Optimal Operation Strategy of Combined Photovoltaic and Storage System in Real Time Energy and Regulation Market

被引：0

作者：

Xie Y. ^{[1
]}

Gu Z. ^{[1
]}

Wang X. ^{[2
]}

Zhuo Y. ^{[3
]}

Wang K. ^{[4
]}

Geng J. ^{[4
]}

机构：

[1] School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, Jiangsu Province

[2] Wenzhou Port Group Co., Ltd., Wenzhou, 325000, Zhejiang Province

[3] Huayun Information Technology Co., Ltd., Hangzhou, 310008, Zhejiang Province

[4] China Electric Power Research Institute, Nanjing, 210003, Jiangsu Province

来源：

Dianwang Jishu/Power System Technology | 2020年 / 44卷 / 05期

基金：

中国国家自然科学基金;

关键词：

Energy market; Regulationmarket; Robust model predictive control; Robust optimization; The photovoltaic and storage system;

D O I：

10.13335/j.1000-3673.pst.2019.1363

中图分类号：

学科分类号：

摘要：

Due to the uncertainty of the photovoltaic output and the electric market price, the existing study mainly employsthe stochastic optimization method based on the probability scene. However, it is difficult to obtain accurate probability density function ofphotovoltaic output power and electric market price. The power producers will pay penaltydue to the deviation of bidding capacity. Therefore, this paper proposes arobust model predictive control basedoperation strategy forphotovoltaic and storage systemto maximizeitsprofilein the energy and regulationmarkets. Theoperation constraints of thephotovoltaic and storage system are considered, including charge, discharge, power and capacityconstraint ofstorage system, and output constraint of photovoltaic power. Forthe uncertainty of the photovoltaic output and the real-time market price, a multi-time step robust optimization model is established, which is transformed into a mixed integer linear programming model bydual theory. The transformed model can be solved efficiently by CPLEX, and the first time-step scheme in the optimization result is applied tothe system. Finally, the effectiveness of the proposed method is verified by the actual photovoltaic and storage data and the ERCOT electricity price data. © 2020, Power System Technology Press. All right reserved.

引用

页码：1758 / 1765

页数：7

共 26 条

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