Integrating EVs into distribution grids — Examining the effects of various DSO intervention strategies on optimized charging

IF 10.1 1区 工程技术 Q1 ENERGY & FUELS Applied Energy Pub Date : 2024-11-01 DOI:10.1016/j.apenergy.2024.124775
Arne Lilienkamp , Nils Namockel
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Abstract

Adopting electric vehicles (EVs) and implementing variable electricity tariffs increase peak demand and the risk of congestion in distribution grids. To avert critical grid situations and sidestep expensive grid expansions, Distribution System Operators (DSOs) must have intervention rights, allowing them to curtail charging processes. Various curtailment strategies are possible, varying in spatio-temporal differentiation and possible discrimination. However, evaluating different strategies is complex due to the interplay of economic factors, technical requirements, and regulatory constraints — a complexity not fully addressed in the current literature. Our study introduces a sophisticated model to optimize electric vehicle charging strategies to address this gap. This model considers different tariff schemes (Fixed, Time-of-Use, and Real-Time) and incorporates DSO interventions (basic, variable, and smart) within its optimization framework. Based on the model, we analyze the flexibility demand and total electricity costs from the users’ perspective. Applying our model to a synthetic distribution grid, we find that flexible tariffs offer consumers only marginal economic benefits and increase the risk of grid congestion due to herding behavior. All curtailment strategies effectively alleviate congestion, with variable curtailment featuring spatio-temporal differentiation, approaching optimality regarding flexibility demand. Notably, applying curtailment from the users’ perspective does not lower cost savings significantly.
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将电动汽车纳入配电网 - 研究各种配电网服务公司干预策略对优化充电的影响
电动汽车(EV)的采用和可变电价的实施增加了高峰需求和配电网拥塞的风险。为了避免出现严重的电网状况,避免昂贵的电网扩建,配电系统运营商(DSO)必须拥有干预权,允许他们削减充电过程。可以采取多种削减策略,这些策略在时空差异和可能的区别对待方面各不相同。然而,由于经济因素、技术要求和监管限制的相互作用,对不同策略的评估非常复杂--目前的文献尚未充分解决这一复杂性。我们的研究引入了一个复杂的模型来优化电动汽车充电策略,以弥补这一不足。该模型考虑了不同的电价方案(固定电价、使用时间电价和实时电价),并将 DSO 干预(基本干预、可变干预和智能干预)纳入其优化框架。基于该模型,我们从用户的角度分析了灵活性需求和总电力成本。将我们的模型应用于合成配电网,我们发现灵活电价只能为消费者带来边际经济效益,并且由于羊群行为会增加电网拥塞的风险。所有缩减策略都能有效缓解拥堵,其中可变缩减具有时空差异,接近灵活性需求的最优化。值得注意的是,从用户角度实施缩减并不会显著降低成本节约。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Applied Energy
Applied Energy 工程技术-工程:化工
CiteScore
21.20
自引率
10.70%
发文量
1830
审稿时长
41 days
期刊介绍: Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.
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