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Optimal Scheduling of TCL and Storage Devices for Demand Side Management: A Game Theoretic Approach

机译:用于需求方管理的TCL和存储设备的最佳调度:一种博弈论方法

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The future grid encourages the integration of renewable energy sources (RES) with the power grid to mitigate the problem of demand-supply mismatch. However, the stochastic nature of RES along with randomness in load demand gives rise to uncertainties in the grid, in turn, the mismatch in demand-supply, which can deteriorate the voltage profiles and system performance. Flattening of load curve at demand side overcomes this demand-supply mismatch problem. In this paper, the decentralized load control problem is solved by a game theoretic approach where every customer is driven to optimize the use of RES, a battery storage system (BSS), electrical vehicle (EV), and thermostatically controlled loads (TCL), to map the demand-supply requirement. The proposed scheme smoothens the consumers’ load profile, which ensures an optimal solution in real-time.
机译:未来的电网鼓励将可再生能源(RES)与电网集成在一起,以缓解供需不匹配的问题。但是,RES的随机性以及负载需求的随机性会引起电网的不确定性,进而导致需求电源的不匹配,这可能会使电压曲线和系统性能恶化。需求侧负载曲线的平坦化克服了这个需求-供应不匹配的问题。本文采用博弈论方法解决了分散式负载控制问题,在这种方法中,每个客户都被驱动以优化RES的使用,电池存储系统(BSS),电动汽车(EV)和恒温控制负载(TCL),绘制供需图。拟议的方案使消费者的负载曲线变得平滑,从而确保了实时的最佳解决方案。

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