Research on integrated energy system planning optimization based on multi-objective genetic algorithm

Rong Yiping; Zhang Aiqun; Liu Jiyan; Ju Wenjie; Tang Xiaoguang; Xu Xiaolong

Abstract：Aiming at how to effectively improve the energy utilization efficiency of the integrated energy system to meet the diversified energy needs of the system and promote the sustainable development of energy,this paper firstly establishes the constraints and power model including photovoltaic,CCHP,energy storage battery,ice storage tank,establishes the economic model including investment cost,maintenance cost and carbon emission cost,establishes the energy efficiency model including power quality,considers the construction constraints including unit building area,and then uses genetic optimization algorithm to plan and optimize the capacity of the equipment.The energy efficiency model including power quality,the construction constraints including unit floor area,etc.are considered,and then the genetic optimization algorithm is used to plan and optimize the equipment capacity.Finally,taking a certain park in Shenzhen as an example,after analyzing the economic development of the actual park,the regional characteristics,the energy supply,the resource endowment,and its load characteristics,the multi-energy coupling of the system is analyzed,and the integrated energy information system in the park is planned based on the multi-objective genetic algorithm,with the use of TTG,which is a multi-objective genetic algorithm.Based on the multi-objective genetic algorithm,the integrated energy information system of the park is planned,and the optimal scheme is ranked by the TOPSIS method.The planning and optimization method proposed in this paper can effectively configure equipment capacity,save costs for users,reduce pressure on the power grid,reduce carbon emissions,and improve the reliability of electricity consumption.