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碳交易背景下基于LGPG-P2G的微电网容量优化配置
作者姓名:冯帅  袁至  王维庆  何山
作者单位:可再生能源发电与并网控制教育部工程研究中心(新疆大学), 新疆 乌鲁木齐 830017
基金项目:国家自然科学基金资助项目(52067020)
摘    要:优化传统微电网的容量配置对其经济性的提升效果有限。为进一步提升经济性,文中在传统微电网的基础上耦合垃圾填埋气发电(landfill gas power generation,LGPG)和电转气(power to gas,P2G),提出一种基于LGPG-P2G的微电网模型。首先,综合考虑碳交易和资金的时间价值对容量优化配置的影响,引入全生命周期理论和经济学中的净现值分析法;然后,以全生命周期的收益最大为目标,利用变异粒子群算法求解4种场景下的微电网容量最优配置,并使用Cplex求解传统微电网模型和所提微电网模型容量最优配置下的最优调度方案。结果表明在碳交易背景下基于LGPG-P2G的微电网模型具有更好的经济性。

关 键 词:微电网  垃圾填埋气发电(LGPG)  电转气(P2G)  碳交易  净现值分析法  容量配置
收稿时间:2022/11/12 0:00:00
修稿时间:2023/2/3 0:00:00

Optimization and configuration of microgrid capacity based on LGPG-P2G in the context of carbon trading
Authors:FENG Shuai  YUAN Zhi  WANG Weiqing  HE Shan
Affiliation:Engineering Research Center of Renewable Energy Power Generation and Grid-connected Control, Ministry of Education, Xinjiang University, Urumqi 830017, China
Abstract:The optimization of capacity allocation of traditional microgrid has limited effect on improving economic efficiency. To solve this problem,a microgrid model based on the coupling of landfill gas power generation (LGPG) and power to gas (P2G) is propoed to improve economic efficiency. Considering the influence of carbon trading and the time value of capital on the optimal allocation of capacity, the full life cycle theory and net present value analysis method in economics are introduced. Then the mutation particle swarm optimization algorithm is used to obtain the optimal allocation of capacity in four scenarios for maximizing the benefit of the whole life cycle. The optimal operation scheme is obtained by Cplex under the optimal allocation of capacity of the traditional microgrid model and the proposed microgrid model. The simulation results show that the economic efficiency of proposed microgrid model based on LGPG-P2G is higher than that of tranditionl microgrid model under the background of carbon trading.
Keywords:microgrid  landfill gas power generation (LGPG)  power to gas (P2G)  carbon trading  net present value analysis  capacity configuration
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