Validation of Demand Management Investigations

Transcription

1 Validation of Demand Management Investigations ST GEORGE AND SUTHERLAND AREA Final Report 19 September 2006

2 Validation of Demand Management Investigations ST GEORGE AND SUTHERLAND AREAS Final Report 19 September 2006 Sinclair Knight Merz ABN Christie Street PO Box 164 St Leonards NSW Australia 1590 Tel: Fax: Web: COPYRIGHT: The concepts and information contained in this document are the property of Sinclair Knight Merz Pty Ltd. Use or copying of this document in whole or in part without the written permission of Sinclair Knight Merz constitutes an infringement of copyright. LIMITATION: This report has been prepared on behalf of and for the exclusive use of Sinclair Knight Merz Pty Ltd s Client, and is subject to and issued in connection with the provisions of the agreement between Sinclair Knight Merz and its Client. Sinclair Knight Merz accepts no liability or responsibility whatsoever for or in respect of any use of or reliance upon this report by any third party.

3 Executive Summary SKM has been engaged by the Demand Management and Planning Project (DMPP) to review and verify the results of a number of studies carried out into the potential for Demand Management (DM) to reduce electricity network peak demands in the St George Sutherland area of Sydney. A number of activities to determine the DM potential in St George Sutherland were carried out. These are: A desktop analysis of Power Factor Correction Level 1 initial site investigations of 125 major sites covering opportunities in: Energy efficiency Power Factor Correction Load shifting and interruptability Standby Generation Cogeneration and fuel switching Follow-up customer feedback of sites seeking customer response to the program Level 2 detailed site investigations of several sites to verify high potential opportunities identified in the Level 1 investigations. Facilitation and financial assistance of 2 demonstration projects Level 1 site investigations were conducted at each of the 125 sites, to identify opportunities for demand reduction, and provide initial indicative (±40%) estimates of the size and cost of these opportunities. Follow-up Level 2 investigations were conducted in more detail, to achieve an indicative (±20%) estimates of the size and cost, followed by The findings of each of these phases are summarised in the sections below. Level 1 investigations Level 1 investigations were the primary source of data for demand reduction opportunities in St George Sutherland, as they included every site that participated in the study. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE i

4 A total of 44 MVA of peak (summer) demand reduction were identified. Of these opportunities, 7.5 MVA were considered to have very attractive (<2 yrs) or attractive (<4 yrs) financial paybacks. Peak demand reduction (kva) 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2,000 Summary of Level 1 findings Unknown Uneconomic Unattractive Attractive Very attractive - Alternate fuel (fuel switching) Energy Efficiency Load shifting Power Factor Correction Standby generation Action category The greatest savings were identified in the Industrial sector (16 MVA / 3.4 MVA attractive), followed by Retail (7 / 1.5 MVA), Hospitality (4.5 / 0.9 MVA) and Health (8 / 0.3 MVA). These results largely reflect the mix of loads in St George Sutherland. Level 2 investigations Level 1 results were used to identify and target a number of sites for more thorough Level 2 investigations, in order to determine the technical practicality and viability of identified opportunities, and develop more accurate cost and savings estimates to within ±20%. The movement in demand reduction and capital cost of opportunities sampled for Level 2 investigation is shown in the table below: Action category Level 1 Level 2 All kva Attractive kva Average cost ($/kva) All kva Attractive kva Average cost ($/kva) Comparison (L2 result as % of L1 result) All kva Attractive kva Average cost Energy efficiency 4,958 2,698 $1,398 2, $3,547 53% 8% 254% Power Factor Correction 7,325 4,659 $157 7,950 4,213 $ % 90% 113% Standby generation 15,727 6,020 N/A 12,122 3,600 $509 77% 30% N/A Load shifting 10,205 8,257 N/A $249 4% 2% N/A Fuel switching 5, $1,229 4, $2,812 80% 15% 229% Total 44,083 21,823 $347 17,270 8,466 $758 39% 16% 219% Total demand of surveyed sites 86,635 % demand reduction 51% 25% 20% 10% Level 2 investigation results generally found the size of demand reductions for opportunities were less than those estimated from Level 1 investigations, and the implementation costs higher. The exception was Power Factor Correction, where it was found that Level 1 estimates, and even I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE ii

5 desktop estimates, were reasonably accurate in terms of both size of demand reduction and implementation cost. When results from the small sample of Level 2 investigations are applied to all Level 1 results, the total demand reduction potential falls from 44 MVA to 17 MVA, while the financially attractive potential falls from 22 MVA to 8.5 MVA. Overall, both the amount and attractiveness of opportunities dropped as a result of the Level 2 verification of Level 1 results. This is demonstrated in the chart opposite, showing a comparison of Level 1 and Level 2 results for Energy Efficiency. Peak demand reduction (kva) Comparison of Level 1 and Level 2 Investigation results Energy Efficiency Unviable Uneconomic Unattractive Attractive Very attractive Level 1 Level 2 Investigation The conclusions that can be reached from this analysis of Level 2 results compared to Level 1 results are: Level 1 investigations are useful for identifying potential opportunities, and for targeting further investigations Results of Level 1 audits contain significant uncertainty, and should be treated as indicative only Based on the sample of Level 1 and 2 investigations in St George Sutherland, there appears to be a systemic bias towards optimistic results from Level 1 investigations. Facilitation and implementation DMPP facilitated a number of implementation projects, coupled with cost subsides in some cases, in order to provide demonstration and case study projects, and also to understand the issues and costs associated with project facilitation. It was found that facilitation costs and timelines were both high, and in some instances significant resources were applied to potential projects that were not subsequently implemented. Examples include: A multi-unit domestic lighting efficiency demonstration project, where it was found the lower wattage high-efficiency lamps did not produce adequate light levels to meet Australian I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE iii

6 Standards. DMPP had invested 9 months and $6,000 in facilitation for the project, which was ultimately abandoned. A number of opportunities in the clubs sector were followed up, with meetings with club management taking 3 months and $8,000, plus $4,000 for Level 2 investigations, before it was determined the site management did not consider the projects sufficiently attractive to warrant implementation. An ice-storage demonstration project, where facilitation and follow-up took longer than 12 months, and cost as much as the (small) project itself. This projects was successfully implemented. Additional measurement and verification costs were also incurred, related to a desire by DMPP to use the project as a case study, and also to reassure the site management. SKM considers these examples are not atypical of DM project facilitation, which typically requires a high degree of interaction, assistance and follow up with potential sites in order to successfully bring projects to fruition. A significant number will pull out part way through the process. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE iv

7 Total cost of Demand Management The total implemented cost of DM opportunities was assessed, including the following cost components: Identification of potential opportunities (Level 1 investigations) Verification of potential opportunities (Level 2 investigations) Facilitation (DM Program costs) Implementation (capital cost of actual DM measures) Internal costs (management and other costs incurred by the participant) These results are shown in the table and chat below: DM Action category Identification Verification Facilitation DM Measure Capital Internal transaction Total Total % of DM Measure Capital Energy efficiency $239 $1,249 $267 $4,925 $267 $6, % Power Factor Correction $12 $55 $15 $164 $15 $ % Standby generation $14 $8 (1) $100 $254 $100 $ % Load shifting $125 $125 $1,200 $124 $1,200 $2, % Fuel switching $1,145 $286 (1) $267 $2,800 $267 $4, % Total $30 $43 $179 $323 $179 $ % As can be seen from these results, other costs such as identification, verification, and facilitation are significant, and can be of the same order as the measure capital costs on average. Average cost / kva $8,000 $7,000 $6,000 $5,000 $4,000 $3,000 $2,000 Total cost of DM Options Internal transaction Measure Capital External Facilitation Verification Identification $1,000 $- Energy efficiency Power Factor Correction Standby generation Load shifting DM Action Category Fuel Switching Average SKM notes that the objective of DMPP was to gather data and assess the cost and potential of DM, rather than seek out least cost DM measures, and hence more targeted DM programs aimed at achieving least cost reductions should be able to reduce overhead costs as a percentage of capital cost. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE v

8 Based on avoided distribution costs in the order of $100 - $200 / kva value created through deferral of network investments, it appears that only the full range of PFC and Standby generation options would be likely to be cost effective. Other very attractive opportunities from the other categories could also be cherry picked. These results should be interpreted with caution, and not necessarily taken as representative of the cost of DM in all instances. Firstly, the focus of the DMPP is to investigate the potential and cost of DM, not necessarily to seek out the least cost DM measures. Given the limited experience in the implementation of DM programs, these results can be considered to be part of a process of learning by doing, which will hopefully lead to better understanding of successful approaches and ways of improving the delivery and execution of DM programs in the future. Given the lack of thorough DM program evaluations in Australia, these results provide a useful baseline of the practical potential and costs of DM, and also the time taken to facilitate and implement DM projects. Barriers to the uptake of DM measures Discussion with site management and facility managers identified a number of potential barriers to the adoption of DM projects. These included Few users had an appreciation of options to reduce peak demand, but were more familiar with traditional energy saving measures. Projects did not meet financial payback criteria, typically of a 2-3 year simple payback. The ability to prepare an internal business case or capital funding submission was often identified as lacking at the site level, and was identified as a potential barrier even when opportunities fell within hurdle rate criteria. Assistance in preparing a business case was seen as a possible solution that would be taken up at a number of sites. Likewise, the ability to prepare a technical specification in order to seek quotes for implementation was often identified as lacking at the site level, and was identified as a potential barrier. Assistance in preparing a technical specification was seen as a possible solution. Most businesses had an environmental or sustainability policy, but this was not seen as being a sufficient driver to justify investments in energy or demand saving opportunities. A number organisations, mostly local government, had developed revolving finance funds for energy efficiency investments, that involved initial seed funding, with the fund replenished from savings accrued from implemented measures. These organisations were generally the most progressive in seeking and implementing energy and demand reduction opportunities. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE vi

9 A number of technical barriers were identified, often related to specific technologies. For example, lack of room in the switchboard for PFC, or protection and fault rating issues for standby generators. Such barriers are often not identified during Level 1 audits. Load shifting and interruptability opportunities can have a high degree of inconvenience for the business, with costs such as reduced service to their customers, staffing and overtime issues, and potential noise issues if production is shifted to night shift. Process DMPP have identified a number of potential improvements based on the St George Sutherland study, including the need for standardised data capture, improved customer feedback, and better definition of the need to focus on peak demand reductions (as opposed to energy savings which are the traditional target of energy audits). These improvements have been implemented in subsequent studies being conducted by DMPP, and should improve the results and accuracy of the data. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE vii

10 Contents Executive Summary Introduction The Demand Management and Planning Project St George Sutherland Demand Management Investigations Demand Management 3 2. Assessment of Demand Management Investigations and Findings Customer feedback results 6 3. Characteristics of St George Sutherland loads and DM opportunities Summary and conclusions Energy Efficiency measures Level 1 Investigations Lighting efficiency options HVAC efficiency options Level 2 Investigations Facilitation and Implementation projects Warehouse lighting dimming project Multi-unit Residential lighting dimming project Lighting and HVAC projects at Clubs Power Factor Correction Desktop Investigations Level 1 Investigations Level 2 Investigations Implementation projects Standby Generation Level 1 Investigations Level 2 Investigations Implementation projects Load Shifting and Interruptible Load Level 1 Investigations Level 2 Investigations Implementation projects Cogeneration and Fuel Switching Level 1 Investigations Level 2 Investigations Implementation projects Total cost of Demand Management Conclusions and Recommendations...62 Appendix A DMPP Conditions of Consent...64 Appendix B AS3598 Energy Audits definitions...66 I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE viii

11 Document history and status Revision Date issued Reviewed by Approved by Date approved Revision type A 7 July 2006 B Kearney Progress draft 1 27 July 2006 B Kearney P Adams Final draft 2 29 Sept 2006 B Kearney P Adams 29 Sept 2006 Final Distribution of copies Revision Copy no Quantity Issued to A 1 1 C Tully C Tully Chris Tully, DMPP Printed: 29 September 2006 Last saved: File name: Author: Project manager: Name of organisation: Name of project: Name of document: Document version: Project number: 21 September :30 PM St George verification report final report.doc Ben Kearney Ben Kearney Demand Management & Planning Project Validation report into Demand Management Investigations Report Final Report HA00831 I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE ix

12 1. Introduction SKM has been engaged by the Demand Management and Planning Project (DMPP) to review and verify the results of a number of studies carried out into the potential for Demand Management (DM) to reduce electricity network peak demands in the St George Sutherland area of Sydney. 1.1 The Demand Management and Planning Project The Demand Management and Planning Project was established as a result of Conditions of Consent placed on the MetroGrid project to enhance the electricity network supplying Sydney. These Conditions include requirements to investigate demand management potential, via initiatives such as power factor correction, energy efficiency, distributed generation, standby generation and load curtailment. 1.2 St George Sutherland Demand Management Investigations DMPP has undertaken a number of studies in the St George Sutherland area to investigate the DM potential in this area. These studies are: A desktop study of Power Factor Correction potential (covering the entire Sydney region) Level 1 initial site investigations 1 of 125 major sites in St George Sutherland, identifying potential demand reduction opportunities under the following categories: Energy efficiency Power Factor Correction Load shifting and interruptability Standby Generation Cogeneration and fuel switching Follow-up customer feedback of sites seeking customer response to the program Level 2 detailed site investigations of 15 sites to verify high potential opportunities identified in the Level 1 investigations. Detailed investigation by generator specialists of 6 high potential standby generator opportunities identified in the Level 1 investigations Detailed investigation at 10 sites of high potential load shifting and interruptability opportunities identified in the Level 1 investigations Facilitation and financial assistance of 2 demonstration projects 1 A site investigation is similar to an energy audit, but with peak demand reduction as the primary focus, rather than energy savings that are typically the focus of energy audits. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 1

13 In addition to studies specifically carried out for St George Sutherland, SKM was also provided with details of Power Factor Correction implementation programs carried out by EnergyAustralia which have been used to estimate the potential uptake of PFC. The purpose of this report is to pull together the results of these separate studies in order to verify the findings and identify outcomes that are not apparent from the studies viewed individually, capture hidden costs and business drivers that can lessen the uptake of DM opportunities. Figure 1 St George Sutherland study area I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 2

14 This report presents the results of investigations carried out at 125 sites within the Sutherland and St George region of Sydney to identify the potential for reducing demand for electricity. This study covers the Local Government Areas of Sutherland, Kogarah, Hurstville and Rockdale, and includes sites with demands ranging from 150 kva to 5 MVA. Typical site types in this range would be from a small business, to a medium sized hospital or manufacturing site. 1.3 Demand Management The term Demand management is often loosely defined, and suffers from poor or conflicting definition which is in part responsible for the confusion regarding its scope and potential. The definition also depends on the drivers and objectives being addressed. For the purpose of this report, the definition of DM includes the following broad characteristics: DM is a focussed and deliberate intervention to change consumer energy-use behaviour The objectives are to optimise the supply and use of energy (often in response to environmental concerns or market failures) A DM program or project has clear justification, objectives and targets DM can impact consumption through changing behaviour (such as turning off the lights when not required) or by changing equipment (such as installing more efficient lights). Not all sales or installations of efficient equipment are DM. A DM program may seek to increase the uptake of certain technologies, but the use of these technologies outside of a DM program is simply an appropriate energy choice or business as usual. DM seeks to manage energy demand, as an alternative and counterbalance to energy supply The generally accepted definition is predominantly focussed on end-use applications DM includes energy efficiency, peak lopping, peak shifting and fuel substitution of loads (and also load building, though this is usually at odds with the objectives of DM) Embedded generators can sometimes achieve DM outcomes, and may be considered alongside DM options to arrive at an overall optimal solution. Cogeneration (the simultaneous production of two forms of energy, usually electricity and heat) in particular is attractive because it can improve end-use efficiency and also reduce network loads. In practical terms, DM is usually undertaken by a body such as a utility or government funded organisation to optimise the overall efficiency and benefits of energy supply and use. This is generally through targeted programs that include planning, investigation and identification of opportunities, mechanisms to influence end-use, and evaluation of program outcomes. Pricing can also be used as a DM tool, both the absolute cost of energy, and also the structure of energy tariffs (such as time-of-use varying costs, or peak demand charges). For the purpose of this report pricing is taken as a fixed or business as usual parameter, and it is assumed that current tariffs are cost reflective and provide appropriate signals to end-users. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 3

15 The DMPP was established in response to the cost and impacts of electrical network infrastructure expansion resulting from growth in peak network loads, to determine the scope of DM to reduce network investments in the future. As a result, this report focuses primarily on the scope of DM to reduce network peak loads. Electricity peak loads in the Sydney area have for some years been occurring in the summer months, usually on hot days when increased air-conditioning loads add to other non temperature dependent loads. For this reason, summer daytime peak demand is the key measure chosen to represent the impact of DM. Other benefits of DM, such as reduced energy costs and greenhouse gas emissions, are largely a function of reducing the amount of energy consumed, which may or may not accompany a reduction in peak summer demand. For example, switching off the lights in an office building at night will save energy, but not reduce the daytime peak demand. These other DM impacts, including winter peak demand, energy and end-user energy cost savings are also discussed in this report, but are not the primary focus. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 4

16 2. Assessment of Demand Management Investigations and Findings The primary sources of data used in compiling this report are Level 1 and 2 investigations commissioned by DMPP. In addition, DMPP sought customer feedback on all sites that received a Level 1 investigation, and has undertaken a small number of implementation projects to confirm investigation results. Definition of the Level 1 investigations is: an investigation similar to a Level 1 energy audit as per Energy Audits, Australian/New Zealand Standard AS/NZS 3598:2000, but with a focus upon the identification of alternatives for reducing peak electricity demand. In practice, a Level 1 investigation is a high level overview, commonly called a walk through audit typically conducted over a half to full day on site only, with cost and savings estimates based on factoring or rule of thumb estimates. It is intended to identify potential opportunities and give an indicative (±40%) estimates of costs and savings, so as to target further more detailed investigations. Level 2 investigations are more detailed assessments of demand reduction opportunities, to verify the technical feasibility of the project, and improve cost and savings estimates to within ±20%. Uncertainty in cost and savings estimates Level 1 audits were walkthrough audits only, with an expected ±40% level of uncertainty, in order to keep the cost of 125 audits reasonable. Level 2 audits were more thorough, focussing only on those opportunities identified in the Level 1 audit as being attractive, and are expected to have a ±20% level of uncertainty. SKM notes these levels of uncertainty, while they may appear high, are reasonable and realistic. Typical accuracy levels of various generic study types are summarised in the table below: Estimate type (DMPP activity) Pre-feasibility (Level 1 audits) Feasibility (Level 2 audits) Budget (Facilitation) Construction (Implementation) Estimation Methods Concept design, rule of thumb costs and factoring Preliminary design, factoring with some quotes and quantity take-off Detailed design & equipment specs, detailed quotes, limited factoring Detailed design and specs, firm quotes for major items Typical Uncertainty ±35% ±25% ±15% ±5-10% In order to validate the demand management investigations and results, SKM has conducted the following analysis: Review of Level 1 investigation findings, and analysis of this data to identify trends I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 5

17 Review of the results of customer feedback of sites following delivery of Level 1 investigation reports Comparison of Level 2 investigation results with the corresponding Level 1 investigation findings, to verify the accuracy or degree of error between the two studies, and analysis of these results to identify overall trends Comparison of Implementation results with earlier (Level 1 or 2) investigation findings, to verify the accuracy or degree of error between forecast and actual costs and savings. Review of total cost of implementation, including opportunity identification (Level 1 and/or 2 investigations), actual project costs, financial assistance, and facilitation costs. In the case of Power Factor Correction (PFC), comparison of Level 1 investigation results with an earlier desktop study of PFC costs and impacts, and with implementation projects undertaken by EnergyAustralia. 2.1 Customer feedback results Following completion of Level 1 investigations and delivery of investigation reports to each individual site, DMPP sought customer feedback of participating sites via telephone to determine: Their initial impression of the investigation Whether they had read and considered the investigation report and recommendations Their intentions with regard to implementation of recommended options Whether they were interested in receiving further assistance from DMPP. These results were also used by DMPP to assess and target sites for follow up and further action, including Level 2 investigations, and consideration for implementation assistance. These surveys were the first time DMPP had conducted follow up surveys, and were trialling the questionnaire and data capture methods. A review of the survey method and results has resulted in a number of improvements to be implemented for future surveys, including: More focussed questionnaire, including greater emphasis on barriers to uptake Development of a database to capture survey results, integrated with investigation results Structuring survey capture data to facilitate improved analysis of results In the case of the St George Sutherland, limited information was able to be extracted from the surveys. SKM considers the improvements identified will significantly improve the ability to analyse future surveys and extract information. From the St George Sutherland customer feedback surveys, the following results were achieved: Of 91 sites contacted, 89 agreed to participate in the survey, with only 2 refusals I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 6

18 At 74 sites (83%) the contact remembered reading the report (in other cases, the report may have gone to another person at the organisation, or not been read). At 50 sites (63%) the report was read by senior management at the site 105 / 338 (31%) of identified opportunities (with multiple opportunities at some sites) had already been implemented** 47 / 338 (14%) of identified opportunities were intended to be implemented 186 / 338 (55%) of identified opportunities were not intended to be implemented for the following reasons: Inability to secure funding (9 = 3%) High payback period (38 = 11%) Not a high priority (20 = 6%) Not core business (8 = 2%) Do not understand the opportunity (1 = 0.3%) Other reasons (110 = 33%) 26 sites (32%) were interested in receiving further assistance Note ** The incidence of implemented opportunities is inconsistent with SKM s understanding of typical levels of implementation. SKM considers this figure is likely to significantly overstate the actual number of opportunities implemented. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 7

19 3. Characteristics of St George Sutherland loads and DM opportunities The St George Sutherland study considered 148 sites in the St George Sutherland area with a maximum demand above 150 kva and less than 5 MVA (which are the subject of a separate study by DMPP). Of these sites 125 agreed to participate in the study, and received a free review of the site with the promise of a business case for each DM reduction opportunity identified. Based on the results of these 125 investigations, a number of high potential sites were selected for further investigation or implementation assistance. The demand characteristics of the 125 sites participating in the study are shown in the table below: Table 1 Demand Characteristics of sites participating in the study Sector Number of sites Summer Maximum demand (kva) Aggregate Min / Av / Max individual sites Aggregate energy consumption (MWh pa) % of total study summer max demand Industrial 29 25, / 866 / 2, ,587 29% Retail 28 18, / 652 / 3,813 73,074 21% Hospitality 27 11, / 416 / 1,014 45,721 13% Health 9 10, / 1,220 / 4,022 50,023 13% Commercial 15 10, / 691 / 2,991 40,271 12% Infrastructure 9 7, / 824 / 2,145 27,909 9% Education 5 2, / 459 / 769 5,612 3% Leisure* / 425 / 519 2,699 1% Residential** / 140 / % Total , / 693 / 4, , % * Includes Entertainment, sporting, and leisure ** Large multi unit residential developments only. Individual households were not considered in this study. This demand pattern is not considered unusual for a mixed residential / commercial / light industrial area, and is likely to be representative of many parts of Sydney and other cities in NSW 2. Further analysis was undertaken to breakdown demand by end-use equipment type, and identified demand reductions by category, with the results shown on the following pages. 2 Relative number and demand of various sectors will vary depending on the local mix, and these figures should not be considered to be overall averages for any area other than St George Sutherland. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 8

20 Summer peak demand in St George Sutherland was broken down by site sector and end-use equipment category, with the results shown in Table 2.below and Figure 2 on the following page, showing a concentration of demand within a few sectors and equipment categories. Those end-use categories within a sector that constitute a significant proportion of the total demand are shown highlighted. Table 2 End-use equipment demand (summer kva) of sites participating in the study Site Sector Equipment Category Electric Cooling / Refrig n Lighting Machinery & Equipment Ventilation / Fans Pumps Compressors Electric Heating Computer Equipment Electric Hot Water / Steam Other Total summer peak demand (kva) % of total Industrial 6,003 1,600 8,457 4,220 1,112 1,446 1, ,114 29% Retail 8,924 3,693 1,060 3,289 Hospitality 5,794 1,510 1,452 1,801 Health 4,765 1,464 1,315 2,065 Commercial 3,244 2,796 1,274 1, ,262 21% ,221 13% ,982 13% ,358 12% Infrastructure 336 2, , ,412 8% Education 615 Leisure* 210 Residential** - Total 29,990 % of total 35% ,296 3% % % 14,682 14,254 13,401 6,649 2,529 2,102 1, ,635 17% 16% 15% 8% 3% 2% 2% 1% 0.3% 100% Key: Greater than 5% of total demand 3-5% of total demand 1-3% of total demand As can be seen from the table above and chart on the following page, demand is concentrated within relatively few sectors and end-use categories. The top 5 equipment categories and sectors each account for around 90% of total demand. This may provide a means of targeting future investigations in order to reduce the cost by focussing on those areas most likely to yield significant savings. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 9

21 Figure 2 Disaggregation of St George Sutherland area loads Study area loads by site sector and equipment category 9,000 8,000 7,000 6,000 5,000 4,000 3,000 Retail Industrial Hospitality Health Commercial Infrastructure Education 2,000 1,000 Summer peak demand (kva) - Electric Cooling / Refrigeration Lighting Machinery & Equipment Ventilation / Fans Pumps Compressors Entertainment / Sporting / sporting / leisure Multi-Residential Electric Heating Computer Equipment Electric Hot Water / Steam Other Equipment Category Site sector I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 10

22 Next, identified demand reductions were categorised by type, using the categories shown below in Table 3. All identified demand reductions (regardless of payback) were broken down by site sector and demand reduction category, again showing a concentration of identified reductions within the same sectors. Savings were spread more evenly amongst the demand reduction categories. Table 3 Level 1 investigations All identified demand reductions (summer kva) by site sector and demand reduction category Site Sector Demand Reduction Category Standby generation Load shifting Power Factor Correction Alternate fuel (fuel switching) Energy Efficiency Total All identified demand reductions % of total identified demand reductions Total sector peak demand (kva) Demand reductions % of total sector demand Industrial 832 7,657 3,267 3,107 1,247 16,110 37% 25,114 64% Retail 4, , ,010 16% 18,262 38% Hospitality 2,474 Health 4,793 Commercial 2, ,455 10% 11,221 40% Infrastructure 700 1, Education Leisure* Residential** Total 15,727 % of total 36% Average demand reduction of opportunities , ,769 18% 10,982 71% ,573 10% 10,358 44% ,116 7% 7,412 42% % 2,296 36% % % % % 10,205 7,325 5,868 4,958 44, % 86,635 51% 23% 17% 13% 11% 100% Key: Greater than 5% of total reduction 3-5% of total reduction 1-3% of total reduction I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 11

23 Finally, identified demand reductions were filtered to show only those with an attractive payback (to the end-user 3 ), and broken down by the same categories and sectors as the previous table, with results shown below in Table 4 below and the charts on the following page. Table 4 Level 1 investigations Attractive demand reductions (summer kva) by site sector and demand reduction category Site Sector Demand Reduction Category Standby generati on (kva identified) Load shifting (kva identified) Power Factor Correction (kva identified) Alternate fuel (fuel switching) (kva identified) Energy Efficiency (kva identified) Total Sector Attractive demand reductions (kva identified) % of total attractive demand reductions Total sector All demand reductions (kva identified) Attractive % of all sector demand reductions Industrial 2, ,440 46% 16,110 22% Note: Level 1 Retail investigation ,487 19% 7,010 21% Hospitality reports did not % 4,455 20% estimate capital or Health implementation % 7,769 4% Commercial costs for standby % 4,573 21% generation and Infrastructure load shifting % 3,116 8% Education opportunities, % % hence payback for Leisure* these options % % Residential** cannot be % 42 72% determined Category Total 4, ,698 7, % 44,083 17% % of total attractive opportunities 0% Attractive opportunities as % of all identified for that sector 0% 0% 61% 2% 37% 100% 0% 64% 3% 56% 17% Average demand reduction of attractive opportunities N/A N/A Key: 5+% of total attractive reduction 3-5% of total attractive reduction 1-3% of total attractive reduction 3 Very attractive was defined as having a simple payback of 0-2 years, with moderately attractive defined as a simple payback of 3-4 years. This analysis at this stage only considered energy and demand savings at the site, that is ignoring the additional value of demand reductions to the network utility. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 12

24 While the primary focus of this report is network peak demand reductions, reduced energy consumption and greenhouse gas savings are also important outcomes, and the primary driver for some other demand side management initiatives. Energy and greenhouse savings identified were analysed, with the results summarised in Table 5 below. Table 5 Energy and greenhouse gas savings identified in Level 1 investigations (MWh pa) Demand Reduction Category Payback Category Very attractive (0-2 yrs payback) Attractive Moderate (3-4 yrs payback) Unattractive (5-10 yrs payback) Uneconomic (11- payback) Total all energy savings Attractive Sub-Total Attractive % of total % of all attractive Alternate fuel (fuel switching) - Energy Efficiency 5,205 Load shifting 1,231 Power Factor Correction - Standby generation - Total 6,436 Total cons of all sites 348,805 Energy savings % of total cons 1.8% Greenhouse gas savings (t CO2e pa) 5,979 1,200 8,492 11,167 20,859 1,200 6% 5% 15,023 14,461 2,798 37,488 20,228 54% 89% ,376 1,301 95% 6% ,293 22,953 14,041 59,723 22,729 38% 100% 348, , , , , % 6.6% 4.0% 17.1% 6.5% 15,136 21,324 13,044 55,483 21,115 Note: Greenhouse savings calculated based on t CO2e / MWh (Source: NSW Greenhouse Gas Abatement Scheme, 2006 Pool Average) From this analysis it can be seen, as would be expected, that energy efficiency options offer the greatest energy savings, followed by fuel switching (including cogeneration), and small savings from some load shifting options. When payback is considered, almost 90% of all attractive energy savings opportunities come from energy efficiency, with over half of identified options having a payback of 4 years or less. Of the fuel switching options, 95% were considered unattractive or uneconomic, leaving only a modest potential for commercially attractive energy and greenhouse gas savings. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 13

25 Figure 3 Level 1 investigation results by site sector Summary of Level 1 audits 30, Summer peak demand (kva) 25,000 20,000 15,000 10,000 5, Numer of sites - - Industrial Retail Hospitality Health Commercial Infrastructure Education Leisure Residential Site sector Total demand Total savings Attractive savings Number of sites (RHS) Figure 4 Level 1 Identified opportunities by sector, action category, and attractiveness 18,000 Summary of Identified demand reductions by site sector 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2,000 - Industrial Retail Hospitality Health Commercial Infrastructure Education Leisure Residential Industrial Retail Hospitality Health Commercial Infrastructure Education Leisure Residential All identified opportunities Summer peak demand (kva) Attractive opportunities Standby generation Load shifting Power Factor Correction Alternate fuel (fuel switching) Energy Efficiency I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 14

26 3.1 Summary and conclusions Loads in the St George Sutherland area are typical of a mixed commercial / industrial / residential area. In this particular case, the principal loads accounting for 96% of total summer peak are in the following sectors: Industrial Retail Hospitality Health Commercial Infrastructure These sectors also account for 98% of identified demand reductions, and 96% of attractive demand reductions in terms of commercial viability (as measured by simple payback). The summer peak demand of the 125 sites investigated is 86.6MW, with a winter peak of 75.4MW. The electricity network in the area is predominantly summer peaking, hence a focus on summer peak demand is appropriate for a demand management investigation. Within the sites investigated, different equipment contributes to these demands, with the following end-use categories accounting for over 90% of the summer peak load: Electric Cooling / Refrigeration Lighting Machinery & Equipment Ventilation / Fans Pumps (Compressors and electric heating are also significant loads in the Industrial sector.) Demand reductions totalling 44.1MW (or 51% of site summer peak demands) were identified during the Level 1 investigations, though this figure includes opportunities that are infeasible for commercial or technical reasons. A total of 7.6MW (or 9% of site summer peak demands) of commercially attractive demand reductions were identified, predominantly in the power factor correction and energy efficiency categories. Level 1 investigations cost around $2,000 per site for a large study such as this, which equates to a cost of some $33 / kva of commercially attractive options identified. These findings could be used to target future opportunity identification studies, in order to reduce the cost of investigation per kva of identified reductions. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 15

27 4. Energy Efficiency measures Of all the action categories, Energy Efficiency had the lowest identified demand reduction, but was second only to Power Factor Correction when only attractive opportunities are considered. In other words, while some other categories such as fuel switching and standby generation had large individual and aggregate opportunities, these were seldom commercially viable. Overall, over half of all identified Energy Efficiency opportunities were commercially attractive, The average size of Energy Efficiency opportunities was only 15 kva per opportunity, both in total and for commercially attractive opportunities, the smallest of all the action categories. As will be seen later, this may exacerbate a transaction cost barrier to Energy Efficiency opportunities that is frequently overlooked in analysis of demand management potential. 4.1 Level 1 Investigations A total of 344 Energy Efficiency opportunities were identified in the 125 Level 1 investigations conducted, or an average of 2.8 per site, some 60% of all opportunities identified. The results of the Level 1 investigations are shown in the tables on the following pages. Firstly, the demand reductions, and demand reductions from financially attractive opportunities, were broken down by sector to identify those sectors and technologies with the highest potential and commercial potential to reduce demand. As previously shown in Table 5, energy and greenhouse savings differed markedly between DM categories, with Energy Efficiency having the highest level of energy savings. Further analysis was conducted to determine energy savings relative to peak demand reduction, that is to identify those demand reduction measures that also had the highest energy savings. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 16

28 Identified demand reductions from Energy Efficiency opportunities were categorised by type, using the categories shown below in Table 6. Table 6 Level 1 investigations All identified energy efficiency options (summer kva) by site sector Energy Efficiency Category Site Sector Lighting HVAC Drives and motors Other Industrial processes Building Management System Energy Efficiency total Sector % of total Industrial ,247 25% Retail Hospitality Health Commercial % % % % Infrastructure % Education % Leisure 11 Residential 10 Total 2,386 % of total 48% Average simple payback % % 1, , % 32% 13% 5% 2% 0% 100% Key: Greater than 5% of total 3-5% of total 1-3% of total I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 17

29 Next, identified energy efficiency opportunities were filtered to show only those with an attractive payback, and broken down by the same categories and sectors as the previous table, with results shown below in Table 7 below and the charts on the following page. Table 7 Level 1 investigations Attractive energy efficiency options (summer kva) by site sector Energy Efficiency Category Site Sector Lighting HVAC Drives and motors Other Industrial processes Building Management System Energy Efficiency total Sector % of total attractive opportunit ies Attractive opportunit ies as % of Sector total Industrial % 73% Retail % 64% Hospitality % 81% Health % 10% Commercial % 63% Infrastructure 99 Education % 66% % 2% Leisure 11 Residential 10 Total 1,643 % of all attractive energy efficiency opportunities (kva basis) 61% Attractive opportunities as % of all identified for that sector (kva basis) 69% % 100% % 100% , % 54% 17% 17% 1% 4% 0% 100% 30% 72% 8% 100% 0% 54% Key: 5+% of total attractive opportunities 3-5% of total attractive opportunities 1-3% of total attractive opportunities Attractive opportunities are heavily concentrated within a few sectors and action categories, namely Lighting and HVAC options in the Industrial, Retail, Hospitality and Commercial sectors, in addition to Drives and Motors and Industrial Processes in the Industrial sector. This subset accounts for 85% of all attractive energy efficiency opportunities, and may be useful for targeting future studies in order to reduce Level 1 investigation costs per attractive opportunity identified. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 18

30 Relative energy savings per kw of peak demand reduction are shown in Table 8 below, for Energy Efficiency category opportunities only. A high 4 kwh pa / kw peak figure in the table above implies the measure achieves relatively high energy savings and per unit of demand savings, or in other words has its principal impact outside peak times. Implied energy savings load factors >100% are possible 5. Table 8 Level 1 investigations Energy savings relative to demand savings by site (kwh pa / peak summer kw saved) Energy Efficiency Category Site Sector Lighting HVAC Drives and motors Other Industrial processes BMS Sector Average Sector savings load factor Sector consumpt ion load factor Industrial 5,574 6,263 7,617 30,580 5,772. 6,725 77% 47% Retail 6,627 17,462 29,551.. **** 11, % 46% Hospitality 5,719 7,037 11,385 4,000. **** 7,093 81% 47% Health 6,963 11,081 17,093 4, , % 52% Commercial 5,652 5,734 7, ,943 68% 44% Infrastructure 3,687 28,600 8,217 11, ,195 82% 39% Education 2,362 3, , ,230 37% 28% Leisure 4,864 ****.... 9, % 36% Residential 8,500 7, ,833 89% 74% Total 5,396 9,389 9,767 9,324 5,772 **** 7,561 86% 46% Implied load factor 62% 107% 111% 106% 66% 86% Key: 25+% higher than average 25+% lower than average **** These instances had energy savings but zero coincident peak demand reduction, ie infinite kwh / kw. Given that the primary focus of the Level 1 investigations was intended to be peak demand reductions, the high load factors are somewhat surprising. The load factor of identified savings is higher than the actual consumption load factor in every sector, and on average almost double that of actual consumption. Possible explanations are that there simply weren t many cost effective peak demand reduction opportunities compared to general efficiency opportunities, or possibly the energy saving estimates are optimistic or demand savings estimates pessimistic (see Section 4.2) 4 A 1kW load that was permanently on would consume 8,760 kwh pa (# of hrs in a year) and have a load factor of 100%. Typical load factors for individual site consumption are around 50%, or 4,380 kwh / kw. 5 For example putting lights on a timer to switch them off at night would save energy, but have little or no impact on peak demand during the day, hence the savings would be expected to have a high load factor. Conversely, demand reduction measures that operate principally during peak times and have little impact at other times (eg load shedding) would be expected to have a low load factor. Measures that provide a fixed efficiency improvement (eg lower wattage lights) will save demand and energy in direct proportion to usage, and should have the same load factor as the actual consumption of energy at the load or site. I:\HARB\Projects\HA00931\100\Deliverables\St George verification report final report.doc PAGE 19