Pub Date : 2023-09-15DOI: 10.1109/TEMPR.2023.3315956
Brent Eldridge;Bernard Knueven;Jacob Mays
Operators of organized wholesale electricity markets attempt to form prices in such a way that the private incentives of market participants are consistent with a socially optimal commitment and dispatch schedule. In the U.S. context, several competing price formation schemes have been proposed to address the non-convex production cost functions characteristic of most generation technologies. This paper considers how the design and analysis of price formation policies for non-convex markets are affected by the uncertainty inherent in electricity demand and supply. We argue that by excluding uncertainty, the analytical framework underlying existing policies mischaracterizes the incentives of market participants, leading to inefficient price formation and poor incentives for flexibility. We establish favorable theoretical properties of a new construct, ex ante convex hull pricing , and demonstrate the difference between this idealized benchmark and existing methods on a large-scale test system. Given increased operational uncertainty with a transition to wind and solar generation, distortions caused by poor incentives for flexibility are likely to grow without improved price formation in organized wholesale markets.
{"title":"Rethinking the Price Formation Problem–Part 1: Participant Incentives Under Uncertainty","authors":"Brent Eldridge;Bernard Knueven;Jacob Mays","doi":"10.1109/TEMPR.2023.3315956","DOIUrl":"10.1109/TEMPR.2023.3315956","url":null,"abstract":"Operators of organized wholesale electricity markets attempt to form prices in such a way that the private incentives of market participants are consistent with a socially optimal commitment and dispatch schedule. In the U.S. context, several competing price formation schemes have been proposed to address the non-convex production cost functions characteristic of most generation technologies. This paper considers how the design and analysis of price formation policies for non-convex markets are affected by the uncertainty inherent in electricity demand and supply. We argue that by excluding uncertainty, the analytical framework underlying existing policies mischaracterizes the incentives of market participants, leading to inefficient price formation and poor incentives for flexibility. We establish favorable theoretical properties of a new construct, \u0000<italic>ex ante convex hull pricing</i>\u0000, and demonstrate the difference between this idealized benchmark and existing methods on a large-scale test system. Given increased operational uncertainty with a transition to wind and solar generation, distortions caused by poor incentives for flexibility are likely to grow without improved price formation in organized wholesale markets.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"480-489"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135495624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-13DOI: 10.1109/TEMPR.2023.3308657
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Pub Date : 2023-09-13DOI: 10.1109/TEMPR.2023.3308661
{"title":"IEEE Power & Energy Society Information","authors":"","doi":"10.1109/TEMPR.2023.3308661","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3308661","url":null,"abstract":"","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 3","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9794458/10250976/10250977.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50329230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-13DOI: 10.1109/TEMPR.2023.3308659
{"title":"IEEE Transactions on Energy Markets, Policy, and Regulation Information for Authors","authors":"","doi":"10.1109/TEMPR.2023.3308659","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3308659","url":null,"abstract":"","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 3","pages":"C3-C3"},"PeriodicalIF":0.0,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9794458/10250976/10251023.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50290971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-11DOI: 10.1109/TEMPR.2023.3304559
Mohammad Ostadijafari;Grishma Manandhar;Anamika Dubey;H. Alan Love;Olvar Bergland
Demand response (DR) is a viable solution to increase the grid's operational efficiency. However, the effective participation of residential customers in DR programs is low, and the available potential of this sector has not been fully utilized. One important reason for this low engagement is the unavailability of amenable demand curtailment contracts that simultaneously include customer preferences and behavior and utilize enabling technologies to realize the full potential to manage usage. This paper addresses the critical need for increasing residential DR by designing economic contracts that maximize power utility's/load serving entity's (LSE) net benefit while considering individual customers' utility. Specifically, we propose a principal-agent model to develop optimal demand curtailment contracts between the LSE and customers based on their willingness-to-pay (WTP) for cooling degrees. Emphasis is on designing contracts that offer critical peak rebates (CPRs). These contracts allow the LSE a short-term load control of customers' facilities to reduce demand by remotely altering individual household thermostat settings of the Heating, Ventilation, and Air Conditioning (HVAC) systems. The efficiency of the proposed contracts is evaluated using several simulation case studies.
{"title":"Principal-Agent Model for Bilateral Contract Design to Incentivize Residential Demand-Side Flexibility","authors":"Mohammad Ostadijafari;Grishma Manandhar;Anamika Dubey;H. Alan Love;Olvar Bergland","doi":"10.1109/TEMPR.2023.3304559","DOIUrl":"10.1109/TEMPR.2023.3304559","url":null,"abstract":"Demand response (DR) is a viable solution to increase the grid's operational efficiency. However, the effective participation of residential customers in DR programs is low, and the available potential of this sector has not been fully utilized. One important reason for this low engagement is the unavailability of amenable demand curtailment contracts that simultaneously include customer preferences and behavior and utilize enabling technologies to realize the full potential to manage usage. This paper addresses the critical need for increasing residential DR by designing economic contracts that maximize power utility's/load serving entity's (LSE) net benefit while considering individual customers' utility. Specifically, we propose a principal-agent model to develop optimal demand curtailment contracts between the LSE and customers based on their willingness-to-pay (WTP) for cooling degrees. Emphasis is on designing contracts that offer critical peak rebates (CPRs). These contracts allow the LSE a short-term load control of customers' facilities to reduce demand by remotely altering individual household thermostat settings of the Heating, Ventilation, and Air Conditioning (HVAC) systems. The efficiency of the proposed contracts is evaluated using several simulation case studies.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"310-321"},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77657653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Electricity markets are transforming from the dominance of conventional energy resources (CERs), e.g., fossil fuels, to low-carbon energy resources (LERs), e.g., renewables and energy storage. This work examines market mechanisms to incentivize LER investments, while ensuring adequate market revenues for investors, guiding investors' strategic investments towards social optimum, and protecting consumers from scarcity prices. To reduce the impact of excessive scarcity prices, we present a new market mechanism, which consists of a P enalty payment for lost load, a supply I ncentive, and an energy price U plift (PIU). We establish a game-theoretical framework to analyze market equilibrium. We prove that one Nash equilibrium under the penalty payment and supply incentive can reach the social optimum given quadratic supply costs of CERs. Although the price uplift can ensure adequate revenues, the resulting system cost deviates from the social optimum while the gap decreases as more CERs retire. Furthermore, under the traditional marginal-cost pricing (MCP) mechanism, investors may withhold investments to cause scarcity prices, but such behavior is absent under the PIU mechanism. Simulation results show that the PIU mechanism can reduce consumers' costs by over 30% compared with the MCP mechanism by reducing excessive revenues of low-cost CERs from scarcity prices.
{"title":"Market Mechanisms for Low-Carbon Electricity Investments: A Game-Theoretical Analysis","authors":"Dongwei Zhao;Sarah Coyle;Apurba Sakti;Audun Botterud","doi":"10.1109/TEMPR.2023.3304555","DOIUrl":"10.1109/TEMPR.2023.3304555","url":null,"abstract":"Electricity markets are transforming from the dominance of conventional energy resources (CERs), e.g., fossil fuels, to low-carbon energy resources (LERs), e.g., renewables and energy storage. This work examines market mechanisms to incentivize LER investments, while ensuring adequate market revenues for investors, guiding investors' strategic investments towards social optimum, and protecting consumers from scarcity prices. To reduce the impact of excessive scarcity prices, we present a new market mechanism, which consists of a \u0000<italic>P</i>\u0000enalty payment for lost load, a supply \u0000<italic>I</i>\u0000ncentive, and an energy price \u0000<italic>U</i>\u0000plift (PIU). We establish a game-theoretical framework to analyze market equilibrium. We prove that one Nash equilibrium under the penalty payment and supply incentive can reach the social optimum given quadratic supply costs of CERs. Although the price uplift can ensure adequate revenues, the resulting system cost deviates from the social optimum while the gap decreases as more CERs retire. Furthermore, under the traditional marginal-cost pricing (MCP) mechanism, investors may withhold investments to cause scarcity prices, but such behavior is absent under the PIU mechanism. Simulation results show that the PIU mechanism can reduce consumers' costs by over 30% compared with the MCP mechanism by reducing excessive revenues of low-cost CERs from scarcity prices.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"441-454"},"PeriodicalIF":0.0,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136079654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1109/TEMPR.2023.3303911
Ahmad Attarha;Masoume Mahmoodi;S. Mahdi Noori R. A.;Paul Scott;José Iria;Sylvie Thiébaux
The increasing penetration of distributed energy resources (DER) has highlighted the role of aggregators as mediators who enable the participation of DER fleet in energy and reserve markets. Since DER are scattered across the distribution network, the overall bids reaching the market need to account for distribution network physical limits. This is challenging as the grid operator and aggregators are independent parties with separate roles and privacy requirements. The uncertainty around demand, solar power, and electricity price further complicates aggregators' job in calculating reliable network-secure bids. To overcome these challenges, we propose a price-sensitive bidding approach within network operating envelopes that enables aggregators to provide reliable market services. To ensure that data uncertainty neither leads to network violations nor leaves aggregators unable to deliver their market commitments, we introduce a piecewise affinely adjustable optimisation (PAARO) controller into our bidding problem. We also extend the aggregator bidding problem to account for cases where the overall consumer uncertainty cancels out, providing a less conservative solution. We illustrate the effectiveness of our proposed approach using 69-bus/906-bus distribution networks. The results show that our approach could increase aggregator and hence consumer benefits by up to 14%, compared to a price-insensitive and deterministic approach.
{"title":"Adjustable Price-Sensitive DER Bidding Within Network Envelopes","authors":"Ahmad Attarha;Masoume Mahmoodi;S. Mahdi Noori R. A.;Paul Scott;José Iria;Sylvie Thiébaux","doi":"10.1109/TEMPR.2023.3303911","DOIUrl":"10.1109/TEMPR.2023.3303911","url":null,"abstract":"The increasing penetration of distributed energy resources (DER) has highlighted the role of aggregators as mediators who enable the participation of DER fleet in energy and reserve markets. Since DER are scattered across the distribution network, the overall bids reaching the market need to account for distribution network physical limits. This is challenging as the grid operator and aggregators are independent parties with separate roles and privacy requirements. The uncertainty around demand, solar power, and electricity price further complicates aggregators' job in calculating reliable network-secure bids. To overcome these challenges, we propose a price-sensitive bidding approach within network operating envelopes that enables aggregators to provide reliable market services. To ensure that data uncertainty neither leads to network violations nor leaves aggregators unable to deliver their market commitments, we introduce a piecewise affinely adjustable optimisation (PAARO) controller into our bidding problem. We also extend the aggregator bidding problem to account for cases where the overall consumer uncertainty cancels out, providing a less conservative solution. We illustrate the effectiveness of our proposed approach using 69-bus/906-bus distribution networks. The results show that our approach could increase aggregator and hence consumer benefits by up to 14%, compared to a price-insensitive and deterministic approach.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"248-258"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77002609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Extreme events, exacerbated by climate change, pose significant risks to the energy system and its consumers. However there are natural limits to the degree of protection that can be delivered from a centralised market architecture. Distributed energy resources provide resilience to the energy system, but their value remains inadequately recognized by regulatory frameworks. We propose an insurance framework to align residual outage risk exposure with locational incentives for distributed investment. We demonstrate that leveraging this framework in large-scale electricity systems could improve consumer welfare outcomes in the face of growing risks from extreme events via investment in distributed energy.
{"title":"An Insurance Paradigm for Improving Power System Resilience via Distributed Investment","authors":"Farhad Billimoria;Filiberto Fele;Iacopo Savelli;Thomas Morstyn;Malcolm McCulloch","doi":"10.1109/TEMPR.2023.3301830","DOIUrl":"10.1109/TEMPR.2023.3301830","url":null,"abstract":"Extreme events, exacerbated by climate change, pose significant risks to the energy system and its consumers. However there are natural limits to the degree of protection that can be delivered from a centralised market architecture. Distributed energy resources provide resilience to the energy system, but their value remains inadequately recognized by regulatory frameworks. We propose an insurance framework to align residual outage risk exposure with locational incentives for distributed investment. We demonstrate that leveraging this framework in large-scale electricity systems could improve consumer welfare outcomes in the face of growing risks from extreme events via investment in distributed energy.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"499-511"},"PeriodicalIF":0.0,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91138014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The flexibility services available from embedded resources, being attractive to both the network operators and retailers, pose a problem of co-ordination and market design at the local level. This research considers how a Flexibility Market Operator (FMO) at the local level, analogous to market operators at the wholesale level, can improve the real-time operation of the power systems and efficiently manage the interests of the TSO, DSO, and Retailers. Using generalized disjunctive programming, a stochastic bilevel representation of the task is reformulated as a stochastic mixed-logical linear program (MLLP) with indicator constraints. An Inference-Dual-Based Decomposition (IDBD) Algorithm is developed with sub-problem relaxation to reduce the iterations. Using expected Shapley values, a new payoff mechanism is introduced to allocate the cost of service activations in a fair way. Finally, the performance and benefits of the proposed method are assessed via a case study application.
{"title":"A Stochastic Inference-Dual-Based Decomposition Algorithm for TSO-DSO-Retailer Coordination","authors":"Hamed Bakhtiari;Mohammad Reza Hesamzadeh;Derek Bunn","doi":"10.1109/TEMPR.2023.3301810","DOIUrl":"10.1109/TEMPR.2023.3301810","url":null,"abstract":"The flexibility services available from embedded resources, being attractive to both the network operators and retailers, pose a problem of co-ordination and market design at the local level. This research considers how a Flexibility Market Operator (FMO) at the local level, analogous to market operators at the wholesale level, can improve the real-time operation of the power systems and efficiently manage the interests of the TSO, DSO, and Retailers. Using generalized disjunctive programming, a stochastic bilevel representation of the task is reformulated as a stochastic mixed-logical linear program (MLLP) with indicator constraints. An Inference-Dual-Based Decomposition (IDBD) Algorithm is developed with sub-problem relaxation to reduce the iterations. Using expected Shapley values, a new payoff mechanism is introduced to allocate the cost of service activations in a fair way. Finally, the performance and benefits of the proposed method are assessed via a case study application.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"2 1","pages":"13-29"},"PeriodicalIF":0.0,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76810885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-27DOI: 10.1109/TEMPR.2023.3299514
Adam Suski;Debabrata Chattopadhyay
This article develops a Nash-Cournot model of multicommodity electricity market, co-optimizing energy and ancillary services, including a strategically behaving storage operator participating in both markets. The model is formulated as a centralized optimization problem and applied to the Ukraine day-ahead market. The impact of battery storage on the prices of energy and ancillary services products under various storage capacities and strategic storage operations is evaluated. It is shown that battery storage could significantly increase competition within the ancillary services market (primarily frequency containment reserves) and reduce prices. Storage with an installed capacity of 1000 MW could cut original frequency containment reserve prices by a third and provide part of its capacity to other ancillary services products.
{"title":"Multicommodity Nash-Cournot Market Model With Strategic Storage Operator","authors":"Adam Suski;Debabrata Chattopadhyay","doi":"10.1109/TEMPR.2023.3299514","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3299514","url":null,"abstract":"This article develops a Nash-Cournot model of multicommodity electricity market, co-optimizing energy and ancillary services, including a strategically behaving storage operator participating in both markets. The model is formulated as a centralized optimization problem and applied to the Ukraine day-ahead market. The impact of battery storage on the prices of energy and ancillary services products under various storage capacities and strategic storage operations is evaluated. It is shown that battery storage could significantly increase competition within the ancillary services market (primarily frequency containment reserves) and reduce prices. Storage with an installed capacity of 1000 MW could cut original frequency containment reserve prices by a third and provide part of its capacity to other ancillary services products.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 3","pages":"145-160"},"PeriodicalIF":0.0,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50290973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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