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Decentralized Programming of Energy Storage System for the Promotion of Wind Power Consumption in Distribution Network

机译:提升配电网风电能耗的储能系统分散规划

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The environmental pollution and ecological damage caused by conventional energy source result in a great demand of renewable energy including wind power and photovoltaic. Especially in modern power system, wind farms have been wildly constructed and deployed. However, along with the increasing penetration of wind power, the operations of power system are significantly influenced due to the fluctuation and uncertainty of wind power. Due to its flexible charging and discharging characteristics, energy storage system (ESS) is considered as an effective tool to deal with the disadvantage of wind power and enhance the controllability of the power grid. In order to Figure out the optimal location and capacity of ESS, this paper presents a two-stage robust optimization model which takes the fluctuation and uncertainty of wind power into account. Additionally to find out the optimized solution, the second-order cone relaxation technique is adopted to guarantee the global optimal solution. Moreover, the strong duality theorem is employed to convert the optimal operation problem with max-min structure into an equivalent maximization problem. Finally, the model is solved by column and constraint generation algorithm. Experiment results indicate the effectiveness of the presented method in dealing with the ESS optimal allocation issues by considering the uncertainty of wind power.
机译:常规能源造成的环境污染和生态破坏导致对包括风力发电和光伏发电在内的可再生能源的巨大需求。特别是在现代电力系统中,风电场已被疯狂地建设和部署。然而,随着风电渗透的增加,由于风电的波动和不确定性,对电力系统的运行产生了重大影响。由于其灵活的充电和放电特性,储能系统(ESS)被认为是解决风力发电缺点并增强电网可控性的有效工具。为了找出ESS的最佳位置和容量,本文提出了一个两阶段的鲁棒优化模型,该模型考虑了风能的波动和不确定性。为了找出最优解,还采用了二阶锥松弛技术来保证全局最优解。此外,采用强对偶定理将具有最大-最小结构的最优运算问题转换为等效的最大化问题。最后,通过列和约束生成算法对模型进行求解。实验结果表明,该方法通过考虑风电的不确定性,可以有效地解决ESS最优分配问题。

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