1Student, Department of Electronic Information Science and Technology, Electrical Information School of Jinan University, Zhuhai of China
2Student, Department of Finance Engineer, International Business School of Jinan University, Zhuhai of China
3Student, Department of Computer, Guangdong University of Foreign Studies, Guangzhou of China
4Professor, Department of Packaging Engineering, Jinan University, Zhuhai of China
*Corresponding Author: 13680324199@163.com
Online published on 7 February, 2019.
Solar power generation is an important energy resource in most countries. It plays an important role in meeting energy demand, improving energy structure and reducing environmental pollution. The main carrier of solar power generation is solar panels, but the utilization efficiency of most existing solar cells is low, which causes serious waste of solar energy. In response to this phenomenon, we propose a Solar Panel Laying System(SPLS) based on genetic algorithm(GA) to construct solar panels, which solves four problems: the determination of the number of battery components, the layout of the panels, the selection of the inverter and the connection of the inverter. In the SPLS, we introduce an improved genetic algorithm and multi-objective optimization solution. Under the double premise that the total amount of solar photovoltaic power generation is as large as possible and the cost per unit of power generation is as small as possible, the quantitative solution of the laying system is realized.
Genetic Algorithm, Multi-Objective Optimization, Laying System
