一种缩小CCHP系统优化调度解空间的方法  

AN OPTIMAL SCHEDULING SCHEME OF CCHP SYSTEMS BY REDUCING SOLUTION SPACE

作　　者：周文操 张学军[1] 闫来清 Zhou Wencao;Zhang Xuejun;Yan Laiqing(College of Electric Power,Civil Engineering and Architecture,Shanxi University,Taiyuan 030031,China)

机构地区：[1]山西大学电力与建筑学院,太原030031

出　　处：《太阳能学报》2023年第11期556-564,共9页Acta Energiae Solaris Sinica

基　　金：中央高校基本科研基金(2018QN097);山西省高校科技创新项目(2021L012)。

摘　　要：在冷热电联供(CCHP)系统中以生物质作为燃气发电的燃料,建立同时考虑光伏、风电消纳、储能电池寿命、CO_(2)排放与电网能量交互及各产能设备间不同能量形式的转换关系等因素的CCHP系统多目标日运行调度模型,针对混合热电(FHL)运行模式解空间偏大的问题,提出通过剔除明显不经济、不环保、不可能的运行工况来缩小每时段解空间的方法,提高了计算效率和获得全局最优解的可能性。在此基础上,采用改进权重的变学习因子粒子群算法求出算例系统的调度方案,结果表明,该文所提方法不仅缩短了FHL运行模式的求解时间,还能使该运行模式获得更好的经济和环境收益。Based on combined cooling heating and power(CCHP)system that uses biomass as a fuel for gas-fired power generation,an optimal scheduling model for the CCHP system multi-objective daily operation is established,which also deals with factors such as PV,wind power consumption,energy storage battery life,CO_(2) emissions,energy interaction with the grid and the conversion relationship among different forms of energy of capacity devices.Aiming at the problem of large operating mode solution space of following hybrid load(FHL),this paper presents a new scheme to reduce the solution space per period by eliminating obviously uneconomic,environmentally unfriendly and impossible operating conditions,and thus the computational efficiency and the possibility of obtaining the globally optimal solution can be improved.On this basis,the scheduling scheme of the arithmetic case system is derived using particle swarm optimization by changing the learning factor with improved weights.The method proposed in this paper not only shortens the solution time of the FHL operation mode,but also leads to better economic and environmental benefits of this operation mode.

关 键 词：冷热电联供系统 多目标优化 能量利用 粒子群算法 调度优化 

分 类 号：TK513.5[动力工程及工程热物理—热能工程]