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Dynamic and adaptive reconfiguration of electrical distribution system including renewables applying stochastic model predictive control

机译:包含随机模型预测控制的包括可再生能源在内的配电系统的动态和自适应重配置

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摘要

In this study, the structure of an electrical distribution network, which includes several electrical distribution feeders, is adaptively and dynamically reconfigured to minimise the daily operation cost of system that is under control of a local distribution company. Herein, for the first time, stochastic model predictive control (MPC) concept is applied in the problem to have dynamic and adaptability futures in the optimisation problem and to deal with the uncertainty and variability issues of renewable energy resources. The daily operation cost of distribution system comprises hourly energy loss cost of electrical feeders and switching cost of initially open and close switches installed on each feeder. The numerical study shows the existence of notable potential in reconfiguration of distribution system for energy loss and operation cost reduction. In addition, it is demonstrated that applying MPC in the optimal reconfiguration of distribution system results in better consequences in the presence of variable power of renewables. Moreover, it is proven that application of MPC in the problem increases the robustness and resiliency of optimisation procedure with respect to the prediction errors due to dynamic and adaptability characteristics of MPC.
机译:在这项研究中,包括几个配电馈线的配电网络的结构被自适应地和动态地重新配置,以最小化受本地配电公司控制的系统的日常运营成本。在此,首次将随机模型预测控制(MPC)概念应用于该问题,以使优化问题具有动态和适应性的未来,并处理可再生能源的不确定性和可变性问题。配电系统的日常运行成本包括电馈线的每小时能量损失成本以及安装在每个馈线上的初始打开和关闭开关的开关成本。数值研究表明,配电系统的重构具有降低能耗和降低运营成本的显着潜力。另外,证明了在可再生能源存在可变功率的情况下,将MPC应用到配电系统的最佳重新配置中会产生更好的结果。而且,已经证明,由于MPC的动态和适应性特征,MPC在该问题中的应用提高了针对预测误差的优化过程的鲁棒性和弹性。

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