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The Evaluation of Agile Demand Response: An Applied Methodology

机译:敏捷需求响应评估:一种应用方法

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This paper formulates an applied methodology for an agile demand response using mathematical micromodels. The optimal strategy chosen by an aggregator is the maximization of social welfare derived from demand flexibility. The notion of complex demand bidding is already given in the literature, however heretofore it is formulated as the relationship of price with both demand elasticity and marginal cost along with temporal and profit constraints. Although the planning of flexible demand is already handled by using advance learning techniques in literature, herein simple Q-learning technique in a decentralized fashion is proposed. Moreover, trade-offs between the proposed complex bidding rules are explored in a day-ahead market context. Due to the given complex bidding rules and principle of learning, the methodology can be easily applied in active distribution network. Several number of houses, equipped with the proposed complex bidding mechanism and decentralized learning capability, has been simulated, thus illustrating the application of methodology formulated herein.
机译:本文使用数学微观模型制定了敏捷需求响应的应用方法。整合者选择的最佳策略是最大化需求灵活性带来的社会福利。复杂的需求竞标的概念已经在文献中给出,但是迄今为止,它被表述为价格与需求弹性和边际成本以及时间和利润约束的关系。尽管在文献中已经通过使用高级学习技术来处理柔性需求的计划,但是在此提出了以分散方式进行的简单Q学习技术。此外,在日复一日的市场环境中探索了提议的复杂竞标规则之间的取舍。由于给出了复杂的投标规则和学习原理,因此该方法可以轻松地应用于主动配电网络。已模拟了数套配备了建议的复杂招标机制和分散式学习能力的房屋,从而说明了本文阐述的方法的应用。

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