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A Distributionally Robust Approach for Transmission and Energy Storage Capacity Planning in a Remote Photovoltaic Power Plant

机译：分布式光伏电站输电和能量存储容量规划的鲁棒方法

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Photovoltaic (PV) power plants have developed rapidly in the past decade. In China, solar resources are abundant in the west, which is far away from the load center. The PV power plant there has to be connected to the power grid by a long transmission line. To further reduce the impact of its volatility on the power grid, energy storage can be built inside the PV power plant and the capacity requirement of the transmission line decreases. This paper proposes a method that jointly plans the capacity of the transmission and energy storage for a remote PV power plant. Since the historical data of the solar source may not be accurate enough, the distributionally robust optimization (DRO) technique based on Kullback-Leibler divergence (KL-divergence) is adopted, so that the difference between the empirical distribution and the real distribution is considered. Then a tractable form is derived, which comes down to linear programming. The effectiveness of the proposed method is shown through a test case of a 200MW PV power plant.
机译：光伏（PV）电厂在过去十年中发展迅速。在中国，西部的太阳能资源丰富，远离负载中心。那里的光伏电站必须通过一条较长的传输线连接到电网。为了进一步减少其波动性对电网的影响，可以在光伏电站内部建立能量存储，并降低输电线路的容量要求。本文提出了一种共同规划远程光伏电站的输电和储能能力的方法。由于太阳能的历史数据可能不够准确，因此采用了基于库尔贝克-莱布里埃散度（KL-散度）的分布鲁棒优化（DRO）技术，因此考虑了经验分布与实际分布之间的差异。然后得出一个易于处理的形式，该形式可以归结为线性编程。通过一个200MW光伏电站的测试案例证明了该方法的有效性。

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