A Comprehensive Optimization Method for Planning and Operation of Building Integrated Photovoltaic Energy Storage System

被引：0

作者：

Chen K. ^{[1
]}

Xiao X. ^{[1
]}

Tian P. ^{[1
]}

Feng K. ^{[2
]}

Sun P. ^{[2
]}

机构：

[1] Department of Electrical Engineering, Tsinghua University, Haidian District, Beijing

[2] Pingliang Power Supply Company, State Grid Gansu Electric Power Company, Gansu Province, Pingliang

来源：

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2023年 / 43卷 / 13期

关键词：

building integrated photovoltaic (BIPV) system; capacity allocation; energy scheduling strategy; particle swarm optimization algorithm (PSO);

D O I：

10.13334/j.0258-8013.pcsee.220820

中图分类号：

学科分类号：

摘要：

Optimal capacity allocation and energy scheduling are the core problems of planning and operation stages of building an integrated photovoltaic (BIPV) system. A comprehensive design method for capacity allocation and energy scheduling is presented. Considering the coupling effects, a two-layer coupling model is established with the cost and benefit as the decisive elements under the whole life cycle. In the outer model, the shortest payback period is taken as the objective function to optimize the allocation of photovoltaic and energy storage capacity. The inner model is solved with the objective of maximizing the daily operating revenue to obtain a comprehensive optimal energy scheduling strategy. The particle swarm optimization algorithm (PSO) is improved, which effectively improves the convergence speed and enhances the global optimization ability. Compared with other scheduling strategies, “peak-valley arbitrage” of the energy storage system is utilized to shorten the investment payback period. This method can comprehensively assess the economics of BIPV systems and apply to different regions with flexible electricity market policies, and it is universal and portable to meet the diverse needs of different scenarios. ©2023 Chin.Soc.for Elec.Eng.

引用

页码：5001 / 5011

页数：10