of In this study, no credit was given for the MWh saved to date by Algona s existing energy efficiency programs, but only for additional future energy efficiency programs.

39 Energy Independent Community Evaluation for the City of Algona, Iowa Page 34 Figure 14 graphically shows the annual energy needs in MWh (along with the sources of those MWh) since the year 2004 out through the entire 15-year study period to 2029 for the BAU scenario. Energy needs are expected to grow about 1 % annually over time for the BAU scenario and would be primarily supplied by Neal 4 and NIMECA. The red line shows the adjusted emission rate for CO 2. The bump upward in 2019 is due to the assumed retirement of the 2 MW IDWGP wind farm. The gray line with round yellow markers shows Algona s annual peak load in kw. 160, ,000 FIGURE 14 Algona's Electricity Needs and Resources Scenario 1 Business As Usual (BAU) BAU MWh < History Future > 2,400 2,100 MWh per Year 120, ,000 80,000 60,000 CO2 per MWh 1,800 1,500 1,301 1, Pounds of CO2 per MWh 40, , Wind Gen Existing Engines Neal4, NIMECA Net Peak Demand CO2/MWh CO2 Target

40 Energy Independent Community Evaluation for the City of Algona, Iowa Page 35 Figure 15 illustrates the average monthly power bills for all residential, commercial and industrial customers as a group, and the overall average electric rate. It shows how the actual power bills have varied since 2000, and what they are projected to be out through the study period. Based on past trends, it was assumed that the number of residential customers would increase by 3 annually, and there would be an increase of 7 annually for the combined commercial and industrial sectors. In 2013 there were 3,714 customers in total. The red line depicts the average monthly power bill, which was $194 per month in The blue line shows the trend in the average electric rate. The average rate was 7.52 per kwh in As the graph clearly shows that rates and power bills are projected to increase 15% by the end of 2014, 13% in 2015, 4% in 2016 and 3% in 2017 (based on a recent financial study and expected board of trustee vote). These four annual rate increases will boost rates by 39% over the four-year period. Additional study will be required to determine if the rate increases will be different for different customer classes. Nevertheless, electric rates and bills in total are projected to increase by the proposed amounts. It should be noted that these rate increases are due to significant capital expenditures and other reasons and they were not caused by any of the proposed energy efficiency programs or renewable energy options evaluated in this study. Increases after 2017 were calculated by the consultants power supply and financial models to maintain a $1.5 million annual operating margin. Those increases after 2017 average 1.4% per year and are necessary to cover inflationary increases in fuel, utility labor, and maintenance costs. FIGURE 15 Average Monthly Power Bills (All Customers) $400 $350 $300 $250 $200 $150 $100 $50 $110 $ $ Average Monthly Power Bills & Electric Rates Scenario 1 Business As Usual (BAU) < History Future > BAU Bills BAU Rates Average Annual Electric Rate in Cents

41 Energy Independent Community Evaluation for the City of Algona, Iowa Page 36 If all of the energy efficiency programs are implemented over a 10-year period, then the customer kwh usage will go down. This is portrayed in Figure , ,000 FIGURE 16 Algona's Electricity Needs and Resources Scenario 2 EE Programs Only < History Future > MWH After More EE BAU MWh 2,400 2,100 MWh per Year 120, ,000 80,000 60,000 CO2 per MWh 1,800 1,500 1,301 1, Pounds of CO2 per MWh 40, , Wind Gen Solar PV Existing Engines Neal4, NIMECA Net Peak Demand CO2/MWh CO2 Target The energy efficiency programs would reduce the energy needs of the utility by 15% by the time they would all be fully implemented. This reduction in energy needs is shown by the black line in Figure 16. Since the energy efficiency programs reduce the kwh usage, they also reduce the annual peak demand. This reduction would be about 2.6 MW after full implementation of the programs. One key benefit of implementing the energy efficiency programs is the reduction in the CO 2 emission rate by 250 pounds per MWh, or 30% of the amount needed to attain the 1301 pounds per MWh goal.

42 Energy Independent Community Evaluation for the City of Algona, Iowa Page 37 The average monthly bills and electric rates are displayed in the graph in Figure 17 below for both the BAU scenario and this new scenario with the energy efficiency programs. The blue lines show that the average electric rates associated with the energy efficiency programs are a little higher than for the BAU scenario (solid blue line is higher than dashed blue line). Although rates are a little higher, power bills are less for customers The red lines show the power bills with the energy efficiency programs (lower red line) and for the BAU scenario (top dashed red line). Power bills would be less every year with the energy efficiency programs. At the end of the study period, the average power bill would be $343, which is $28 or 7.5% less than for the BAU scenario. All of this reduction is due to the fact that average usage for these customers has declined by 14%, because of the energy savings of the energy efficiency programs. Although rates average 0.8 per kwh higher on average over the 15-year period, there is a narrowing of the difference due to a decrease in spending on energy efficiency programs after the initial 10- year phase in period. During the 10-year period energy efficiency program spending was $405,000 per year above current energy efficiency program funding levels. After the 10-year period, spending dropped to $80,000 above current levels, hence the narrowing of the difference in electric rates. FIGURE 17 Average Monthly Power Bills (All Customers) $400 $350 $300 $250 $200 $150 $100 $50 $110 Average Monthly Power Bills & Electric Rates Scenario 2 EE Programs Only $371 $ $ < History Future > BAU Bills BAU Rates Average Annual Electric Rate in Cents In summary, implementing the energy efficiency programs achieves 30% of EPA s CO 2 reduction requirements, while saving customers and the utility money. The savings over 15 years totals $9.1 million for customers, and $8 million for the utility.

43 Energy Independent Community Evaluation for the City of Algona, Iowa Page 38 Section 11 Financial Impacts of the Low Renewables Scenario The financial impacts on the utility and the customers were analyzed for three penetration levels of local renewable energy. The three scenarios were designed to result in an ever increasing ratio of energy that was supplied locally, compared to the BAU scenario where essentially all of the energy was generated by Neal 4 or provided by NIMECA. The first scenario, called the Low Renewables relied on a combination of two 1.7 MW wind turbines totaling 3.4 MW, and 3.4 MW DC of solar PV arrays, along with all of the energy efficiency programs to eventually obtain 40,000 MWh of savings in energy needs from Neal 4 and NIMECA at the end of the study period. The solar PV used a combination of large arrays, both with a fixed- tilt mounting and with single-axis trackers, and rooftop solar panels on homes and businesses, totaling 3.4 MW DC. Using the 75% multiplier discussed above, the solar PV systems would have a 2.55 MW AC rating. It should be noted that 1 kw DC of solar PV generation generates about 1,000 kwh per year over its lifetime, whereas 1 kw of wind generation at Algona is assumed to generate about 4,000 kwh per year, based on using the GE model wind turbine. Therefore, wind generation puts out 4 times the energy per 1 kw of rating, compared to solar panels using their DC rating. The second scenario, called Medium Renewables, relies on four 1.7 MW wind turbines totaling 6.8 MW, and 9.6 MW DC of solar PV generation. Collectively with the energy efficiency savings, this scenario supplies about 61,000 MWh per year in savings at the end of 15 years. This would be enough to achieve the EPA proposed 1,301 pounds of CO 2 per MWh requirement. Collectively this saving would result in a 41% reduction in energy needs from coal-fired resources by the end of 15 years. With this much renewable energy capacity, it was projected that there would be less than 100 hours per year during sunny and windy days with mild weather when the renewable energy generation would exceed Algona s load. Over those few hours, Algona would actually export a total of 100 to 200 MWh per year to the grid. This represents less than 0.2% of Algona s annual energy needs. There was no monetary value given for these exports in this study. The renewable energy generation could easily be curtailed to avoid exporting power back to the grid. The third scenario is the High Renewables scenario, which assumes five 1.7 MW turbines totaling 8.5 MW, and 14.3 MW DC of solar PV. Collectively with the energy efficiency savings, this scenario supplies 50% of the BAU energy, or 74,000 MWh per year by With this much renewable energy capacity, there would be about 10,000 MWh of generation in excess of load annually during 500 hours of the year, with a maximum export of 10 MW to the grid. This excess generation represents 1.6% of Algona s annual needs in This third scenario represents the largest amount of renewable generation studied in this report. This amount was selected as being the maximum that would likely not start causing issues with the functioning of the NIMECA contract. Although NIMECA members can now export excess diesel generation to the grid during critical peak load periods, exporting during other hours was not anticipated in the design of the NIMECA contract. In all likelihood, many aspects of grid operation will change over the next 15 years to accommodate cleaner generating resources. It is technically feasible for Algona to get essentially all of its energy from local resources to become

44 Energy Independent Community Evaluation for the City of Algona, Iowa Page 39 net zero energy. However, it simply does not make economic sense given Algona s ownership share of a large, economic coal-fired power plant. Table 4 shows the amount of new local generating capacity in kw for each of the three renewable energy scenarios. The Solar PV capacity is in direct current kw, or kw DC. The typical AC rating was assumed to be 75% of those DC values. TABLE 4 New Local Generating Capacity in kw Used for the Low, Medium and High Renewable Energy Scenarios Year > Low Renewables Scenario Cumulative kw by Year Large Solar PV Fixed Tilt, kw DC ,120 1,120 Large Solar PV Tracker, kw DC ,120 Rooftop Solar PV, kw DC ,000 1,080 1,160 Wind Turbines 0 3,400 3,400 3,400 3,400 3,400 3,400 3,400 3,400 3,400 3,400 3,400 3,400 3,400 3,400 Total kw AC Capacity 30 3,520 3,648 3,843 4,000 4,195 4,390 4,585 4,780 4,975 5,170 5,365 5,560 5,755 5,950 Medium Renewables Scenario Cumulative kw by Year Large Solar PV Fixed Tilt, kw DC ,150 1,150 1,660 1,660 2,170 2,170 2,680 2,680 3,190 3,190 Large Solar PV Tracker, kw DC ,150 1,150 1,660 1,660 2,170 2,170 2,680 2,680 3,190 Rooftop Solar PV, kw DC ,210 1,430 1,650 1,870 2,090 2,310 2,530 2,750 2,970 3,190 Wind Turbines 0 6,800 6,800 6,800 6,800 6,800 6,800 6,800 6,800 6,800 6,800 6,800 6,800 6,800 6,800 Total kw AC Capacity 83 7,145 7,505 8,053 8,503 9,050 9,598 10,145 10,693 11,240 11,788 12,335 12,883 13,430 13,978 High Renewables Scenario Cumulative kw by Year Large Solar PV Fixed Tilt, kw DC ,730 1,730 2,500 2,500 3,270 3,270 4,040 4,040 4,810 4,810 Large Solar PV Tracker, kw DC ,730 1,730 2,500 2,500 3,270 3,270 4,040 4,040 4,810 Rooftop Solar PV, kw DC ,120 1,440 1,760 2,080 2,400 2,720 3,040 3,360 3,680 4,000 4,320 4,640 Wind Turbines 0 8,500 8,500 8,500 8,500 8,500 8,500 8,500 8,500 8,500 8,500 8,500 8,500 8,500 8,500 Total kw AC Capacity 120 9,003 9,528 10,345 11,020 11,838 12,655 13,473 14,290 15,108 15,925 16,743 17,560 18,378 19,195 Figure 18 illustrates the amount of renewable generation capacity to be installed by year. Generating Capacity in kw AC 12,000 10,000 8,000 6,000 4,000 2,000 0 FIGURE 18 Renewable Energy AC Generating Capacity Used in Scenarios by Years Wind Solar PV High Renewables Scenario Medium Renewables Scenario Low Renewables Scenario

45 Energy Independent Community Evaluation for the City of Algona, Iowa Page 40 In all cases with additional purchases of renewable energy it was assumed that Algona would hire one to three additional employees to help manage the operation of those resources, even though the solar and wind generation would be owned, operated and maintained by private third parties. The Low Renewables scenario had 1.5 full time equivalent (FTE) employees when fully implemented, whereas the Medium and High Renewables had 2.5 FTEs and 3 FTEs when fully implemented. The cost of these employees was included in the cost of the utility operations. The Low Renewables Scenario has a total of about 3.4 MW DC of solar PV generation added nearly linearly over the 15-year study period, with two wind turbines added in In this study, it was assumed that the utility would have contracts to buy all of this solar and wind power from private owners. Figure 19 on the following page shows the projected hourly loads during three periods of time in the last year of the study, when all of the wind and solar PV is projected to be installed. The top strip chart shows the peak week in 2029, which runs from July 15 through July 21. Based on the load pattern from the year 2011, the peak would be on Monday, July 18 th, and it would be 26,415 kw for the BAU scenario (top black dotted line) at 4:00 PM daylight savings time. Assuming all of the energy efficiency programs have been fully implemented by that year, the peak load would be reduced to 23,753kW (solid blue line). The solar PV generation for the that day in July for a Typical Meteorological Year (TMY) for the Algona area, shows the PV array generating 1,800 kw AC, and the wind turbines generating 275 kw during the peak hour. This solar PV generation is based on using about 2/3 fixed-tilt collectors and 1/3 single-axis tracking. The two wind turbines would generate an average of 1700 kw per hour over the course of the year, so they would be well below their typical output. The dark area above the wind and solar generation represents coal-fired energy from Neal 4 and NIMECA. The second strip chart graph shows the minimum load day in 2029, which would be the second week in May, based on the 2011 reference year. The minimum load was projected to be 6,703 kw after the energy efficiency program savings at 3 AM daylight savings time on that Sunday morning on May 8 th. The wind turbines would be at full power at that hour and the PV panels would, of course, be in the dark. The last strip chart shows a more normal load week in late April that would have a combination of sunny and cloudy days, with and without wind power. Wind generation that week would be about 20% more than average, and solar PV generation would be about 35% less than the annual average for the week.

46 FIGURE 19 Hourly Loads for the Peak Load Week, Minimum Load Week, and Typical Load Week in the Year ,000 Hourly Loads for the Peak Load Week in the Year 2029 Scenario 4 EE + Low Renewables Hourly Load in kw 25,000 20,000 15,000 10,000 5,000 Neal 4, NIMECA Solar Gen Wind Gen BAU Load Load with EE Export to Grid (5,000) 0 7/15 7/16 7/17 7/18 7/19 7/20 7/21 30,000 Hourly Loads for the Minimum Load Week in the Year 2029 Scenario 4 EE + Low Renewables Hourly Load in kw 25,000 20,000 15,000 10,000 5,000 Neal 4, NIMECA Solar Gen Wind Gen BAU Load Load with EE Export to Grid (5,000) 0 5/4 5/5 5/6 5/7 5/8 5/9 5/10 30,000 Hourly Loads for a Typical Load Week in the Year 2029 Scenario 4 EE + Low Renewables Hourly Load in kw 25,000 20,000 15,000 10,000 5,000 Neal 4, NIMECA Solar Gen Wind Gen BAU Load Load with EE Export to Grid (5,000) 0 4/25 4/26 4/27 4/28 4/29 4/30 5/1

47 Energy Independent Community Evaluation for the City of Algona, Iowa Page 42 Figure 20 illustrates how the various energy sources contribute to the annual energy needs during each year of the study period for the Low Renewables scenario. The green bars show the amount of wind generation in MWh, and the orange bars show the amount of solar PV generation. The diesel engine generation was assumed to only be 150 MWh per year, so it does not show up on the chart. During the last year of the study, the solar PV arrays would provide only about 3% of the remaining annual energy needs, while the wind generation would provide 11% of the net needs. 160, ,000 FIGURE 20 Algona's Electricity Needs and Resources Scenario 4 EE + Low Renewables < History Future > MWH After More EE BAU MWh 2,400 2,100 MWh per Year 120, ,000 80,000 60,000 CO2 per MWh 1,800 1,500 1,301 1, Pounds of CO2 per MWh 40, , Wind Gen Solar PV Existing Engines Neal4, NIMECA Net Peak Demand CO2/MWh CO2 Target

48 Energy Independent Community Evaluation for the City of Algona, Iowa Page 43 Figure 21 illustrates the impact of the Low Renewables scenario on the monthly customer bills and average electric rates. At the end of the study period, the average customer bill would be $344 per month, which would still be less than the BAU amount of $371. This represents a 7% savings. These savings are only $2 less per month than if only the energy efficiency programs were implemented. Therefore, adding this amount of renewable energy has very little impact on the customer bills. Compared to the BAU scenario, these customer bill savings total about $10.7 million over the 15-year study period. FIGURE 21 Average Monthly Power Bills (All Customers) $400 $350 $300 $250 $200 $150 $100 $50 $110 Average Monthly Power Bills & Electric Rates Scenario 4 EE + Low Renewables $371 $ $ < History Future > BAU Bills BAU Rates Average Annual Electric Rate in Cents In summary, it appears that adding 3.4 MW of solar PV and 3.4 MW of wind generation, along with incorporating the energy efficiency programs, can save customers $10.7 million over the 15-year period compared to the BAU scenario.

49 Energy Independent Community Evaluation for the City of Algona, Iowa Page 44 Section 12 Financial Impacts of the Medium Renewables Scenario The Medium Renewables Scenario has a total of 9.6 MW DC of solar PV generation, added nearly linearly over the 15-year study period. It also has four 1.7 MW wind turbines totaling 6.8 MW to be installed in Again, it was assumed that the utility would have contracts to buy all of this solar and wind power from private owners. Under this scenario, the use of Neal 4 and NIMECA power would be reduced by 41% of what they would be under the BAU scenario. Figure 22 on the following page shows the projected hourly loads during the peak load week, the minimum load week, and a typical load week in Again, the top strip chart shows the same peak week as before in The solar PV generation during the peak hour would be 5 MW, while the wind generation would only be 0.5 MW. The second strip chart graph shows the same minimum load day in 2029, which would be the first week in May. The wind generation would be at full output for most of the day. Assuming a sunny afternoon, the solar PV would add another 4 to 6 MW of generation, which would total more than Algona s load that afternoon. As a result, the 2 to 4 MW of excess renewable energy would be exported back to the grid during a 4-hour period. The last strip chart illustrates the same week in April that has a combination of sunny and cloudy days, and windy and still periods. The combination of solar and wind generation does a fairly good job of somewhat following the load during the week.

50 FIGURE 22 Hourly Loads for the Peak Load Week, Minimum Load Week, and Typical Load Week in the Year ,000 Hourly Loads for the Peak Load Week in the Year 2029 Scenario 5 EE + Medium Renewables Hourly Load in kw 25,000 20,000 15,000 10,000 5,000 Neal 4, NIMECA Solar Gen Wind Gen BAU Load Load with EE Export to Grid (5,000) 0 7/15 7/16 7/17 7/18 7/19 7/20 7/21 30,000 Hourly Loads for a Typical Load Week in the Year 2029 Scenario 5 EE + Medium Renewables Hourly Load in kw 25,000 20,000 15,000 10,000 5,000 Neal 4, NIMECA Solar Gen Wind Gen BAU Load Load with EE Export to Grid (5,000) 0 4/25 4/26 4/27 4/28 4/29 4/30 5/1 30,000 Hourly Loads for the Minimum Load Week in the Year 2029 Scenario 5 EE + Medium Renewables Hourly Load in kw 25,000 20,000 15,000 10,000 5,000 Neal 4, NIMECA Solar Gen Wind Gen BAU Load Load with EE Export to Grid (5,000) 0 5/4 5/5 5/6 5/7 5/8 5/9 5/10

51 Energy Independent Community Evaluation for the City of Algona, Iowa Page 46 Figure 23 illustrates how the various energy sources contribute to the annual energy needs during each year of the study period for the Medium Renewables scenario. The wind generation was modeled on an hourly basis, and the hourly patterns changed in each year of the study. However, the total amount was adjusted, so as to make the annual total wind generation match the median wind power projection. During the last year of the study the solar PV arrays would provide about 9% of the remaining annual energy needs, while the wind generation would provide 23% of the net needs. FIGURE , ,000 Algona's Electricity Needs and Resources Scenario 5 EE + Medium Renewables < History Future > MWH After More EE BAU MWh 2,400 2,100 MWh per Year 120, ,000 80,000 60,000 CO2 per MWh 1,800 1,500 1,301 1, Pounds of CO2 per MWh 40, , Wind Gen Solar PV Existing Engines Neal4, NIMECA Net Peak Demand CO2/MWh CO2 Target In the last year of the study there would be excess generation about 1% of the time, which totals 120 MWh. The maximum hourly export to the grid was projected to be 5 MW. The key advantage of this scenario is that Algona would meet EPA s Clean Power Plan CO 2 emission reduction requirements. As the graph shows, the red line slowly drops to the dashed red line target of 1,301 pounds of CO 2 per MWh. The slow decline is caused by the ramping up of the energy efficiency programs and the addition of more solar PV generation.

52 Energy Independent Community Evaluation for the City of Algona, Iowa Page 47 The customer bill impact of implementing the Medium Renewables scenario is illustrated in Figure 24. At the end of the study period, the average bill would be $346 per month, which is $2 more than the Low Renewables scenario, but $25 less than the BAU amount of $371. Again, this represents a 7% savings compared to the BAU scenario. Compared to the BAU scenario, these customer bill savings total about $10.0 million over the 15-year study period. Under this Medium Renewables scenario, the utility s operating cost would be $6.6 million less than the BAU scenario. However, it would be $2 million higher than simply implementing all of the energy efficiency programs. FIGURE 24 Average Monthly Power Bills (All Customers) $400 $350 $300 $250 $200 $150 $100 $50 $110 Average Monthly Power Bills & Electric Rates Scenario 5 EE + Medium Renewables $371 $ $ < History Future > BAU Bills BAU Rates Average Annual Electric Rate in Cents In summary, it appears that adding 9.6 MW DC of solar PV generation and 6.8 MW of wind generation along with the energy efficiency programs will allow Algona to meet the requirements of EPA s Clean Power Plan along with saving customers $10.0 million over the 15 year study period.

53 Energy Independent Community Evaluation for the City of Algona, Iowa Page 48 Section 13 Financial Impacts of the High Renewables Scenario The High Renewables Scenario has 14.3 MW DC of solar PV generation, which is about 5 MW more of solar PV than in the Medium Renewables scenario. It also has five wind turbines instead of four. This additional solar and wind generation reduces the need for Neal 4 and NIMECA power down to 50% of what it would have been under the BAU scenario. Again, all of the solar and wind power would be contracted from private owners, so as to take advantage of the state and federal income tax benefits. Figure 25 on the following page shows the projected hourly loads during the peak load week, the minimum load week and a typical load week in Again, the top strip chart shows the same peak week in The solar PV generation for the summer peak day would have 8 MW of output at the peak hour. Again, the wind turbines would contribute less than 1 MW at that time. The second strip chart graph shows the same minimum load day in 2029, which would be the first week in May. The wind generation would be at full output for most of the day and the solar PV would add another 7 MW of generation on that Sunday afternoon. This would result in 7 MW of excess renewable energy being exported back to the grid for about 4 hours that afternoon. The last strip chart illustrates the same week in April that has a combination of sunny and cloudy days, and windy and still periods. The combination of solar and wind generation results in some renewable energy exports to the grid during sunny and windy days. Over the course of the year, Algona would export power to the grid about 5% of the hours during the year with a total export of 1200 MWh to the grid, which represents about 1.6% of what it would use from Neal 4 and NIMECA. The maximum export would be about 10 MW. Of course, if the export caused contractual or operational problems, the renewable generation could be curtailed a little on those sunny and windy days with low electric loads. Curtailments would amount to only 2% of all solar and wind generation to eliminate any exports to the grid. The total renewable generation during 2029 was projected to be 52,000 MWh, which combined with the savings from the energy efficiency programs would replace 50% of the BAU energy needs.

54 FIGURE 25 Hourly Loads for the Peak Load Week, Minimum Load Week, and Typical Load Week in the Year ,000 Hourly Loads for the Peak Load Week in the Year 2029 Scenario 6 EE + High Renewables Hourly Load in kw 25,000 20,000 15,000 10,000 5,000 Neal 4, NIMECA Solar Gen Wind Gen BAU Load Load with EE Export to Grid (5,000) 0 7/15 7/16 7/17 7/18 7/19 7/20 7/21 30,000 Hourly Loads for a Typical Load Week in the Year 2029 Scenario 6 EE + High Renewables Hourly Load in kw 25,000 20,000 15,000 10,000 5,000 Neal 4, NIMECA Solar Gen Wind Gen BAU Load Load with EE Export to Grid (5,000) 0 4/25 4/26 4/27 4/28 4/29 4/30 5/1

55 Energy Independent Community Evaluation for the City of Algona, Iowa Page 50 Figure 26 shows the various energy sources meeting the total annual energy needs over the study period for the High Renewables scenario. During the last year of the study, the five wind turbines would provide 28% of AMU s net energy needs, while the solar PV arrays would provide 13%. This increased renewable energy drives the CO 2 emission rate below the 1,301 pounds per MWh Clean Power Plan requirement. 160, ,000 FIGURE 26 Algona's Electricity Needs and Resources Scenario 6 EE + High Renewables < History Future > MWH After More EE BAU MWh 2,400 2,100 MWh per Year 120, ,000 80,000 60,000 CO2 per MWh 1,800 1,500 1,301 1, Pounds of CO2 per MWh 40, , Wind Gen Solar PV Existing Engines Neal4, NIMECA Net Peak Demand CO2/MWh CO2 Target

56 Energy Independent Community Evaluation for the City of Algona, Iowa Page 51 The customer bill impact of implementing the High Renewables scenario is illustrated in Figure 27. At the end of the study period, the average bill would be $347 per month, which is again very nearly the same as for the Low and Medium Renewables scenarios. This results in a $26 per month saving for customers compared to the BAU amount of $371. Again, this represents a 7% savings over BAU. Compared to the BAU scenario, these customer bill savings total $9.3 million over the 15-year study period. FIGURE 27 Average Monthly Power Bills (All Customers) $400 $350 $300 $250 $200 $150 $100 $50 $110 Average Monthly Power Bills & Electric Rates Scenario 6 EE + High Renewables $371 $ $ < History Future > BAU Bills BAU Rates Average Annual Electric Rate in Cents In summary, incorporating 14.3 MW DC of solar generation and 8.5 MW of wind generation, along with the energy efficiency program energy savings, reduce the BAU scenario energy needs by 50%, while saving customers $9.3 million over the study period. The utility saves about $5.9 million in its operating costs, while still maintaining the same operating margin as it would have in the BAU scenario.

57 Energy Independent Community Evaluation for the City of Algona, Iowa Page 52 Section 14 Summary and Comparison of Results Table 5 provides a summary and comparison of the results of the financial analysis of all six scenarios. It provides the results from both the utility s perspective (green shading) and the customers perspective (yellow shading). From the Utility s perspective, its operating costs are lower than the BAU scenario for all of the other alternative six scenarios. This operating cost includes all costs except for nonoperating costs such as bond payments. The operating margins are essentially the same for all six scenarios. From the customers perspective, they save $9 to $11 million for all of the other six alternative scenarios over the 15-year period compared to the BAU scenario (Column 10). TABLE 5 Summary of Results from Financial Analysis of All Seven Scenarios Scenario Number Description Results from the Utility's Perspective Results from the Customers' Perspective Average Cost Over 15 Year Study Period Residential, Commercial and Industrial Customer Total Utility Operating Neal 4, Power Bills Over the 15 Year Period Costs Energy NIMECA, Solar PV Wind 15 Year Savings Monthly Bill Efficiency Diesels & Power Power Cumulative Total Compared to Savings Programs Total Savings Transmission of All Power Bills BAU Compared to BAU $1,000's $1,000's / kwh /kwh /kwh /kwh $1,000's $1,000's $ per Month Column Number Business As Usual (BAU) $ 196,260 $ $ 216,240 Reference Reference 2 Energy Efficiency (EE) Programs $ 187,970 $ 8, (EE Only) $ 204,920 $ 11,320 $16 (5.2%) 3 EE + Direct Load Controls $ 188,420 $ 7, (EE+DLC) $ 205,120 $ 11,120 $16 (5.1%) 4 EE Programs + Low RE (3.4 MW Solar PV MW Wind) $ 188,750 $ 7, (EE Only) $ 205,520 $ 10,720 $16 (4.9%) 5 EE Programs + Medium RE (9.6 MW Solar PV MW Wind) $ 189,650 $ 6, (EE Only) $ 206,270 $ 9,970 $14 (4.6%) 6 EE Programs + Low RE (14.3 MW Solar PV MW Wind) $ 190,380 $ 5, (EE Only) $ 206,910 $ 9,330 $14 (4.3%) Notes: The cost per kwh in Column 6 does not include the fixed ownership costs for Neal 4, such as bond payments, property taxes and depreciation. Columns 9, 10, and 11 do not include any out of pocket costs the customers would pay for energy efficiency improvements. These costs would average 19% of the savings.

58 Energy Independent Community Evaluation for the City of Algona, Iowa Page 53 Figure 28 shows how the power bills vary over time for each of the 7 scenarios. Monthly Average Power Bills in Dollars $400 $350 $300 $250 $200 $150 FIGURE 28 Algona's Average Monthly Power Bills Average of Residential, Commercial and Industrial Customers < History Future > BAU BAU Medium RE EE + DLC Low RE High RE EE Only $ It is a bit surprising that the costs to the customers for the all of the other alternative scenarios are all about the same, and they are all lower than the BAU scenario. The most cost-effective option is to implement an aggressive set of energy efficiency programs. If the energy efficiency programs are not implemented but then any of the three renewable energy scenarios are implemented, then the cost to the customers will be slightly higher than the BAU scenario. For example, the Low Renewables scenario without the energy efficiency programs would cost customers $1 more per month in 2029, while the Medium and High Renewables scenarios would cost $3 and $5 more per month respectively compared to the BAU scenario.

59 Energy Independent Community Evaluation for the City of Algona, Iowa Page 54 Figure 29 graphically illustrates how the different technologies are used to achieve the 27%, 41%, and 50% levels of energy independence, where local resources are used to supply Algona s electricity needs. The need for coal-fired generation is decreased as energy efficiency programs are implemented and as renewable energy generation is increased. 160,000 FIGURE 29 Sources of MWh Savings for Each Scenario for the Year ,000 Needed for BAU Annual MWh Needed 120, ,000 80,000 60,000 40,000 20,000 Neal 4 & NIMECA Purchases 27 % 41 % 50 % Neal 4 / NIMECA Solar Wind EE 0 BAU EE Low RE Medium RE High RE These are the primary benefits from pursuing any of these alternative scenarios compared to the BAU scenario: 1) Electric customers save money. 2) Electric power bills will escalate less in the longer-term future, because the cost of renewable energy is more stable than that from fossil fuels. 3) More money stays and circulates in the community, because of the home and business improvements fostered by the energy efficiency programs. 4) Several stable and good paying jobs are created to implement the energy efficiency programs and to operate the renewable energy facilities. 5) Air pollution and greenhouse gas emissions are reduced, since less energy is used and more of it is from renewable energy generation. The scenarios with energy efficiency and medium or high renewable energy deployment would allow Algona to meet the U.S. Environmental Protection Agency s proposed Clean Power Plan.

60 Energy Independent Community Evaluation for the City of Algona, Iowa Page 55 There are other community-wide economic impact benefits of these alternative scenarios. However, they would require some additional analysis. Nevertheless, the table below summarizes some of the key factors that affect the overall economic impact on the community. The yellow shaded area shows how the alternative scenarios compare to the BAU scenario. For example, the right-hand column on the top line in yellow shading shows that $43,697,000 less will be spent on power costs from Neal 4 and NIMECA for the High Renewables scenario compared to BAU. This $44 million savings would be used to pay for local renewable energy, energy efficiency investments, additional local employees, and to reduce customers power bills. TABLE 6 Measures of Economic Activity Cumulative Sums Over 15 Years in $1,000's Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Scenario 6 BAU EE Only EE + DLC Low RE Med. RE High RE Total Cost of Neal 4 & NIMECA Purchases & Sales $ 121,479 $ 108,758 $ 108,523 $ 97,199 $ 84,791 $ 77,781 Additional Employee Wages & Benefits $ $ 1,406 $ 1,406 $ 2,974 $ 3,771 $ 4,271 Energy Efficiency Investments by Customers $ $ 543 $ 543 $ 543 $ 543 $ 543 Local Renewable Energy Purchased $ $ $ $ 10,767 $ 23,278 $ 30,521 Customers' Power Bills $ 219,550 $ 208,474 $ 208,680 $ 209,086 $ 209,854 $ 210,499 Changes in Values Compared to BAU, in $1,000's Total Cost of Neal 4 & NIMECA Purchases & Sales Reference $ (12,720) $ (12,956) $ (24,279) $ (36,687) $ (43,697) Additional Employee Wages & Benefits Reference $ 1,406 $ 1,406 $ 2,974 $ 3,771 $ 4,271 Energy Efficiency Investments by Customers Reference $ 543 $ 543 $ 543 $ 543 $ 543 Local Renewable Energy Purchased Reference $ $ $ 10,767 $ 23,278 $ 30,521 Customers' Power Bills Reference $ (11,076) $ (10,870) $ (10,465) $ (9,696) $ (9,051) This $44 million savings and its reinvestment in the local community also have multiplier effects that increase other business activity. For example, the private sector capital investment in the local renewable energy generation equipment is projected to be $50 million in the High Renewables scenario. The construction of these facilities alone will involve perhaps 20 manyears of local construction work. This economic benefit is not shown in the above table. Some of the investment for the renewable energy facilities could come from local area investors, if AMU specified that desire in the planning and procurement process.

61 Energy Independent Community Evaluation for the City of Algona, Iowa Page 56 Figure 30 provides a pictorial diagram illustrating the cumulative additional flows of cash over the 15-year period for the High Renewables scenario discussed above. FIGURE 30 Evaluating the overall economic impact of these changes in cash flows is beyond the scope of this study, but would not be difficult to do.

62 Energy Independent Community Evaluation for the City of Algona, Iowa Page 57 Section 15 Uncertainties and Limitations Any engineering and financial analysis that projects out into the future depends upon many assumptions about the future. The most important economic factors for this study are the future costs of Neal 4 and NIMECA power, and the cost of renewable energy. The cost for Neal 4 power should be fairly stable now that the scrubber has been added. However, there may be additional costs for carbon emissions in the longer term if the US is going to seriously address climate change. The Clean Power Plan might be just the first of many regulations concerning carbon emissions and each will likely be more restrictive, which will increase the cost of coal-fired generation. There were no specific costs such as a carbon tax used in this study. If additional emission regulations or a carbon tax were implemented, then the economics would improve for both the energy efficiency programs and the renewable energy options. Since the economics of the energy efficiency programs are strong, it is unlikely that the economics of the energy efficiency programs will be impacted by changes in power supply costs. Of course, if power supply costs escalate more than projected, the economics of the energy efficiency programs will improve. At 2.1 per kwh, energy efficiency will be less expensive than any other option. Another uncertainty is whether the federal and state governments will continue to provide some level of subsidy to renewable energy. The federal government provides a 30% investment tax credit for solar through the end of The 10-year 2.3 per kwh federal production tax credit has lapsed for new wind projects, and must be renewed again for wind power to be economically feasible for Algona. There is a reasonable chance that Congress will renew this tax credit for one more 2- to 3-year period of time. Renewal after that is questionable. Iowa s 10-year 1.5 per kwh state tax credit is available for a couple more years, too. This tax credit is also economically necessary for AMU to use locally generated wind power. Because there is always some uncertainty about the future availability of these subsidies, it may be beneficial to commit to renewable energy projects while the tax credits are known to be available, rather than risking paying a higher price later on, when there are less or no tax credits. This is especially true of wind power. This is the reason the wind turbines were always added in the early years of the study. If the federal subsidy expires, the cost of local wind power will be about 1.5 per kwh higher. Because of the limited time and resources allowed for this study, an evaluation of Algona s distribution system to absorb the renewable energy was not made. However, it was assumed that a kv or higher voltage dedicated collection circuit going to one of the substations would be needed for the additional wind generation. Some allowances for these costs were included in this study, but it is not known if the allowances are enough. There is some uncertainty with the coincidence of the solar PV output with the utility s load. The solar PV output data used in this study was based on the Typical Meteorological Year (TMY) data compiled by government-supported researchers. They analyzed the solar incidence data on a monthly basis to determine a typical representative month. This TMY monthly data used in this analysis is not synchronized with the utility loads. Therefore, it is not known if the solar PV output is too high or too low on those hot and humid summer days when air

63 Energy Independent Community Evaluation for the City of Algona, Iowa Page 58 conditioners cause high utility loads. Although personal observations suggest the sun is shining on those days, some additional analysis is needed to refine the modeling technique. It should be noted that the hourly wind production data from Algona is synchronized with the hourly load data from Algona. Since all of this data was used as a starting basis for this study for AMU, the wind power output on an hourly load basis should be realistically modeled. Another assumption surrounded by uncertainty is that there were no costs assumed for integrating the renewable energy into Algona s power supply arrangements. With the High Renewables scenario, the solar and wind generation would collectively provide about 42% of Algona s remaining needs in With this high of penetration of variable generation, NIMECA may possibly incur additional costs that could be passed on to Algona. However, there is little known about potential integration costs in Algona s particular situation.

64 Energy Independent Community Evaluation for the City of Algona, Iowa Page 59 Section 16 Observations The results of this study clearly indicate that starting an aggressive energy efficiency program will save utility customers money. Furthermore, there is little doubt that incorporating some level of wind generation is likely to save customers money in the long run as other power costs go up. Wind generation tends to reduce power bills, while solar PV generation tends to increase them a little. However, a combination of the two was used in this study to better match Algona s load profile. Solar PV generation always occurs during business hours when loads are higher. The solar and wind power cost estimates used in this study for the next three years or so are likely to be conservative, but longer-term price trends are uncertain. Therefore, evaluating the benefits of adding some renewable energy in the next few years will not be too difficult, since the Neal 4 and NIMECA power supply costs are relatively stable and predictable over the next few years. Making the decision to add renewable energy should be relatively easy and straightforward. If the utility does want to move forward with any of these options, then it should consider incorporating wind power in the next couple of years, because of possible expiration of future government subsidies. If they expire, the near-term economic feasibility for using wind power from a small locally-owned wind farm may disappear. Fortunately the utility does not need to make a decision on which of the three renewable energy scenarios to implement. The results show that all of the renewable energy scenarios have about the same impact. Therefore to start the plan, the utility simply makes the decision to add one solar PV array at a time or a couple of wind turbines. After that the utility can decide whether to proceed (or to stop) with more arrays and wind turbines. Battery energy storage was not deemed to be economic in this study, because of the particular terms of the NIMECA contract. Furthermore, there is little difference in cost between the onpeak and off-peak periods. A large difference in price between the on- and off-peak periods is needed to justify battery storage. If AMU s future power supply arrangements better reflect market prices, then energy storage may become economical before the end of the 15-year study period, since battery prices are projected to decline. If the City is concerned about local economic growth, then it should evaluate the economic benefits that adopting one of the aggressive renewable energy scenarios would bring. It should then take these benefits into consideration when making any decisions about whether to pursue any of these alternative scenario strategies. Although nearly all utilities in Iowa have some renewable energy in their power supply, no Iowa or Midwest utility has yet attempted to get a majority of its needs from solar and wind power. As a result, this effort will require some further analysis and planning. Since AMU would be forging a new path, there will likely be some unanticipated issues that will have to be addressed as they arise over time. There is no doubt that any of these alternative scenarios can be accomplished.

65 Energy Independent Community Evaluation for the City of Algona, Iowa Page 60 Section 17 Other Considerations Under all of the alternative scenarios customers would pay lower bills, but rates per kwh would be higher primarily because fewer kwhs would be sold. What this really means is that customers who take advantage of energy efficiency programs would pay less. Renters and those who lack the means to capture efficiencies in their use of energy may end up paying a little more. There are several things AMU can do to mitigate that risk. a) Successful energy efficiency programs require professional staff committed to that success. This study assumes funding for two full-time energy efficiency employees and additional contract personnel. Efficiency goals for rental properties and low-income housing should be made a priority for these personnel. b) The City should consider adopting minimum standards of energy efficiency for rental housing. IAMU has a model ordinance that requires broken windows to be replaced and cracked ones replaced or taped. It requires basic weatherization measures (repair of cracks, gaps, or other holes in the building envelope) that allow significant air infiltration. It also requires minimum standards of efficiency, based on the age of the refrigerator. c) Grant funding could be sought to hire a summer intern, who would merge basic information about the size and type of buildings from the county recorder s web site with energy usage from utility records to create an index of building efficiency. Such indices rank buildings on the basis of energy use in British Thermal Units (Btu) per square foot. The index helps the energy efficiency professionals to find and direct program dollars to the least efficient buildings and systems, to capture the greatest efficiencies for the lowest investment. d) The City could provide opportunities for renters and for homeowners who do not have good solar access to invest in community solar projects. As described elsewhere in this report, community projects offer economies of scale and allow customers to match their investment in renewables to their own budgets. Thomas A. Wind, Wind Utility Consulting, PC Joel Logan, Iowa Association of Municipal Utilities Bob Haug, Iowa Association of Municipal Utilities August 29, 2014

66 Appendix 1 Information on the Economics of Energy Efficiency Programs Page 1

67 Appendix 1 Information on the Economics of Energy Efficiency Programs Page 2

68 Appendix 1 Information on the Economics of Energy Efficiency Programs Page 3

69 Appendix 1 Information on the Economics of Energy Efficiency Programs Page 4