A Bilevel Optimization Model-Based Planning Method for Building Integrated Photovoltaic and Storage Systems

This article addresses the issues of capacity optimization configuration and energy scheduling within Building Integrated Photovoltaic and Storage Systems (BIPV) and proposes a comprehensive design method. By establishing a dual-layer coupled model, this method considers the interdependence between system capacity and energy scheduling, as well as the cost and benefits over the entire life cycle of the system. The outer layer of the model targets the shortest investment payback period for the configuration of photovoltaic and energy storage capacities; the inner layer aims to maximize daily operational profits, utilizing an improved Particle Swarm Optimization (PSO) algorithm to enhance convergence speed and global optimization capabilities. This approach not only optimizes energy scheduling strategies and effectively exploits the peak-valley arbitrage mechanism of the storage system to shorten the payback period, but it also possesses excellent universality and portability, adapting to various regional and electricity market policies to meet diverse needs. Additionally, the method enhances the economic viability of BIPV systems, facilitating their large-scale promotion and construction.