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Optimal operation strategy for interconnected microgrids in market environment considering uncertainty
Applied Energy ( IF 11.2 ) Pub Date : 2020-06-23 , DOI: 10.1016/j.apenergy.2020.115336
Xiangyu Kong , Dehong Liu , Chengshan Wang , Fangyuan Sun , Shupeng Li

The interconnected microgrid system (IMS) is a promising solution for the problem of growing penetration of renewable-based microgrids into the power system. To optimally coordinate the operation of microgrids owned by different owners while considering uncertainties in market environment, a bi-level distributed optimized operation method for IMS with uncertainties is proposed in this paper. A hierarchical and distributed operational communication architecture of IMS is first established. A bi-level distributed optimization model was built for IMS, where at the upper level, the IMS operates purchase-sale mode or demand response mode with the distribution network operator and optimizes the trading power with microgrids to maximize revenue. At the lower level, the chance constraint programming is used to describe and deal with the uncertainty of renewable energy and loads and optimize the output and energy storage of distributed energy with the goal of minimum cost. The analytical target cascading and augmented Lagrange method are combined to decouple and reconstruct the bi-level model for distributed solution and establishing a fair price mechanism. The optimal solutions of the problem are obtained through parallel iteration, in which the price signal plays a coordinated role in the distributed iterative optimization process. Abundant case studies verify the advantages of the model and the performance of the proposed method.



中文翻译:

考虑不确定性的市场环境下互联微电网的最优运行策略

互连微电网系统(IMS)是解决基于可再生能源的微电网日益渗透到电力系统中的一个有前途的解决方案。为了在考虑市场环境不确定性的同时,优化不同所有者拥有的微电网的运行,提出了一种具有不确定性的IMS的双层分布式优化运行方法。首先建立IMS的分层和分布式操作通信体系结构。为IMS构建了一个双层分布式优化模型,其中,IMS在较高级别上与配电网络运营商一起运行买卖模式或需求响应模式,并通过微电网优化交易能力以最大化收入。在较低的级别,机会约束编程用于描述和处理可再生能源和负荷的不确定性,并以最低成本为目标优化分布式能源的输出和储能。结合分析目标级联和增强拉格朗日方法,对分布式解决方案的双层模型进行解耦和重构,并建立了公平的价格机制。通过并行迭代获得问题的最优解,其中价格信号在分布式迭代优化过程中起协调作用。大量的案例研究证明了该模型的优点以及所提出方法的性能。结合分析目标的级联和增强的拉格朗日方法,对分布式解决方案的双层模型进行解耦和重构,并建立了公平的价格机制。通过并行迭代获得问题的最优解,其中价格信号在分布式迭代优化过程中起协调作用。大量的案例研究证明了该模型的优点以及所提出方法的性能。结合分析目标级联方法和增强拉格朗日方法,对分布式解决方案的双层模型进行解耦和重构,建立了公平的价格机制。通过并行迭代获得问题的最优解,其中价格信号在分布式迭代优化过程中起协调作用。大量的案例研究证明了该模型的优点以及所提出方法的性能。

更新日期:2020-06-23
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