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Two-level Day-ahead Optimal Scheduling of Distributed Energy Storage System

机译:分布式能量存储系统的两级前方最佳调度

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Stochastic characteristics of wind and photovoltaic (PV) power causes great challenge for power system operations. Distributed energy storage system (DESS) can mediate the intermittent renewable energy. This paper proposes a two-level optimization method for DESS scheduling. Firstly, DESSs are aggregated in a virtual power plan (VPP) and participates the power scheduling as a whole, the power schedules of DESSs are obtained with the proposed two-level optimization method. Secondly, in the upper-level optimization model, a two-stage stochastic unit commitment model is established with considering power uncertainties, and thermal units as well as VPP of DESS are optimized to maximize the power generation of renewable energy. And then, in the lower-level optimization model, an optimization model is proposed to schedule each DESS in order to minimize the total life loss cost of DESSs. Case studies are inducted based on actual data of a provincial power grid. The effectiveness and practicability of the proposed method is verified by the testing results.
机译:风和光伏(PV)电力的随机特性对电力系统操作引起了极大的挑战。分布式储能系统(DESS)可以介导间歇性可再生能源。本文提出了一种用于DESS调度的两级优化方法。首先,DESS在虚拟电力计划(VPP)中聚合并参与整体的电源调度,使用所提出的两级优化方法获得DESS的电源调度。其次,在上层优化模型中,考虑到电源不确定性,以及热量单位以及DES的V​​PP进行了优化,以最大化可再生能源的发电。然后,在较低级优化模型中,提出了一种优化模型来安排每个DES来最小化DESS的总寿命损失成本。基于省级电网的实际数据,案例研究。通过测试结果验证了所提出的方法的有效性和实用性。

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