考虑需求响应的CCHP系统中分布式电源的选址定容

发布时间：2018-03-25 18:30

本文选题：冷/热/电联供(CCHP)系统　切入点：需求响应(DR)　出处：《电力建设》2017年12期

【摘要】：以往对于冷/热/电联供(combined cooling heating and power,CCHP)系统的研究主要集中在其运行优化上,较少对系统中分布式电源(distributed generation,DG)的选址定容问题进行研究,更少有文献将基于价格与基于激励的需求响应(demand response,DR)综合考虑在系统中。该文利用CCHP系统的多能源互补特性,综合考虑基于价格与基于激励的需求响应,以分布式电源接入节点与接入容量为变量,提出了计及需求响应的分布式电源选址定容模型。首先,建立了CCHP系统热电耦合运行模型。其次,综合考虑负荷削减量、中断持续时间与中断时间因子等因素,提出了可中断负荷的单位电量补偿定价的方法。通过在目标函数中分析需求响应成本,使规划目标更为全面,从而节约投资。另外,综合基于激励与基于价格的需求响应作用,考虑用户对于电价、燃气价格、可中断负荷单位电量补偿定价的响应,定义了改进的价格弹性系数,并利用此系数对负荷预测进行修正。最后,通过基于邻域再搜索的改进粒子群算法(neighborhood re-dispatch particle swarm optimization,NR-PSO)对规划模型进行求解,并通过对某13节点综合园区系统的仿真分析,验证了所提模型及方法的有效性。
[Abstract]:In the past, the research on the combined cooling heating and and CCHPs was mainly focused on its operation optimization, and less on the location and capacity determination of distributed generation DGs in the system. In this paper, we consider the demand response based on price and the demand response based on incentive in the system. In this paper, we take advantage of the multi-energy complementary characteristic of CCHP system to consider the demand response based on price and incentive. Taking distributed power access node and access capacity as variables, a distributed power supply location and capacity model considering demand response is proposed. Firstly, a thermoelectric coupled operation model of CCHP system is established. Secondly, load reduction is considered synthetically. By analyzing the demand response cost in the objective function, the planning goal is more comprehensive and the investment can be saved by the factors such as interruption duration and interruption time factor, etc. In addition, the method of unit electricity compensation pricing with interruptible load is put forward in this paper, and the cost of demand response is analyzed in the objective function. Based on incentive and price-based demand response, the improved price elasticity coefficient is defined by considering the user's response to electricity price, gas price, interruptible load unit electricity compensation pricing. Finally, the improved particle swarm optimization (PSO) algorithm based on neighborhood research is used to solve the planning model, and the simulation analysis of a 13-bus integrated park system is carried out. The validity of the proposed model and method is verified.
【作者单位】：华北电力大学电气与电子工程学院;
【分类号】：TM715

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