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作 者:彭祖剑 PENG Zujian(Ucap Cloud Information Technology Co.,Ltd.,Dongguan 523000,China)
机构地区:[1]开普云信息科技股份有限公司,广东东莞523000
出 处:《自动化与信息工程》2024年第6期41-46,共6页Automation & Information Engineering
摘 要:为提高虚拟电厂的经济性和稳定性,提出一种考虑中断负荷的虚拟电厂经济调度模型。首先,以中断负荷成本最小为目标函数,构建虚拟电厂经济调度模型;然后,利用扩展记忆系数改进的粒子群优化(IPSO)算法求解虚拟电厂经济调度模型;最后,将IPSO算法与PSO算法、遗传算法(GA)进行仿真对比分析。仿真结果表明:IPSO算法相较于PSO算法、GA,其最小中断负荷成本分别降低了0.77万元、1.81万元,迭代次数分别减少了65、84次;经过IPSO算法的优化调度,有效降低了虚拟电厂高峰时段的用电负荷,提升了虚拟电厂运行的经济性和稳定性。To improve the economy and stability of virtual power plants,a virtual power plant economic dispatch model considering interrupted load is proposed.Firstly,a virtual power plant economic dispatch model is constructed with the objective function of minimizing the interruption load cost;Then,the extended memory coefficient improved particle swarm optimization(IPSO)algorithm is used to solve the economic dispatch model of the virtual power plant;Finally,the IPSO algorithm will be compared and analyzed with PSO algorithm and genetic algorithm(GA)through simulation.The simulation results show that compared to the PSO algorithm,the IPSO algorithm GA,The minimum interruption load cost has been reduced by 7700 yuan and 18100 yuan respectively,and the number of iterations has been reduced by 65 and 84 times respectively;Through the optimization scheduling of IPSO algorithm,the electricity load during peak hours of virtual power plants has been effectively reduced,and the economy and stability of virtual power plant operation have been improved.
关 键 词:虚拟电厂 经济调度模型 中断负荷 改进的粒子群优化算法
分 类 号:TP311.5[自动化与计算机技术—计算机软件与理论]
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