摘要
针对需求侧资源的优化调度问题,建立了计及经济性和环保性的需求侧资源的数学模型,并且采用鹦鹉算法对所提出的数学模型进行求解。鹦鹉算法主要是在传统粒子群优化算法的基础上增加自适应权重和学习因子,以此来改变传统粒子群优化算法容易陷入局部最优、低精度两大缺点。使用惩罚函数法将有约束问题转化为无约束问题,同时考虑到需求侧资源与主网之间的协同运行情况,规划了4种有部分差别的需求侧资源运行策略。最后,通过相关的案例仿真,证明了所提模型和算法的有效性。
For the optimal dispatch problem of demand-side resources,a mathematical model of demand-side resources considering economic and environmental protection is established,and the parrot algorithm is used to solve the proposed mathematical model.In order to change the traditional particle swarm algorithm to fall into local optimum and low precision easily,we add the adaptive weight and learning factor to solve these two questions,and we called it parrot algorithm.The penalty function method is used to transform the constrained problem into an unconstrained problem.Considering the cooperative operation between the multi-energy power system and the main network,four different operation strategies of demand-side resources with partial differences are planned.Finally,the effectiveness of the proposed mathematical model and algorithm is proved by case simulation.
作者
潘廷哲
金鑫
罗鸿轩
徐迪
PAN Tingzhe;JIN Xin;LUO Hongxuan;XU Di(China Southern Power Grid Research Institute Co.LTD,Guangzhou 510640,China;Key Laboratory of Power Grid Intelligent Measurement and Advanced Metering Enterprises of Guangdong Province,Guangzhou 510640,China)
出处
《控制工程》
CSCD
北大核心
2023年第12期2245-2253,共9页
Control Engineering of China
基金
南方电网公司科技项目(ZBKJXM20232275)。
关键词
需求侧资源
优化调度
鹦鹉算法
学习因子
自适应权重
Demand-side resources
optimize dispatch
parrot algorithm
learning factor
adaptive weight
