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Bi-level programming optimization method of rural integrated energy system based on coupling coordination degree of energy equipment

能量(信号处理) 联轴节(管道) 环境经济学 计算机科学 数学优化 工程类 机械工程 数学 经济 统计
作者
Yongli Wang,Lu Guo,Yanan Wang,Yunfei Zhang,Siwen Zhang,Zeqiang Liu,Juntai Xing,Ximei Liu
出处
期刊:Energy [Elsevier BV]
卷期号:298: 131289-131289 被引量:21
标识
DOI:10.1016/j.energy.2024.131289
摘要

Promoting energy transformation in rural areas, building a Rural Integrated Energy System, and developing multi-energy complementary and comprehensive utilization of rural energy in accordance with local conditions are important paths to support global low-carbon transformation and rural revitalization. However, how to consider the coupling synergy of multiple devices and plan the capacity of multiple devices in rural energy systems in an economical, low-carbon, and reliable manner is an urgent issue facing the development of Rural Integrated Energy System. This paper proposes a bi-level programming optimization method of Rural Integrated Energy System based on coupling coordination degree of energy equipment. Firstly, a multi-dimensional rural user energy utilization framework is designed that comprehensively considers agriculture, animal husbandry, industry, and lifestyle. Secondly, the bi-level optimization model of the Rural Integrated Energy System based on the coupling coordination degree of energy equipment is constructed. The upper-level planning model puts forward the equipment coupling coordination degree, and determines the equipment selection scheme for different types of Rural Integrated Energy System planning. The lower-level planning model considers economy, low carbon, and reliability, and uses the improved multi-objective Harris Hawk optimization algorithm to solve the capacity of different energy equipment in the Rural Integrated Energy System. Finally, the effectiveness and scientific nature of the model and method proposed in this paper are verified by the Integrated Energy Systems of a rural area in the north of China. In addition, by comparing the equipment selection scheme with the traditional method, it can be found that the optimization scheme in this paper that considers the coupling coordination of energy equipment reduces the annualized total cost by 29.34%, reduces the annual carbon emissions by 60.43%, and increases the reliability by 15.85%. The collaborative planning of energy economy, low carbon energy and reliable energy has been realized.
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