计及柔性资源的含风电场电力系统多目标动态协调调度  

Multi-objective Dynamic Coordination Dispatching for Power Systems with Wind Farms Considering Flexible Resources

作　　者：张亚超[1] 刘开培[1] 秦亮[1] 方仍存[2] 

机构地区：[1]武汉大学电气工程学院,武汉430072 [2]国网湖北省电力公司经济技术研究院,武汉430077

出　　处：《高电压技术》2017年第4期1186-1193,共8页High Voltage Engineering

基　　金：国家自然科学基金(51309258);国家重点基础研究发展计划(973计划)(2012CB215101)~~

摘　　要：针对风电出力的间歇性和不确定性,提出考虑能量存储系统和需求侧管理的含风电场电力系统的动态经济环境协调调度模型。结合风电出力概率模型,将含随机变量的机会约束转化为确定性约束条件。在此基础上,建立含风电场及柔性资源的多目标调度模型,并提出一种基于拥挤熵的改进多目标粒子群优化(IMOPSO-CE)算法对该模型进行求解。最后以含6台火电机组和1个风电场的电力系统为算例,对不同调度情景下的仿真结果进行比较分析,验证了所提模型的合理性及IMOPSO-CE算法的有效性,为解决含风电场电力系统动态经济环境调度问题提供了一种新思路。In allusion to the intermittency and uncertainty of wind power output, we propose a dynamic, economic, and environmental coordination dispatching model for power systems with wind farms after taking the energy storage system and demand side management into consideration. Incorporated with the probabilistic model of wind power output, the chance constraint including the random variable is converted to the deterministic constraint. Thereby, the multi-objective dispatch model with wind farms and flexible resources is established. Moreover, an improved multi-objective particle swarm optimization algorithm based on crowding entropy（IMOPSO-CE） is put forward to solve the above model. Finally, taking a system composed of six thermal power units and one wind farm as an example, we compare and analyze the simulation results under different scheduling scenarios. It is demonstrated that the model proposed is reasonable and the IMOPSO-CE algorithm is effective, which can provide a new idea for solving dynamic economic environmental dispatch problem for power systems integrated with wind farms.

关 键 词：风电 能量存储系统 需求侧管理 多目标优化 动态经济环境调度 

分 类 号：TM73[电气工程—电力系统及自动化]