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Optimal pricing for residential demand response: A stochastic optimization approach

机译:住宅需求响应的最优定价:一种随机优化方法

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The problem of optimizing retail electricity price for residential demand response is considered. A two stage stochastic optimization is formulated in which the retailer optimizes the day ahead price in the first stage, and residential customers schedule their demands optimally in respond to the optimized retail price and in a distributed fashion. For the control of thermal dynamic loads, the optimal residential demand response policy is obtained based on a form of consumer surplus that captures the tradeoff between comfort level and cost. It is shown that the optimal control is an affine function of the retail price with a negative definitive factor matrix. The optimal retail pricing is obtained through a convex program that maximizes average profit or a form of conditional value at risk. Effects of incorporating renewable energy are also considered.
机译:考虑了优化零售电价以应对居民需求的问题。制定了一个两阶段的随机优化方法,其中零售商在第一阶段优化前一天的价格,而居民客户则根据优化的零售价格并以分布式方式优化其需求计划。为了控制动态热负荷,基于一种消费者剩余形式获取了最佳的居住需求响应策略,该形式捕获了舒适水平和成本之间的权衡。结果表明,最优控制是零售价格的仿射函数,具有负的确定性因子矩阵。最佳零售价格是通过凸计划获得的,该计划使平均利润或某种形式的有条件价值风险最大化。还考虑了结合可再生能源的效果。

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