Pub Date : 2026-03-01Epub Date: 2026-03-16DOI: 10.1109/TEMPR.2026.3666414
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Pub Date : 2026-03-01Epub Date: 2026-03-16DOI: 10.1109/TEMPR.2026.3666410
{"title":"IEEE Power & Energy Society Information","authors":"","doi":"10.1109/TEMPR.2026.3666410","DOIUrl":"https://doi.org/10.1109/TEMPR.2026.3666410","url":null,"abstract":"","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"4 1","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11435556","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557966","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 : 2026-03-01Epub Date: 2025-11-17DOI: 10.1109/TEMPR.2025.3633559
Alessio Berdin;Laurens de Vries;Aad Correljé;Kenneth Bruninx
Hydrogen and derived fuels may act as long-term energy storage in climate-neutral energy systems. However, risk-averse investors will not invest in sufficient renewable electricity, back-up, electrolyzer and storage capacity if they are only remunerated for the hydrogen or electricity produced and markets for risk are missing. We develop a stochastic equilibrium model to study whether capacity markets can limit costs to consumers by restoring investments risk-neutral levels. Our results show that the efficacy of capacity markets depends on complementary instruments to ensure the availability of renewables. If risk-aversion and missing markets for risk reduce renewable build-out, capacity markets in the electricity and hydrogen sectors are needed to restore the overall capacity mix and limit costs for consumers. If complementary instruments lift investments in renewables, a capacity market in the electricity sector suffices. In this situation, an additional capacity market in the hydrogen sector triggers a bias toward hydrogen-fired backup capacity. This illustrates that an integrated systems perspective is required to design future energy markets.
{"title":"Missing Risk Markets and Capacity Remuneration Mechanisms in Electricity-Hydrogen Systems","authors":"Alessio Berdin;Laurens de Vries;Aad Correljé;Kenneth Bruninx","doi":"10.1109/TEMPR.2025.3633559","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3633559","url":null,"abstract":"Hydrogen and derived fuels may act as long-term energy storage in climate-neutral energy systems. However, risk-averse investors will not invest in sufficient renewable electricity, back-up, electrolyzer and storage capacity if they are only remunerated for the hydrogen or electricity produced and markets for risk are missing. We develop a stochastic equilibrium model to study whether capacity markets can limit costs to consumers by restoring investments risk-neutral levels. Our results show that the efficacy of capacity markets depends on complementary instruments to ensure the availability of renewables. If risk-aversion and missing markets for risk reduce renewable build-out, capacity markets in the electricity and hydrogen sectors are needed to restore the overall capacity mix and limit costs for consumers. If complementary instruments lift investments in renewables, a capacity market in the electricity sector suffices. In this situation, an additional capacity market in the hydrogen sector triggers a bias toward hydrogen-fired backup capacity. This illustrates that an integrated systems perspective is required to design future energy markets.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"4 1","pages":"67-77"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557909","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 : 2026-03-01Epub Date: 2025-10-30DOI: 10.1109/TEMPR.2025.3626480
Albane Seres;Miguel Heleno
This paper proposes a methodology to generate sets of distribution feeders representative of any U.S. county for economic and policy studies. The methodology modifies prototypical feeders and organizes them into sets that (i) reproduce historical economic and infrastructure investment patterns and (ii) accommodate county-specific demand characteristics, including energy, peak, and building types. The approach relies on publicly available data, enabling systematic application across all U.S. counties and adaptation to other regions. The use of the resulting feeders is demonstrated through an electrification impact study in Alameda County, California.
{"title":"US Representative Feeder Sets for Distribution Grid Economics and Policy Applications","authors":"Albane Seres;Miguel Heleno","doi":"10.1109/TEMPR.2025.3626480","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3626480","url":null,"abstract":"This paper proposes a methodology to generate sets of distribution feeders representative of any U.S. county for economic and policy studies. The methodology modifies prototypical feeders and organizes them into sets that (i) reproduce historical economic and infrastructure investment patterns and (ii) accommodate county-specific demand characteristics, including energy, peak, and building types. The approach relies on publicly available data, enabling systematic application across all U.S. counties and adaptation to other regions. The use of the resulting feeders is demonstrated through an electrification impact study in Alameda County, California.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"4 1","pages":"106-116"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557903","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 : 2026-03-01Epub Date: 2025-12-11DOI: 10.1109/TEMPR.2025.3642801
Denis Osipov;Syed Ahsan R. Naqvi;Sai R. K. M. S. Palepu;James Onyejizu;Daniel Kirk-Davidoff;Pengwei Du;Koushik Kar;Joe H. Chow;Aparna Gupta
This paper presents a risk segmentation approach for scheduling generation in power systems with high penetration of renewable energy resources (RERs). This approach aims to facilitate risk-adjusted participation of RERs in the day-ahead market (DAM). It borrows from debt securitization techniques to define risk tranches and develops separate bid curves of RERs by the tranches of different grades of risk. Assigning a higher price to a tranche with greater risk can prevent a renewable asset owner from incurring losses when the asset cannot produce the day-ahead committed amount of energy and must buy energy from the real-time market (RTM). In the proposed approach, the system operator utilizes the risk-segmented bids from RERs and generation reliability constraints to solve a risk-adjusted unit commitment (UC) problem. To a system operator, this can be treated as a deterministic DAM dispatch. The stochasticity of this UC problem is embedded in the renewable bid curves. The resulting increase in DAM revenues due to additional DAM commitment benefits the renewable asset owners. The loads can also benefit from additional RER commitment in DAM as it lowers DAM energy prices. The paper will focus on using this risk-adjusted strategy for wind energy resources. The approach is illustrated on a synthetic 6,700-bus model of the 2030 Electric Reliability Council of Texas (ERCOT) system that has a significant penetration of wind resources.
{"title":"Unit Commitment With Risk-Adjusted Tranching of Renewable Energy Resources","authors":"Denis Osipov;Syed Ahsan R. Naqvi;Sai R. K. M. S. Palepu;James Onyejizu;Daniel Kirk-Davidoff;Pengwei Du;Koushik Kar;Joe H. Chow;Aparna Gupta","doi":"10.1109/TEMPR.2025.3642801","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3642801","url":null,"abstract":"This paper presents a risk segmentation approach for scheduling generation in power systems with high penetration of renewable energy resources (RERs). This approach aims to facilitate risk-adjusted participation of RERs in the day-ahead market (DAM). It borrows from debt securitization techniques to define risk tranches and develops separate bid curves of RERs by the tranches of different grades of risk. Assigning a higher price to a tranche with greater risk can prevent a renewable asset owner from incurring losses when the asset cannot produce the day-ahead committed amount of energy and must buy energy from the real-time market (RTM). In the proposed approach, the system operator utilizes the risk-segmented bids from RERs and generation reliability constraints to solve a risk-adjusted unit commitment (UC) problem. To a system operator, this can be treated as a deterministic DAM dispatch. The stochasticity of this UC problem is embedded in the renewable bid curves. The resulting increase in DAM revenues due to additional DAM commitment benefits the renewable asset owners. The loads can also benefit from additional RER commitment in DAM as it lowers DAM energy prices. The paper will focus on using this risk-adjusted strategy for wind energy resources. The approach is illustrated on a synthetic 6,700-bus model of the 2030 Electric Reliability Council of Texas (ERCOT) system that has a significant penetration of wind resources.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"4 1","pages":"93-105"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557905","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 : 2026-03-01Epub Date: 2025-09-03DOI: 10.1109/TEMPR.2025.3605808
Jacques Cartuyvels;Gilles Bertrand;Alexandros Visas;Anthony Papavasiliou
This paper provides a framework for analyzing the interaction of imbalance settlement and the strategy of system operators for activating reserves on the clearing of multi-product real-time energy markets. We characterize the optimal strategies of price-taking flexibility providers that can participate in sequential auctions conducted by the system operator to activate automatic and manual frequency restoration reserves. Combinations of imbalance settlement schemes and activation strategies are assessed based on their influence on bidding incentives and cost efficiency.
{"title":"Imbalance Settlement and Multi-Product Balancing Energy Markets","authors":"Jacques Cartuyvels;Gilles Bertrand;Alexandros Visas;Anthony Papavasiliou","doi":"10.1109/TEMPR.2025.3605808","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3605808","url":null,"abstract":"This paper provides a framework for analyzing the interaction of imbalance settlement and the strategy of system operators for activating reserves on the clearing of multi-product real-time energy markets. We characterize the optimal strategies of price-taking flexibility providers that can participate in sequential auctions conducted by the system operator to activate automatic and manual frequency restoration reserves. Combinations of imbalance settlement schemes and activation strategies are assessed based on their influence on bidding incentives and cost efficiency.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"4 1","pages":"156-167"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11150599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557914","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}
The increasing penetration of distributed energy resources (DERs) requires better coordination between transmission and distribution (T&D) planning to ensure system security and cost efficiency. However, misaligned planning horizons, computational burdens, and privacy concerns hinder effective coordination, leading to either underutilized resources caused by overinvestments or reliability risks due to underinvestment. To address this challenge, we introduce netload range cost curves (NRCCs), a novel approach for managing long-term DER growth uncertainty through T&D coordination, while preserving existing data-sharing and regulatory structures. NRCCs provide pairs of (i) peak substation netload guarantees and (ii) corresponding distribution upgrade options and costs, enabling their seamless integration into transmission planning workflows. To compute NRCCs efficiently, we develop a transmission-aware distribution network planning (TADNP), which is subsequently integrated to an iterative computation procedure. These NRCCs are then embedded into an NRCC-informed transmission planning model to enable resource-efficient coordination. We illustrate our proposed approach with a case study based on realistic distribution and transmission systems in the San Francisco Bay Area, California. Our results indicate the possibility of dramatic savings in transmission investments by incorporating the proposed NRCC-integrated T&D coordination framework.
{"title":"Netload Range Cost Curves for Coordinated Transmission-Distribution Planning Under DER Growth Uncertainty","authors":"Yujia Li;Samuel Córdova;Alexandre Moreira;Miguel Heleno","doi":"10.1109/TEMPR.2025.3638837","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3638837","url":null,"abstract":"The increasing penetration of distributed energy resources (DERs) requires better coordination between transmission and distribution (T&D) planning to ensure system security and cost efficiency. However, misaligned planning horizons, computational burdens, and privacy concerns hinder effective coordination, leading to either underutilized resources caused by overinvestments or reliability risks due to underinvestment. To address this challenge, we introduce netload range cost curves (NRCCs), a novel approach for managing long-term DER growth uncertainty through T&D coordination, while preserving existing data-sharing and regulatory structures. NRCCs provide pairs of (i) peak substation netload guarantees and (ii) corresponding distribution upgrade options and costs, enabling their seamless integration into transmission planning workflows. To compute NRCCs efficiently, we develop a transmission-aware distribution network planning (TADNP), which is subsequently integrated to an iterative computation procedure. These NRCCs are then embedded into an NRCC-informed transmission planning model to enable resource-efficient coordination. We illustrate our proposed approach with a case study based on realistic distribution and transmission systems in the San Francisco Bay Area, California. Our results indicate the possibility of dramatic savings in transmission investments by incorporating the proposed NRCC-integrated T&D coordination framework.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"4 1","pages":"25-39"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557939","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 : 2026-03-01Epub Date: 2025-10-31DOI: 10.1109/TEMPR.2025.3628116
Payal Vyankat Dahiwale;Zakir H. Rather
To develop a robust electrified road transport ecosystem, various policy initiatives are being introduced in different countries. However, the actual implementation of interventions specified in the electric vehicle (EV) policy needs to be assessed to analyze the on-ground implementation of these policies. For determining the status of EV policy intervention implementation, this paper proposes an L1-distance based indicator for EV policy implementation in terms of a remoteness score. To improve the intervention implementation of EV policies, effective intervention selection is carried out in this paper using a quantitative method of L1-distance based integer linear optimization approach. This L1-distance based optimization considers the attributes of relative cost and benefit of intervention implementation in the EV ecosystem. The proposed method minimizes the remoteness score while identifying the optimal interventions by considering full and partial information availability. The proposed method is implemented for Indian State EV policies of Maharashtra, Delhi, and Karnataka with a remoteness score reduction of 50% and 75% considering the State and idealistic EV policy. To validate the effectiveness of the proposed L1-distance based optimization for optimal intervention selection, the proposed strategy is compared with existing methods. A comparative analysis is performed in terms of the relative cost of implementation and performance indices such as L$infty $ distance, L1 distance, Hamming distance, Trucker’s coefficient of congruence, and Gower’s similarity coefficient. This paper also performs a detailed analysis of the smart charging aspect considering its significance toward a sustainable EV charging ecosystem.
为了发展强大的电气化道路运输生态系统，不同国家正在推出各种政策举措。然而，需要评估电动汽车（EV）政策中规定的干预措施的实际实施情况，以分析这些政策的实际实施情况。为了确定电动汽车政策干预的实施状况，本文提出了一种基于l1距离的电动汽车政策实施指标，即距离分数。为了提高电动汽车政策的干预实施效果，本文采用基于l1距离的整数线性优化方法定量进行有效的干预选择。这种基于l1距离的优化考虑了在电动汽车生态系统中实施干预的相对成本和收益属性。所提出的方法通过考虑全部和部分信息可用性来确定最佳干预措施，同时最大限度地减少了远程得分。该方法在印度马哈拉施特拉邦、德里和卡纳塔克邦的电动汽车政策中实施，远程得分降低了50分% and 75% considering the State and idealistic EV policy. To validate the effectiveness of the proposed L1-distance based optimization for optimal intervention selection, the proposed strategy is compared with existing methods. A comparative analysis is performed in terms of the relative cost of implementation and performance indices such as L$infty $ distance, L1 distance, Hamming distance, Trucker’s coefficient of congruence, and Gower’s similarity coefficient. This paper also performs a detailed analysis of the smart charging aspect considering its significance toward a sustainable EV charging ecosystem.
{"title":"L1 Distance-Based Optimization Approach for Recommendation and Effective Intervention Selection for EV Policy Implementation","authors":"Payal Vyankat Dahiwale;Zakir H. Rather","doi":"10.1109/TEMPR.2025.3628116","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3628116","url":null,"abstract":"To develop a robust electrified road transport ecosystem, various policy initiatives are being introduced in different countries. However, the actual implementation of interventions specified in the electric vehicle (EV) policy needs to be assessed to analyze the on-ground implementation of these policies. For determining the status of EV policy intervention implementation, this paper proposes an L1-distance based indicator for EV policy implementation in terms of a remoteness score. To improve the intervention implementation of EV policies, effective intervention selection is carried out in this paper using a quantitative method of L1-distance based integer linear optimization approach. This L1-distance based optimization considers the attributes of relative cost and benefit of intervention implementation in the EV ecosystem. The proposed method minimizes the remoteness score while identifying the optimal interventions by considering full and partial information availability. The proposed method is implemented for Indian State EV policies of Maharashtra, Delhi, and Karnataka with a remoteness score reduction of 50% and 75% considering the State and idealistic EV policy. To validate the effectiveness of the proposed L1-distance based optimization for optimal intervention selection, the proposed strategy is compared with existing methods. A comparative analysis is performed in terms of the relative cost of implementation and performance indices such as L<inline-formula><tex-math>$infty $</tex-math></inline-formula> distance, L1 distance, Hamming distance, Trucker’s coefficient of congruence, and Gower’s similarity coefficient. This paper also performs a detailed analysis of the smart charging aspect considering its significance toward a sustainable EV charging ecosystem.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"4 1","pages":"53-66"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557944","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 : 2026-03-01Epub Date: 2026-01-12DOI: 10.1109/TEMPR.2026.3652086
Bo Chen;Yu Christine Chen
This paper presents a method to internalize the impact of system frequency dynamics into real-time pricing of reserves. The proposed frequency dynamics-aware price of reserves helps to incentivize and compensate generators for setting aside reserves that contribute to de-risking real-time dynamic performance subject to uncertainty in the net-load forecast. Central to the proposed method is to augment a static chance-constrained economic dispatch (CCED) with constraints modelling system frequency dynamics driven by generator inertia response along with primary and secondary frequency controls. Chance constraints in the resulting dynamics-aware CCED enforce tolerable probability of dynamic system frequency and generator power trajectories violating their respective limits. We show that the dynamics-aware price of reserves internalizes uncertainty in dynamic state variables along with the risk of violating limits in frequency excursions and generator outputs during frequency transients as well as in steady state. We also assess the sensitivity of the dynamics-aware price of reserves with respect to generator parameters that directly affect system dynamic performance. Numerical case studies involving the Western System Coordinating Council and New England test systems confirm dynamics in the proposed price of reserves, reveal additional revenue for generators, and demonstrate computational scalability.
{"title":"Chance-Constrained Real-Time Pricing of Reserves Incorporating System Frequency Dynamics","authors":"Bo Chen;Yu Christine Chen","doi":"10.1109/TEMPR.2026.3652086","DOIUrl":"https://doi.org/10.1109/TEMPR.2026.3652086","url":null,"abstract":"This paper presents a method to internalize the impact of system frequency dynamics into real-time pricing of reserves. The proposed frequency dynamics-aware price of reserves helps to incentivize and compensate generators for setting aside reserves that contribute to de-risking real-time dynamic performance subject to uncertainty in the net-load forecast. Central to the proposed method is to augment a static chance-constrained economic dispatch (CCED) with constraints modelling system frequency dynamics driven by generator inertia response along with primary and secondary frequency controls. Chance constraints in the resulting dynamics-aware CCED enforce tolerable probability of dynamic system frequency and generator power trajectories violating their respective limits. We show that the dynamics-aware price of reserves internalizes uncertainty in dynamic state variables along with the risk of violating limits in frequency excursions and generator outputs during frequency transients as well as in steady state. We also assess the sensitivity of the dynamics-aware price of reserves with respect to generator parameters that directly affect system dynamic performance. Numerical case studies involving the Western System Coordinating Council and New England test systems confirm dynamics in the proposed price of reserves, reveal additional revenue for generators, and demonstrate computational scalability.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"4 1","pages":"40-52"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557945","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 : 2026-03-01Epub Date: 2025-12-10DOI: 10.1109/TEMPR.2025.3642697
Ashish Radhakrishnan;Chiara Lo Prete;Jiaxing Wu
Fuel supply interruptions at gas-fired power plants are a leading cause of power outages during winter storms, often affecting even plants holding firm contracts. These challenges are especially acute in the Northeastern U.S., where pipeline congestion during peak heating demand restricts gas deliveries to the power sector. This paper examines the potential of Advanced Exchange Agreements, under which industrial customers transfer firm supply and transportation capacity to power plants during emergencies in exchange for compensation. We develop an optimization framework for the joint operation of gas and electricity systems during winter emergencies. The framework captures competing gas uses, contract types, and curtailment priorities, and is applied to a system representing the Northeastern U.S. during the 2014 Polar Vortex, leveraging a novel dataset on gas deliveries by sector and contract type. Our results show that the net benefits of the proposed initiative vary widely (ranging from 1.0% to 40% of baseline costs on days with unserved electric energy), based on assumptions on the share of firm contracts held by industrial customers and the subset of power plants eligible for participation in the bilateral agreements. Limiting power plant participation in the Advanced Exchange Agreements emerges as a greater barrier to realizing the potential benefits of the proposed initiative than modest firm contract holdings of industrial customers.
{"title":"Contracts for Gas Prioritization to Power Plants During Winter Emergencies","authors":"Ashish Radhakrishnan;Chiara Lo Prete;Jiaxing Wu","doi":"10.1109/TEMPR.2025.3642697","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3642697","url":null,"abstract":"Fuel supply interruptions at gas-fired power plants are a leading cause of power outages during winter storms, often affecting even plants holding firm contracts. These challenges are especially acute in the Northeastern U.S., where pipeline congestion during peak heating demand restricts gas deliveries to the power sector. This paper examines the potential of Advanced Exchange Agreements, under which industrial customers transfer firm supply and transportation capacity to power plants during emergencies in exchange for compensation. We develop an optimization framework for the joint operation of gas and electricity systems during winter emergencies. The framework captures competing gas uses, contract types, and curtailment priorities, and is applied to a system representing the Northeastern U.S. during the 2014 Polar Vortex, leveraging a novel dataset on gas deliveries by sector and contract type. Our results show that the net benefits of the proposed initiative vary widely (ranging from 1.0% to 40% of baseline costs on days with unserved electric energy), based on assumptions on the share of firm contracts held by industrial customers and the subset of power plants eligible for participation in the bilateral agreements. Limiting power plant participation in the Advanced Exchange Agreements emerges as a greater barrier to realizing the potential benefits of the proposed initiative than modest firm contract holdings of industrial customers.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"4 1","pages":"130-142"},"PeriodicalIF":0.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557906","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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