多能微电网规划中的博弈论部门需求响应采购

Soheil Mohseni, A. Brent
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引用次数: 0

摘要

多能源社区微电网(MGs)已被认为是利用分布式需求侧灵活性资源的关键推动者,特别是在集成存储时。然而,目前关于需求响应集成的社区能源系统设计和调度优化的文献未能同时最大化多个能源载体的灵活性潜力,从而忽略了相关业务案例潜在的重大改进机会。为此,本文提出了一种新颖的基于纳什议价的合作博弈方法,用于解决以氢为运输燃料、为电力和热负荷服务的多能源社区mg的最优聚合器介导需求响应调度问题。更具体地说,拟议的方法系统而有效地描述了参与者如何在参与者的利益——MG运营商、部门需求响应聚合者和小规模最终用户——既不完全对立也不完全一致的假设下,以公平的方式分享需求侧管理产生的盈余。然后将提出的方法集成到基于元启发式的长期MG规划方法中。通过对新西兰aotearoa地区社区居民用户聚集方案的案例研究表明,与以下两种情况相比,该方法可以有效地将多能MG的总贴现系统成本分别降低约14%(相当于190万美元)和约31%(540万美元):(i)参与者的行为在自利假设下使用非合作博弈论来描述;(ii)没有实施需求响应计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Game-Theoretic Sectoral Demand Response Procurement in Multi-Energy Microgrid Planning
Multi-energy community microgrids (MGs) have been recognized as key enablers for harnessing distributed demand-side flexibility resources, especially when integrating storage. However, the literature on demand response-integrated community energy system design and dispatch optimization has, thus far, failed to concurrently maximize the flexibility potential in several energy carriers, thereby neglecting the potentially significant improvement opportunities of the associated business cases. In response, this paper introduces a novel Nash bargaining-based cooperative game approach for the optimal aggregator-mediated demand response scheduling of multi-energy community MGs serving electricity and thermal loads, as well as hydrogen as a transportation fuel. More specifically, the proposed approach systematically and effectively characterizes how the players share the resulting surplus from demand-side management in an equitable manner under the assumption that the interests of the players - the MG operator, sectoral demand response aggregators, and small-scale end-users - are neither completely opposed nor completely coincident. The proposed approach is then integrated into a meta-heuristic-based long-term MG planning method. A case study for a community-based residential users' aggregation scheme in Aotearoa-New Zealand demonstrates the effectiveness of the method in reducing the total discounted system cost of a multi-energy MG by ~14% (equating to US$1.9m) and ~31% (US$5.4m) respectively compared to the cases where: (i) the actors' behaviors are characterized using non-cooperative game theory under self-interestedness assumptions; and (ii) no demand response programs are implemented.
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