Author:
Cui Shaofeng,Li Wei,Sui Hailin,Xu Yibin,Wang Baoxiang,Qi Weiping,Sun Shaoyang,Li Guo
Abstract
Abstract
Photovoltaic (PV) is becoming popular in many countries. However, due to the influence of weather, the PV output power often fluctuates greatly in a short time, and its intermittence makes it difficult to meet the load demand. The Hybrid energy storage system (HESS) can smooth the PV power fluctuation and optimize the operation of the whole system. Therefore, this paper proposes a capacity configuration strategy for the HESS composed of a battery and super capacitor. The strategy aims to minimize the construction and operation costs. It contains a two-layer optimization model. The upper layer configures the capacity and output power of the HESS, and the lower model optimizes the operation of the PV-HESS system and solves the model through deep reinforcement learning. Finally, a PV demonstration project in Shandong Province, China, is taken as an example to verify the effectiveness of the HESS capacity configuration strategy.
Subject
General Physics and Astronomy
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