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Approximate dynamic programming-based decentralised robust optimisation approach for multi-area economic dispatch considering wind power uncertainty

机译:考虑风电不确定性的多区经济派遣基于动态编程的基于动态编程的分散鲁棒优化方法

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摘要

This study presents a fully decentralised robust optimisation (RO) approach for multi-area economic dispatch (MA-ED) in the presence of wind power uncertainty. Unlike traditional algorithms, the authors formulate this MA-ED problem as dynamic programming problem, and decompose the centralised robust MA-ED problem into a series of sub-problems based on approximate dynamic programming algorithm. The value functions are proposed for each area to iteratively estimate the impacts of its dispatches on the dispatches of other areas which make decisions subsequently. The proposed algorithm does not require a central operator but only needs to exchange a small amount of information among neighbouring areas to achieve fully decentralised decision-making. It is practical in cases where the centralised operator cannot be implemented considering the dispatch independence and the detailed data of one area is unavailable considering the privacy. Additionally, the accuracy, adaptability and computational efficiency of the proposed algorithm are illustrated using numerical simulations on two test systems and an actual power system.
机译:本研究介绍了风力不确定性存在的多区经济调度(MA-ED)的完全分散的鲁棒优化(RO)方法。与传统算法不同,作者将该MA-ED问题标制作动态编程问题,并将集中式鲁棒MA-ED问题分解为基于近似动态编程算法的一系列子问题。为每个区域提出了价值函数,以迭代地估计其调度对其他区域的派遣的影响,这些区域随后做出决定。所提出的算法不需要中央运营商,但只需要在邻近区域之间交换少量信息以实现完全分散的决策。在考虑调度独立性的情况下无法实现集中式运营商并且考虑隐私不可用的情况下无法使用的情况下,它是实用的。另外,使用两个测试系统和实际电力系统的数值模拟来说明所提出的算法的准确性,适应性和计算效率。

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