Capacity Configuration Optimization of Micro-grid System basedon Quantum Particle Swarm Algorithm

• Main Authors: Yuqiong Zhang, Ziwei Chen, Zhifang Shao, Qiang Zhao, Chuyin Han
• Format: Article
• Language: English
• Published: EDP Sciences 2021-01-01
• Series: E3S Web of Conferences
• Online Access: https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/28/e3sconf_pgsge2021_01021.pdf

The optimized configuration of wind/photovoltaic/storage micro-grid system capacity can realize multi-energy complementation and improve the stability and economy of grid-connected operation of power generation units. In this paper, the capacity of each core component of the micro-grid system under different combination paths such as Wind-PV power generation, battery energy storage, hydrogen production by electrolysis, and fuel cell power generation are optimized and economically analyzed. Taking the FCFF (Free Cash Flow of Firm) net present value maximization of the system running for 20 years as the objective function, considering the impact of energy shortage rate and dynamic electricity price, an operation research optimization model is established and intelligent algorithms are used to solve the model. The model can flexibly realize capacity optimization under different micro-grid combination paths, and it can prevent the solution result from falling into the local optimum through the design of quantum particle swarm algorithm. We analyzed the optimization results in terms of economic benefits, social benefits, and environmental benefits, and further analyzed the annual power generation status of the system and the operation status of the electrolysis hydrogen production system. The calculation example shows that under the current technical conditions, the micro-grid system composed of wind and solar power generation, electrochemical energy storage, and hydrogen production by electrolysis has better economic, social and environmental benefits than other models.