AMI & Demand Response

Transcription

1 AMI & Demand Response Ross Malme President & CEO RETX Energy Services, Inc. American Utility Week Atlanta, GA April 2006 Proprietary Information Not for Distribution Page 1

2 Beliefs Widespread use of interval metering would be a great thing for the electric industry. Interval metering is a powerful DR enabling technology AMI can even be a stronger DR enabling technology But it it s s important to know what type of DR you seek or you may build/buy the wrong AMI solution. Buying the wrong solution can be an extremely expensive mistake Proprietary Information Not for Distribution Page 2

3 Which metering solution matches your DR requirements? DR APPLICATION Spinning Reserves Backup Capacity Economic Dispatch Residential Load Control Seconds / Minutes Hours Daily AMI TIME LATENCY Monthly / Profiled Proprietary Information Not for Distribution Page 3

4 Issues EPACT 2005 requires utilities and PUCs to investigate interval metering and time based rates. Many metering solutions (rightfully) count the benefits of DR in their business cases. However, different DR products can yield different total benefits. Therefore, the industry would benefit from determining which DR solutions it needs and then determine which metering solution is right for those products. Proprietary Information Not for Distribution Page 4

5 Things to Consider What is the right amount of DR for my market? How do you validate this? What is the DR market potential in my market? Top performing players have 10% of their peak demand (or more) What DR product type will be most beneficial to my firm, my customer, and my market? This requires simultaneous understanding of multiple market variables. ables. What type of data and what type of speed do I need to deliver those products? Key issues: notification, monitoring, control, market settlement,, & consumer settlement Proprietary Information Not for Distribution Page 5

6 IEA DSM An international collaboration with 17 IEA Member countries and the European Commission Working to clarify and promote opportunities for demand-side management (DSM) DSM is defined to include a variety of purposes such as load management, energy efficiency, strategic conservation and related activities DSM is thus forming a "tool-box" for utilities and governments in their work to make energy systems more suited to their purpose See Proprietary Information Not for Distribution Page 6

7 Task XIII: Demand Response Resources Task XIII is charged with reviewing DRR practices in various markets around the world and developing recommendations and tools for integrating DRR into regular market activities. Supported by: US DOE, FERC & US Demand Response Coordinating Committee OA Team: Ross Malme, Operating Agent; Summit Blue Consulting Proprietary Information Not for Distribution Page 7

8 Task XIII Membership Australia Canada Denmark Finland Italy Japan Korea Netherlands Norway Spain Sweden USA Proprietary Information Not for Distribution Page 8

9 IEA DRR Project Subtasks 2) Market Characterization - of demand response products, services and enabling technologies 3) Market Potential of DRR - methods for assessing the available DR market potential in a given market 4) DRR Valuation - methods and procedures required to establish the value of DR and to administer them in each country to create a valuation framework to guide development initiatives 5) Role and Value of Technologies - catalogue that describes the technologies and systems available for use in DR programs both from perspective of system operator and participating customer 6) Market Barriers, DR Solutions and Recommendations - Identify current DR products and market barriers. Develop recommendations for DR implementations. 7) Communications & Workshops - web portal and country workshops on DRR methods, technologies, and applications 8) Implementation - delivery of intellectual property created in the DRR Project to the IEA DSM Programme and the participating countries Proprietary Information Not for Distribution Page 9

10 DRR Project Portal dsm.iea.org/newdsm/work/tasks/13/task13.asp Proprietary Information Not for Distribution Page 10

11 DR Valuation / Product Analysis To appropriately determine the future impact of DR products, the following must be considered: The planning framework should have a sufficiently long time horizon to allow for the benefits of DRR to be recognized and captured. DRR has the potential to reduce the costs of low- probability, high-consequence events that impact system reliability, but these events may occur only every 5 or 10 years. DRR can reduce the risks of high electricity prices during periods when several factors combine to create shortages or high system costs. To address this risk management aspect of DRR, the planning framework must explicitly address the uncertainty that is present around key factors, including fuel prices, weather, and system factors such as transmission constraints and plant operation. Proprietary Information Not for Distribution Page 11

12 Market Scenario Analysis Step 1: 1 Assess the current base-case electric system and develop base-case resource planning model runs using standard planning principles and supply-side side resource options. Step 2: 2 Determine pivotal factors, i.e., those factors that have significant influence on the market costs of electricity. These are likely to include future fuel prices (coal, oil and natural gas), summer month energy demands in the peak month, monthly peak demand, plant outages and transmission system performance, and the future e costs of environmental compliance (e.g., carbon taxes or offset costs). Step 3: Assess the uncertainty around these pivot factors and express that uncertainty via probability distributions. Step 4: Create a combination of these factors, i.e., combine the probability distributions to create a joint probability surface. Step 5: Draw a set of discrete futures (termed cases )) from the probability surface. Each case includes a value for each key factor (e.g. 100 draws). Step 6: Each case represents an alternative future with a given probability bility of occurrence. These 100 cases are input into a resource planning model, which provides 100 values for system costs one for each alternative future. These costs are used to create e a distribution of costs for a given set of available resources. Step 7: Repeat Step 6 for different portfolios of resources to determine the cost differential and reliability differential for with DRR and without DRR options. Proprietary Information Not for Distribution Page 12

13 Our Simulated Market Supply Mix Installed Capacity Nuclear Coal Combined Cycle Gas Distillate Residual Hydro Pumped Storage Total Number of Units MW 8,663 4,369 7,429 5,356 5,923 2, ,280 36,357 Proprietary Information Not for Distribution Page 13

14 Our Simulated Market (Cont.) Other Characteristics Peak Demand Reserve Margin Energy Demand Load Factor Customers System Cost Average System Cost 30,064 MW 20.9% 145,423 GWh 55.0% 6 Million $4,505 M $46.39 / MWh Proprietary Information Not for Distribution Page 14

15 Key Input Variables Fuel prices natural gas, residual oil, distillate oil, and coal Peak demand Energy demand Unit outages Tie line capacities Proprietary Information Not for Distribution Page 15

16 Simulated DR Products Interruptible Product A known amount of load reduction based on a two-hour call period. Customers are paid a capacity payment for the MW pledged and there are penalties if MW reductions are not attained. Direct Load Control Product A known amount of load reduction with 5 to 10 minutes of notification. This is focused on mass market customers. As a result, r it has a longer ramp- up time to attain a sizeable amount of MW capacity. Dispatchable Purchase Transaction A call option where the model looks at the marginal system cost and decides to take the DRR offered when that price is less than the marginal system cost. This program can also be classified as a day-ahead ahead pricing program. Real-Time Pricing Product The real-time pricing program posed a challenge in that there is no feedback loop built into the model that looks at the marginal hourly cost and the demand for that same hour. As a result, two pricing products were examined: One was a peak-period period pricing program which produced a reduction in peak demand and little impact on load in other hours. This is similar to a critical c peak pricing product, with the overall monthly and annual energy demand largely ly unaffected. The second was a standard RTP program that produced a reduction in peak demand and also an overall energy efficiency effect, resulting in reductions in weekly, monthly, and annual energy demand this is consistent with the RTP literature. Proprietary Information Not for Distribution Page 16

17 Simulation Results Hourly Costs: On a peak demand day with additional system stresses, such as 10% of generating capacity being off-line, savings in marginal production costs are substantial. The addition of DRR to the system greatly y reduced the peakiness of the hourly costs, reducing the maximum by more than 50%. For example, in one peak day in July the total cost savings were $24.5 million. Proprietary Information Not for Distribution Page 17

18 Simulation Results (Cont.) Total System Cost: Overall, the incorporation of DRR results in some reduction in the average total system cost NPV in all three scenarios with DRR (callable DRR, DRR with CPP, and DRR with standard RTP). System costs savings ($M) Average NPV over 20 years Callable DRR Only 48 Callable DRR with Critical Peak Pricing (peak hour load reduction only) Callable DRR with Standard RTP (reduction in demand in all high price hours) 574 1,984 Proprietary Information Not for Distribution Page 18

19 Bottom Line DR can provide substantial market benefits. Different DR portfolios will yield different financial and risk management benefits Therefore, proper consideration of the type and expected magnitude of DR is critical when determining the functional requirements of a metering system.especially if the DR benefits are used to justify the business case. Proprietary Information Not for Distribution Page 19

20 US DOE Says State regulatory authorities and electric utilities should assure that utility consideration of advanced metering systems includes evaluation of their ability to support price-based and reliability-driven DR, and that the business case analysis includes the potential impacts and benefits of expanded DR along with the operational benefits to utilities. * Let s get it right the first time! * Source: [US DOE: Benefits of Demand Response in Electricity Markets and Recommendations for Achieving Them February 2006] Proprietary Information Not for Distribution Page 20

21 Questions? Ross Malme President and Chief Executive Officer RETX Phone: Fax: Proprietary Information Not for Distribution Page 21