基于多智能体系统并考虑需求响应的电力系统节能减排调度  

Cost-emission dispatch based on multi-agent system considering demand response

作　　者：张晓花[1,2] 朱陈松 路睿 许云帆 郑剑锋 强浩[1] 周兴龙[1] ZHANG Xiaohua;ZHU Chensong;LU Rui;XU Yunfan;ZHENG Jianfeng;QIANG Hao;ZHOU Xinglong(School of Mechanical Engineering,Changzhou University,Changzhou 213164,China;Jiangsu Key Laboratory of Green Process Equipment,Changzhou 213164,China;Business College,Changzhou University,Changzhou 213164,China)

机构地区：[1]常州大学机械工程学院,江苏常州213164 [2]江苏省绿色过程装备重点实验室,江苏常州213164 [3]常州大学商学院,江苏常州213164

出　　处：《电力需求侧管理》2019年第5期35-40,共6页Power Demand Side Management

基　　金：国家自然科学基金项目（51207074）;江苏省社会科学基金项目（18GLB016）

摘　　要：针对能源与环境日益突出的问题,将直接负荷控制和紧急需求响应结合,考虑自弹性和交叉弹性的动态需求价格弹性,形成多时间弹性的综合负荷经济模型,建立考虑需求响应的节能减排调度模型。通过多智能体系统(multi?agent system,MAS)将问题分解为一系列相互作用的代理,各代理的静态调度采用拍卖算法求解,代理间通过具有自适应协同乘子的协同进化代理进行协同,并优化各时段的激励补偿值,比较了激励补偿值为固定值和优化值情况下对结果的影响。结果表明本文的算法可提高计算效率;考虑需求价格弹性的调度可实现负荷曲线的削减与转移,弹性越大,削减负荷的能力越强,系统节能减排效果越好;综合考虑系统的节能与减排,增加了系统调度的全面性。The energy and environment problems have be?come increasingly prominent,the direct load control and emergency response requirements are combined.Considering the self?elasticity and cross?elasticity price,the multiperiod dynamic elastic loads are modelled,the cost?emission demand response dispatch model is es?tablished.The system is decomposed into the optimization of interac?tive agents by multi?agent system and agents’are solved by auction algorithm,the adaptive co?evolution of agents is reached by coopera?tive co?evolution agent with the adaptive cooperative multipliers.And the optimal incentive compensation value at each time interval is obtained.The influence of the incentive compensation value on the optimization results is compared under the fixed value and the op?timal value.The results show that the combination of MAS and auc?tion algorithm can improve the computation efficiency.Considering the demand elasticity,the dispatch can achieve the reduction and transfer of the load curve.The maximum level of reducing load is ob?tained with the maximum values of elasticity by the optimization of incentive value.Comprehensive energy saving and emission reduc?tion into the system increase the comprehensive scheduling system.

关 键 词：需求价格弹性 激励补偿 多智能体系统 拍卖算法 协同乘子 

分 类 号：TM73[电气工程—电力系统及自动化] TK018[动力工程及工程热物理]