Multi-Source Collaborative Control Technology of Photovoltaic Power Generation Based on Differential Evolution-Gray Wolf Optimization Algorithm

Abstract

The existing photovoltaic power generation multi-source collaborative control technology cannot improve the control effect of microgrid, resulting in high peak load balancing cost of microgrid. Therefore, the photovoltaic power generation multi-source collaborative control technology based on differential evolution (DE)-gray wolf optimization (GWO) algorithm is adopted. The main components of the microgrid system, such as photovoltaic power generation equipment, hydroelectric power generation equipment, and battery pack, are modeled. With the goal of minimum peak cost and maximum transmission power, collaborative control of water, light and energy storage is carried out. The gray Wolf algorithm is used to solve the multi-objective problem of water and light storage in microgrid, and the gray Wolf algorithm is optimized by DE algorithm. Experiments show that the convergence speed of the optimized DEVOLU-Gray Wolf algorithm is obviously accelerated, and the problem of falling into the local optimal solution is completely avoided. After the application of this method, the photovoltaic, hydraulic, and battery of the microgrid run in order, ensure the smooth operation of the microgrid, and improve the economic benefit of the microgrid.

Keywords:

• microgrid
• differential evolution
• grey wolf algorithm
• collaborative control
• photovoltaic power generation
• waterpower

Disclosure statement

The author declares that there is no conflict of interest regarding the publication of this paper.

Additional information

Funding

The study was supported by a Technology Research Project from State Grid Zhejiang Electric Power Company Ltd. (No. 5211QZ230002).

Notes on contributors

Xuan Xu

Xuan Xu male, with a Master’s degree in Power System and Automation. He is an engineer at the Power Dispatching and Control Center of State Grid Zhejiang Quzhou Power Supply Company. His main research direction is power system dispatch and operation work.

Chao Fang

Chao Fang female, holds a Master’s degree in Power System and Automation. She is a senior engineer at the Power Dispatching and Control Center of State Grid Zhejiang Quzhou Power Supply Company. Her main research direction is power system dispatching automation work.

Zhanglei Zheng

Zhanglei Zheng male, holds a Bachelor’s degree in Information and Computing Science. He is an engineer at the Technology Digitalization Department of State Grid Zhejiang Quzhou Power Supply Company. His main research direction is the digitization of power systems.

Wencheng Zheng

Wencheng Zheng male, holds a Master’s degree in Power System and Automation. He is a senior engineer at the Power Dispatching and Control Center of State Grid Zhejiang Quzhou Power Supply Company. His main research direction is power system dispatch and operation work.

Yang Yu

Yang Yu with a Master’s degree in Electrical Engineering. He is an engineer at the Technology Digitalization Department of State Grid Zhejiang Quzhou Power Supply Company. His main research direction is power big data work.