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Wind-ES Coordinated Scheduling Optimization Model Considering Electric Vehicles as Flexible Load

机译:以电动汽车为柔性负荷的风电协调调度优化模型

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The randomness of wind generation is one of the main factors restricting gird connection of wind generation. The involvements of energy storage systems and resources used for demand response in the process of optimization for wind power are useful means to enhance its regulation capacity. Considering the uncertainty of wind generation in day-ahead plans, this paper proposes a coordinated scheduling optimization model for Wind-ES hybrid systems with demand response via electric vehicles. The model can be used to apply energy storage systems and electric vehicles simultaneously to both peak shaving/valley filling and wind generation plan tracking to achieve the coordination between the on-grid revenue and penalty cost of the hybrid system, so as to develop the optimal strategy for maximum benefits. The wind power is modeled by using scenario analysis method, and the mixed integer programming problem of this paper is solved via CPLEX software. The case study results show that the coordinated scheduling optimization model can not only earn additional revenue for electric vehicle owners, but also effectively improve the economy of wind power grid connection, which provides an important reference for scheduling the demand response resources of electric vehicles to consume wind generation.
机译:风力发电的随机性是限制风力发电网架连接的主要因素之一。风力发电优化过程中涉及能量存储系统和用于需求响应的资源是增强其调节能力的有用手段。考虑到日前计划中风力发电的不确定性,本文提出了具有电动汽车需求响应的Wind-ES混合动力系统的协调调度优化模型。该模型可用于同时应用储能系统和电动汽车进行调峰/谷灌和风力发电计划跟踪,以实现混合动力系统的并网收益与惩罚成本之间的协调,从而开发出最优的混合动力系统。最大利益的策略。利用情景分析方法对风电进行建模,并通过CPLEX软件解决了本文的混合整数规划问题。案例研究结果表明,协调调度优化模型不仅可以为电动汽车所有者带来额外的收入,而且可以有效提高风电并网的经济性,为调度电动汽车的需求响应资源消耗提供重要参考。风力发电。

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