%0 Journal Article %1 noauthororeditor %A Xu, Chun-yu %A Lin, Jun-hua %A Lin, Qin-ming %A Zhang, Yuan-biao %D 2018 %J International Journal of Engineering and Management Research %K Algorithm Genetic Laying Multi Objective Optimization System %N 6 %P 69-80 %R 10.31033/ijemr.8.6.7 %T Construction of Solar Panel Laying System based on Genetic Algorithm %U http://www.ijemr.net/DOC/ConstructionOfSolarPanelLayingSystemBasedOnGeneticAlgorithm.pdf %V 8 %X 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.

@article{noauthororeditor, abstract = {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. }, added-at = {2019-02-13T07:45:25.000+0100}, author = {Xu, Chun-yu and Lin, Jun-hua and Lin, Qin-ming and Zhang, Yuan-biao}, biburl = {https://www.bibsonomy.org/bibtex/2bb2fc45deef64ae567a2c3b4c70eca21/amarjeetsingh}, doi = {10.31033/ijemr.8.6.7}, interhash = {80bae197363878e5f918997b833b4b4d}, intrahash = {bb2fc45deef64ae567a2c3b4c70eca21}, issn = {2250-0758}, journal = {International Journal of Engineering and Management Research}, keywords = {Algorithm Genetic Laying Multi Objective Optimization System}, number = 6, pages = {69-80}, timestamp = {2019-02-13T07:45:25.000+0100}, title = {Construction of Solar Panel Laying System based on Genetic Algorithm }, url = {http://www.ijemr.net/DOC/ConstructionOfSolarPanelLayingSystemBasedOnGeneticAlgorithm.pdf}, volume = 8, year = 2018 }