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高铁客运站分布式多能源系统供能协同优化策略研究 被引量:4

Research on cooperative energy supply optimization strategy of distributed multi-energy system for high-speed railway passenger station
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摘要 为解决传统高铁客运站供能系统中能源利用率较低的问题,以日运行购气费用和购电费用最优为优化目标,以系统运行过程中实时能量平衡为约束条件,以可再生能源出力和吸收式制冷占比为优化变量,建立多能源协同供能的分布式能源系统,并将该模型应用于北方某高铁客运站,分析可再生能源的利用率、制冷系统中可再生能源电出力的电制冷占比以及电网出力的节电率。仿真计算结果表明:分布式能源系统的使用提高了可再生能源的利用率,其中风电机组出力占其出力极限的96.50%,光伏机组出力94.70%;相比于参比系统,分布式能源系统的成本节约率为12.5%;电制冷占比为13.00%;电网的节电率为53.9%。 Tosolve the problem of lower energy efficiency in traditional energy supply systems for high-speed railway passenger station,an optimization model of distributed energy system with multi-energy supply is established,where the daily operation cost of gas and electricity is taken as the objective function,the electric refrigeration ratio and renewable energy output are regarded as optimization variables and the hourly energy balance is chosen as constraint.Furthermore,the model is applied to a high-speed rail passenger station to analyze the utilization rate of renewable energy,the proportion of electric refrigeration in the renewable energy output of the refrigeration system,and the power saving rate of the grid output.The simulation results show that the cost saving rate is 12.5%,the electric cooling ratio is 13.00%and the power saving rate of the power grid is 53.9%of distributed energy system compared with the reference system.The output of each power supply equipment is that the wind turbine is 96.50%and the output of the photovoltaic unit is 94.70%,which improves the utilization rate of renewable energy.
作者 李要红 杨斌 徐飞 魏名山 田冉 LI Yaohong;YANG Bin;XU Fei;WEI Mingshan;TIAN Ran(School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081,China;Engineering Managem ent Center,China National Railway Group CO.,Ltd.,Beijing 100844,China;State Key Laboratory of Control and Simulation of Power System and Generation Equipment,Department of Electrical Engineering,Tsinghua University,Beijing 100084,China)
出处 《热科学与技术》 CAS CSCD 北大核心 2020年第4期394-400,共7页 Journal of Thermal Science and Technology
基金 中国铁路总公司科技研究开发计划系统性重大资助项目(P2018G004)。
关键词 多能协同 分布式能源系统 电制冷比 优化 multi-energy coordinated energy supply distributed energy system electric cooling ratio optimization
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