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Framework for Assessing the Impacts of Proposed Market Improvements

An analysis approach to evaluate the impact of proposed energy security improvements on energy and ancillary service markets using a production cost model.

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Framework for Assessing the Impacts of Proposed Market Improvements

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  1. May 8, 2018| Markets committee Chris Geissler and Chris Parent 413.535.4367 | 413.540.4599 cgeissler@iso-ne.com | cparent@iso-ne.com Framework for assessing the impacts of the proposed market improvements Energy Security Improvements: Impact Assessment Approach

  2. Objective of analysis is to inform stakeholders of how the design performs under different scenarios Quantitatively analyze energy and ancillary service market impacts of energy security improvements (ESI) using a production cost model (PCM) Develop a qualitative framework for understanding the impacts of ESI on the capacity market Today: Further discussion of the PCM that will be used to evaluate ESI’s impact on energy and ancillary service markets ISO plans to perform analysis of both Energy Market and Capacity Market

  3. Production cost model

  4. ISO has retained the Analysis Group to build a PCM to estimate the impact of the proposed ESI changes on market outcomes Generally, the PCM will ‘mimic’ the process by which the ISO determines which resources sell energy and ancillary services More specifically, the PCM will determine forward and spot positions in order to minimize bid production costs, while satisfying relevant constraints (e.g. energy production equals energy demand, ancillary service requirements, etc.) PCM: Overview

  5. The PCM seeks to inform stakeholders how ESI may change system dispatch and market outcomes across a range of scenarios Compare results from two runs of PCM that each use the same assumptions about load, generation, etc., except: Baseline run assumes current rules (i.e., no ESI) Counterfactual run assumes that ESI is in place, and new ancillary services are procured DA Model’s outputs include DA and RT prices for energy and applicable ancillary services, summary data on simulated system dispatch Limit granularity of reported output data to comply with ISO’s information policy and protect confidential information PCM: Using model to assess impact of ESI

  6. PCM will make several simplifying assumptions so that it can produce results before October filing deadline Actual production software for ESI will likely take several years to build Assumptions include, but are not limited to, the following: PCM simulations limited to winter months when ESI’s impact is expected to be most significant No transmission constraints Relax resource specific intertemporal parameters Static reserve requirements Must also make assumptions about resource bidding behavior (for energy, ancillary products), fuel replenishments, etc. Plan to discuss the model’s assumptions in more detail at upcoming stakeholder meetings PCM: Assumptions

  7. To fully evaluate the impacts of ESI, the PCM must include several distinct components, including: Model inputs: Load (bid, forecast, and actual), energy supply curves in DA and RT, ancillary service requirements, etc. Day Ahead: Determine forward positions and prices for energy and ancillary services Real-Time: Determine dispatch and spot energy price Model outputs: Summarize DA and RT results, including dispatch, prices, and total costs Each component is discussed in more detail (next) PCM: Mechanics

  8. The PCM requires several model input parameters that can be based on historic data or future forecasts: Load: Model uses several load parameters including DA cleared, forecasted, actual RT load Energy supply curves: Dependent on assumed resource mix, natural gas prices, outages rates, and availability of resources not cleared DA to be dispatched in RT Ancillary service requirements: In simulations where ESI is in effect, model must specify requirements in DA for GCR, RER, and EIR Will include requirements for Total Ten-Minute Reserves and Minimum Operation Reserve and Thirty-Minute Operating Reserves – No Ten-Minute Spinning Reserve Requirement will be included PCM: Model inputs

  9. The DA module uses DA load and supply offers to determine awards to energy suppliers, and the DA clearing price Under counterfactual runs (where ESI is in place), module will also determine the set of resources that sell the new ancillary service products, and the contract parameters associated with these products (e.g., the option clearing and strike prices) Plan to discuss how simulations consider M-DAM at future MC meetings PCM: Day ahead module

  10. To capture the full effect of ESI, the model must also consider dispatch in RT New ancillary products introduced under ESI will impact resource availability in RT PCM includes stochastic RT ‘shocks’ to reflect unexpected changes to system conditions between DA and RT Could occur because RT load exceeds DA load, generation that cleared DA is unavailable in RT, etc. RT module will be informative for assessing how new ancillary services procured DA affect RT resource availability/dispatch and energy prices, including in cases where the ISO must dispatch resources in RT that did not sell energy DA PCM: Real-time module

  11. Model output will include information on system dispatch by resource type, DA and RT prices, emissions, energy inventories, and total costs Participants can use this output data to assess how introduction of ESI may impact clearing prices and total costs across a range of scenarios for the market and specific types of resources PCM: Output

  12. Simulation Scenarios

  13. PCM can be run using a range of input assumptions to evaluate impact of ESI across various conditions and scenarios, including: Different load conditions Various resource mixes Will help participants understand the sensitivity of ESI’s potential impacts to broader market conditions Welcome continued stakeholder input on what scenarios may be most informative to explore in limited time before committee votes and FERC-mandated filing (October 15th) Scenario analysis: Overview

  14. More detailed discussion of model’s assumptions and input data, and how modules determine awards and prices, including: Use of historic versus forecasted input parameters DA load, forecast load, actual load, and the relationship between these variables Gas availability and prices Stochastic ‘shocks’ between DA and RT Bidding behavior for energy and new ancillary services, including determination of opportunity costs Looking Ahead: June Markets Committee

  15. July MC: Present first set of simulations, assessing impact of ESI under range of scenarios, including: Average scenario: Average weather, load, gas prices, etc. Mild scenario: Mild weather, low load, low gas prices, etc. Severe scenario: Severe weather, high load, high gas prices, low gas availability, etc. August MC: Present additional simulation results illustrating model’s sensitivity to various assumptions and parameters based on stakeholder requests and feedback Because of October filing deadline, may not be able to model every scenario requested Looking Ahead: July and August Markets Committees

  16. Proposed impact analysis schedule May-2019. Provide a more detailed explanation of the PCM structure and scenarios which the ISO plans to simulate June-2019. Continued discussion of PCM, respond to feedback from stakeholders and discuss July-2019. Provide initial results (limited scenarios) and discuss how to understand analysis/results August-2019. Review full results of the analysis September-2019. Provide a final report on the impact analysis

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