Pub Date : 2024-01-15DOI: 10.1109/TEMPR.2024.3354162
Ahmed S. Alahmed;Lang Tong
We propose a social welfare maximizing market mechanism for an energy community that aggregates individual and community-shared energy resources under a general net energy metering (NEM) policy. Referred to as Dynamic NEM (D-NEM), the proposed mechanism dynamically sets the community NEM prices based on aggregated community resources, including flexible consumption, storage, and renewable generation. D-NEM guarantees a higher benefit to each community member than possible outside the community, and no sub-communities would be better off departing from its parent community. D-NEM aligns each member's incentive with that of the community such that each member maximizing individual surplus under D-NEM results in maximum community social welfare. Empirical studies compare the proposed mechanism with existing benchmarks, demonstrating its welfare benefits, operational characteristics, and responsiveness to NEM rates.
{"title":"Dynamic Net Metering for Energy Communities","authors":"Ahmed S. Alahmed;Lang Tong","doi":"10.1109/TEMPR.2024.3354162","DOIUrl":"https://doi.org/10.1109/TEMPR.2024.3354162","url":null,"abstract":"We propose a social welfare maximizing market mechanism for an energy community that aggregates individual and community-shared energy resources under a general net energy metering (NEM) policy. Referred to as Dynamic NEM (D-NEM), the proposed mechanism dynamically sets the community NEM prices based on aggregated community resources, including flexible consumption, storage, and renewable generation. D-NEM guarantees a higher benefit to each community member than possible outside the community, and no sub-communities would be better off departing from its parent community. D-NEM aligns each member's incentive with that of the community such that each member maximizing individual surplus under D-NEM results in maximum community social welfare. Empirical studies compare the proposed mechanism with existing benchmarks, demonstrating its welfare benefits, operational characteristics, and responsiveness to NEM rates.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"2 3","pages":"289-300"},"PeriodicalIF":0.0,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142173965","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 : 2024-01-10DOI: 10.1109/TEMPR.2024.3350051
Hikaru Hoshino;Yosuke Irie;Eiko Furutani
The profitability of solar energy self-consumption in households, the so-called photovoltaic (PV) self-consumption, is expected to boost the deployment of PV and battery storage systems. This paper develops a novel method for economic analysis of PV self-consumption using battery storage based on an extension of the Screening Curve Method (SCM). The SCM enables quick and intuitive estimation of the least-cost generation mix for a target load curve and has been used for generation planning for bulk power systems. In this paper, we generalize the framework of existing SCM to take into account the intermittent nature of renewable energy sources and apply it to the problem of optimal sizing of PV and battery storage systems for a household. Numerical studies are provided to verify the estimation accuracy of the proposed SCM and to illustrate its effectiveness in a sensitivity analysis, owing to its ability to show intuitive plots of cost curves for researchers or policy-makers to understand the reasons behind the optimization results.
{"title":"Screening Curve Method for Economic Analysis of Household Solar Energy Self-Consumption","authors":"Hikaru Hoshino;Yosuke Irie;Eiko Furutani","doi":"10.1109/TEMPR.2024.3350051","DOIUrl":"https://doi.org/10.1109/TEMPR.2024.3350051","url":null,"abstract":"The profitability of solar energy self-consumption in households, the so-called photovoltaic (PV) self-consumption, is expected to boost the deployment of PV and battery storage systems. This paper develops a novel method for economic analysis of PV self-consumption using battery storage based on an extension of the Screening Curve Method (SCM). The SCM enables quick and intuitive estimation of the least-cost generation mix for a target load curve and has been used for generation planning for bulk power systems. In this paper, we generalize the framework of existing SCM to take into account the intermittent nature of renewable energy sources and apply it to the problem of optimal sizing of PV and battery storage systems for a household. Numerical studies are provided to verify the estimation accuracy of the proposed SCM and to illustrate its effectiveness in a sensitivity analysis, owing to its ability to show intuitive plots of cost curves for researchers or policy-makers to understand the reasons behind the optimization results.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"2 3","pages":"368-378"},"PeriodicalIF":0.0,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142173944","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 : 2024-01-05DOI: 10.1109/TEMPR.2024.3350510
Anshul Goyal;Kankar Bhattacharya
This article presents a novel framework with new mathematical models that integrate Demand Response (DR) and Battery Energy Storage Systems (BESSs) simultaneously in a Locational Marginal Price (LMP)-based Multi-Settlement Market (MSM), i.e. a coordinated Day-Ahead Market (DAM) and Real-Time Market (RTM). A new set of generator ramping constraints, developed from the DAM settlement, and referred to as Day-Ahead Load-Following (DALF) Ramp, are included in the RTM auction model. The performance of the mathematical models are tested on the IEEE 24-bus Reliability Test System (RTS) by carrying out various case studies, scenarios, uncertainty and sensitivity analyses. Effect of DR and BESS characteristics such as level of participation, initial state-of-charge (SOC), discharge rate, etc. on market settlement is examined. The results demonstrate the merits of the proposed framework, and the impact of the DALF Ramp, DR and BESS inclusion in the MSM auction models on marginal prices, market settlement and system operation. It is noted that the system with DR and BESS in the MSM hedges real-time prices and effectively supports system operation during uncertain events such as line and generators outages, changes in demand or in generation from renewables.
本文提出了一种新的数学模型框架，将需求响应（DR）和电池储能系统（BESS）同时纳入基于本地边际价格（LMP）的多结算市场（MSM），即协调的日前市场（DAM）和实时市场（RTM）。RTM 拍卖模型中包含了一组新的发电机斜坡约束，该约束由 DAM 结算发展而来，被称为 "日前负荷跟随（DALF）斜坡"。通过开展各种案例研究、情景分析、不确定性和敏感性分析，在 IEEE 24 总线可靠性测试系统（RTS）上测试了数学模型的性能。研究了 DR 和 BESS 特性（如参与水平、初始充电状态 (SOC)、放电率等）对市场结算的影响。结果表明了所建议框架的优点，以及将 DALF Ramp、DR 和 BESS 纳入 MSM 拍卖模型对边际价格、市场结算和系统运行的影响。结果表明，在 MSM 中包含 DR 和 BESS 的系统可以对冲实时价格，并在线路和发电机停运、需求变化或可再生能源发电量变化等不确定事件发生时有效支持系统运行。
{"title":"Design of Multi-Settlement Electricity Markets Considering Demand Response and Battery Energy Storage Systems Participation","authors":"Anshul Goyal;Kankar Bhattacharya","doi":"10.1109/TEMPR.2024.3350510","DOIUrl":"https://doi.org/10.1109/TEMPR.2024.3350510","url":null,"abstract":"This article presents a novel framework with new mathematical models that integrate Demand Response (DR) and Battery Energy Storage Systems (BESSs) simultaneously in a Locational Marginal Price (LMP)-based Multi-Settlement Market (MSM), i.e. a coordinated Day-Ahead Market (DAM) and Real-Time Market (RTM). A new set of generator ramping constraints, developed from the DAM settlement, and referred to as Day-Ahead Load-Following (DALF) Ramp, are included in the RTM auction model. The performance of the mathematical models are tested on the IEEE 24-bus Reliability Test System (RTS) by carrying out various case studies, scenarios, uncertainty and sensitivity analyses. Effect of DR and BESS characteristics such as level of participation, initial state-of-charge (SOC), discharge rate, etc. on market settlement is examined. The results demonstrate the merits of the proposed framework, and the impact of the DALF Ramp, DR and BESS inclusion in the MSM auction models on marginal prices, market settlement and system operation. It is noted that the system with DR and BESS in the MSM hedges real-time prices and effectively supports system operation during uncertain events such as line and generators outages, changes in demand or in generation from renewables.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"2 2","pages":"226-239"},"PeriodicalIF":0.0,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319671","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 : 2024-01-02DOI: 10.1109/TEMPR.2023.3349134
Nan Gu;Chenye Wu;Daniel S. Kirschen
Owners of renewable energy resources (RES) often choose to invest in energy storage for joint operation with RES to maximize profitability. Standalone entities also invest in energy storage systems and use them for arbitrage. In this paper we examine how these two forms of ownership affect the value of energy storage. Our study reveals that in a perfectly competitive market, energy storage holds equal value for both types of owners if they are risk-neutral. However, when agents are able to exert market power or exhibit risk aversion, the value of energy storage can differ between the two ownership structures. Additionally, we discuss how differential pricing and market barriers influence the value of energy storage. In the numerical studies, we explore how factors such as seasonal price volatility, RES types, and the siting of energy storage influence investment decisions.
{"title":"Economic Value of Energy Storage Systems: The Influence of Ownership Structures","authors":"Nan Gu;Chenye Wu;Daniel S. Kirschen","doi":"10.1109/TEMPR.2023.3349134","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3349134","url":null,"abstract":"Owners of renewable energy resources (RES) often choose to invest in energy storage for joint operation with RES to maximize profitability. Standalone entities also invest in energy storage systems and use them for arbitrage. In this paper we examine how these two forms of ownership affect the value of energy storage. Our study reveals that in a perfectly competitive market, energy storage holds equal value for both types of owners if they are risk-neutral. However, when agents are able to exert market power or exhibit risk aversion, the value of energy storage can differ between the two ownership structures. Additionally, we discuss how differential pricing and market barriers influence the value of energy storage. In the numerical studies, we explore how factors such as seasonal price volatility, RES types, and the siting of energy storage influence investment decisions.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"2 3","pages":"313-327"},"PeriodicalIF":0.0,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174025","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 : 2024-01-01DOI: 10.1109/TEMPR.2023.3348984
Qingwen Pang;Vincenzo Trovato;Antonio De Paola;Goran Strbac
The significant reduction in the system inertial response due to the increasing penetration of converter-interfaced renewable generators may reduce the ability to safely control post-fault frequency dynamics. Larger volumes of flexible ancillary services may be required to ensure system stability. Part of these additional regulation resources may be procured from other power systems by means of existing and new interconnectors. The paper investigates this framework by assessing the techno-economic benefits of interconnectors that operate in a multi-area power network and whose capacity can be utilized for simultaneous exchange of power and fast-frequency services. Two different operational approaches are considered: a traditional centralized allocation of the interconnectors’ capacity and an alternative market-based paradigm where price-making interconnectors act as profit-seeking agents that aim to maximize their collected congestion surplus. The paper provides new fundamental results on the benefits of a multi-purpose allocation of the interconnectors’ capacity, directly comparing the operational choices and the interactions between centrally-operated and self-interested interconnectors, and quantifying the impact of the latter on the overall social welfare of the system. This novel methodology is applied to a model of an interconnected Great Britain-France-Ireland multi-area system, quantifying the potential benefits of multi-service interconnectors and assessing the impact of their self-interested scheduling within a realistic framework that considers power systems of different sizes and characteristics.
{"title":"Market-Based Operation of Interconnectors in a Multi-Area Power Network With Meshed Topology","authors":"Qingwen Pang;Vincenzo Trovato;Antonio De Paola;Goran Strbac","doi":"10.1109/TEMPR.2023.3348984","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3348984","url":null,"abstract":"The significant reduction in the system inertial response due to the increasing penetration of converter-interfaced renewable generators may reduce the ability to safely control post-fault frequency dynamics. Larger volumes of flexible ancillary services may be required to ensure system stability. Part of these additional regulation resources may be procured from other power systems by means of existing and new interconnectors. The paper investigates this framework by assessing the techno-economic benefits of interconnectors that operate in a multi-area power network and whose capacity can be utilized for simultaneous exchange of power and fast-frequency services. Two different operational approaches are considered: a traditional centralized allocation of the interconnectors’ capacity and an alternative market-based paradigm where price-making interconnectors act as profit-seeking agents that aim to maximize their collected congestion surplus. The paper provides new fundamental results on the benefits of a multi-purpose allocation of the interconnectors’ capacity, directly comparing the operational choices and the interactions between centrally-operated and self-interested interconnectors, and quantifying the impact of the latter on the overall social welfare of the system. This novel methodology is applied to a model of an interconnected Great Britain-France-Ireland multi-area system, quantifying the potential benefits of multi-service interconnectors and assessing the impact of their self-interested scheduling within a realistic framework that considers power systems of different sizes and characteristics.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"2 1","pages":"79-91"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135202","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 : 2023-12-29DOI: 10.1109/TEMPR.2023.3347627
Shuangyuan Wang;Ran Li;Qiuyang Ma;Chenghong Gu;Furong Li
Most existing network pricing methodologies are designed for retailers and large customers. With the development of responsive technologies, domestic customers may have very different impacts on networks cost, thus calling for a cost-reflective network pricing method for mass customers in the retail market. The naive volumetric and marginal pricing methods may cause issues of inequality and mis-signaling. Inspired by the Passenger Car Equivalent (PCE) in transportation economics, this paper proposes a Unit Home Equivalent (UHE) pricing to reflect the compatibility between electricity networks and a certain type of users. The method is validated against the Distribution Use of System (DUoS) charging methodology in the U.K. by using real network and household data. The results show the proposed pricing can encourage existing customers to adjust energy usage behaviours and guide new customers and EVs to the right locations.
{"title":"Unit Equivalent Distribution Network Pricing for Electricity Retail Market","authors":"Shuangyuan Wang;Ran Li;Qiuyang Ma;Chenghong Gu;Furong Li","doi":"10.1109/TEMPR.2023.3347627","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3347627","url":null,"abstract":"Most existing network pricing methodologies are designed for retailers and large customers. With the development of responsive technologies, domestic customers may have very different impacts on networks cost, thus calling for a cost-reflective network pricing method for mass customers in the retail market. The naive volumetric and marginal pricing methods may cause issues of inequality and mis-signaling. Inspired by the Passenger Car Equivalent (PCE) in transportation economics, this paper proposes a Unit Home Equivalent (UHE) pricing to reflect the compatibility between electricity networks and a certain type of users. The method is validated against the Distribution Use of System (DUoS) charging methodology in the U.K. by using real network and household data. The results show the proposed pricing can encourage existing customers to adjust energy usage behaviours and guide new customers and EVs to the right locations.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"2 2","pages":"276-288"},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141319670","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 : 2023-12-21DOI: 10.1109/TEMPR.2023.3344329
{"title":"2023 Index IEEE Transactions on Energy Markets, Policy, and Regulation Vol.1","authors":"","doi":"10.1109/TEMPR.2023.3344329","DOIUrl":"10.1109/TEMPR.2023.3344329","url":null,"abstract":"","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"549-558"},"PeriodicalIF":0.0,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10368212","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139020062","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 : 2023-12-19DOI: 10.1109/TEMPR.2023.3344126
Dongwei Zhao;Vladimir Dvorkin;Stefanos Delikaraoglou;Alberto J. Lamadrid L.;Audun Botterud
This work proposes an uncertainty-informed bid adjustment framework for integrating variable renewable energy sources (VRES) into electricity markets. This framework adopts a bilevel model to compute the optimal VRES day-ahead bids. It aims to minimize the expected system cost across day-ahead and real-time stages and approximate the cost efficiency of the stochastic market design. However, solving the bilevel optimization problem is computationally challenging for large-scale systems. To overcome this challenge, we introduce a novel technique based on strong duality and McCormick envelopes, which relaxes the problem to a linear program, enabling large-scale applications. The proposed bilevel framework is applied to the 1576-bus NYISO system and benchmarked against a myopic strategy, where the VRES bid is the mean value of the probabilistic power forecast. Results demonstrate that, under high VRES penetration levels (e.g., 40%), our framework can significantly reduce system costs and market-price volatility, by optimizing VRES quantities efficiently in the day-ahead market. Furthermore, we find that when transmission capacity increases, the proposed bilevel model will still reduce the system cost, whereas the myopic strategy may incur a much higher cost due to over-scheduling of VRES in the day-ahead market and the lack of flexible conventional generators in real time.
{"title":"Uncertainty-Informed Renewable Energy Scheduling: A Scalable Bilevel Framework","authors":"Dongwei Zhao;Vladimir Dvorkin;Stefanos Delikaraoglou;Alberto J. Lamadrid L.;Audun Botterud","doi":"10.1109/TEMPR.2023.3344126","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3344126","url":null,"abstract":"This work proposes an uncertainty-informed bid adjustment framework for integrating variable renewable energy sources (VRES) into electricity markets. This framework adopts a bilevel model to compute the optimal VRES day-ahead bids. It aims to minimize the expected system cost across day-ahead and real-time stages and approximate the cost efficiency of the stochastic market design. However, solving the bilevel optimization problem is computationally challenging for large-scale systems. To overcome this challenge, we introduce a novel technique based on strong duality and McCormick envelopes, which relaxes the problem to a linear program, enabling large-scale applications. The proposed bilevel framework is applied to the 1576-bus NYISO system and benchmarked against a myopic strategy, where the VRES bid is the mean value of the probabilistic power forecast. Results demonstrate that, under high VRES penetration levels (e.g., 40%), our framework can significantly reduce system costs and market-price volatility, by optimizing VRES quantities efficiently in the day-ahead market. Furthermore, we find that when transmission capacity increases, the proposed bilevel model will still reduce the system cost, whereas the myopic strategy may incur a much higher cost due to over-scheduling of VRES in the day-ahead market and the lack of flexible conventional generators in real time.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"2 1","pages":"132-145"},"PeriodicalIF":0.0,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135282","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 : 2023-12-15DOI: 10.1109/TEMPR.2023.3343631
Phillippe K. Phanivong;Duncan S. Callaway
Power engineers have examined the potential impacts on the electric grid of high electric vehicle (EV) adoption, while energy economists have shown issues with modern electricity retail tariff design. However, little work has shown how customer decisions regarding their tariff and optimizing EV charging costs could affect the utility and the customer. If commercial customers can optimize their charging profile, how do different tariff structures affect local distribution system voltage, utility cost recovery, and customer bills? To answer this question, we model commercial customers optimizing their EV charging to minimize costs using real-world tariffs. Then, we model the voltage impacts of customers charging EVs on a realistic distribution feeder. Finally, we calculate the costs of EV charging for customers and the distribution utility. We find that current tariff designs do not support large-scale deployments of EVs without system upgrades or additional control measures. We also find that customers can reduce costs nearly 15% by switching retail tariffs, leading to a potential revenue gap for the utility. Finally, we show that new power subscription-based tariffs are less efficient than traditional demand charge-based tariffs, and instead, designing tariffs for load optimization can reduce costs for both the customer and the utility.
{"title":"The Impacts of Retail Tariff Design on Electric Vehicle Charging for Commercial Customers","authors":"Phillippe K. Phanivong;Duncan S. Callaway","doi":"10.1109/TEMPR.2023.3343631","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3343631","url":null,"abstract":"Power engineers have examined the potential impacts on the electric grid of high electric vehicle (EV) adoption, while energy economists have shown issues with modern electricity retail tariff design. However, little work has shown how customer decisions regarding their tariff and optimizing EV charging costs could affect the utility and the customer. If commercial customers can optimize their charging profile, how do different tariff structures affect local distribution system voltage, utility cost recovery, and customer bills? To answer this question, we model commercial customers optimizing their EV charging to minimize costs using real-world tariffs. Then, we model the voltage impacts of customers charging EVs on a realistic distribution feeder. Finally, we calculate the costs of EV charging for customers and the distribution utility. We find that current tariff designs do not support large-scale deployments of EVs without system upgrades or additional control measures. We also find that customers can reduce costs nearly 15% by switching retail tariffs, leading to a potential revenue gap for the utility. Finally, we show that new power subscription-based tariffs are less efficient than traditional demand charge-based tariffs, and instead, designing tariffs for load optimization can reduce costs for both the customer and the utility.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"2 1","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135280","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 : 2023-12-13DOI: 10.1109/TEMPR.2023.3333487
{"title":"IEEE Power & Energy Society Information","authors":"","doi":"10.1109/TEMPR.2023.3333487","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3333487","url":null,"abstract":"","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10359324","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138633931","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：