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Robust optimization of power network operation: storage devices and the role of forecast errors in renewable energies

机译:电网运行的稳健优化:存储设备和预测误差在可再生能源中的作用

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In this paper we investigate a robust optimization framework for controlling energy storage devices in power networks with high share of fluctuating renewable energy sources. Our approach relies on the industry-standard DC power flow approximation, together with a multi-stage model that incorporates renewable uncertainty and an approximation of battery dynamics. More precisely, we consider storage device operation under linear control and taking into account power limits, energy conversion efficiencies, and energy limits for the state of charge. The aim of the robust optimization is to minimize costs for generating energy from conventional power generators while relying on storage to compensate for renewable output forecast errors. In order to obtain a solution we propose a cutting-plane procedure which can be used for investigating practical case studies.
机译:在本文中,我们研究了一种稳健的优化框架,用于控制电网中波动较大的可再生能源的储能设备。我们的方法依赖于行业标准的DC功率流逼近以及结合可再生不确定性和电池动态逼近的多阶段模型。更准确地说,我们考虑线性控制下的存储设备操作,并考虑了功率限制,能量转换效率和充电状态的能量限制。稳健优化的目的是最大程度地降低常规发电机产生能源的成本,同时依靠存储来补偿可再生能源输出预测误差。为了获得解决方案,我们提出了一种切平面程序,该程序可用于调查实际案例研究。

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