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An Online Adaptive Intelligent Framework for Customer Willingness Interpretation in Demand Response Exchange

机译:需求响应交换中客户意愿解释的在线自适应智能框架

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The demand response exchange presents an independent pool based market clearing mechanism dedicated for resources in the demand side. The active demand resources participate in the pool acting as demand response buyers. The of such buyers can be better represented by utilizing the concepts of fuzzy systems. This paper presents a methodology to enhance the benefit of DR sellers and buyers in the demand response exchange through fuzzy inference system. However, the performance of the fuzzy system is dependent on the structure of membership function and rule base. Thus, an adaptive way of membership function tuning has been adopted in this paper. The tuning of the parameters has been performed using various heuristic approaches to observe the performance of tuned fuzzy system for DRX application compared to traditional non- fuzzy and un-tuned models. The simulation experiments carried out with different load types in different seasons demonstrate the improvement in DRX welfare for adaptively tuned fuzzy system to the traditional and un-tuned models. The adaptive tuning presented in this paper can be used by individual DR seller to calculate the participation bids.
机译:需求响应交换提供了一个基于池的独立市场清除机制,专门用于需求侧的资源。活跃的需求资源作为需求响应购买者参与池中。通过使用模糊系统的概念可以更好地代表此类购买者。本文提出了一种方法,可以通过模糊推理系统增强DR卖方和买方在需求响应交换中的利益。但是,模糊系统的性能取决于隶属函数和规则库的结构。因此,本文采用了一种自适应的隶属函数调整方法。与传统的非模糊和未调整模型相比,已使用各种启发式方法对参数进行了调整,以观察针对DRX应用的调整后模糊系统的性能。在不同季节使用不同负载类型进行的仿真实验表明,自适应调整的模糊系统对传统模型和未调整模型的DRX福利有所提高。本文中介绍的自适应调整可由单个DR卖方用来计算参与投标。

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