摘要
针对电力综合能源系统中能源配置不合理的情况,将混沌粒子群优化(CPSO)算法引用到电力综合能源协同优化方案中,实现综合能源电能、热能、天然气能协同优化。采用CPOS算法,用户能够将各种不同能源形式的信息粒子群划分为形式各异的子种群,将每个子种群中的粒子彼此各自寻求自己的最优值,实现各种群粒子信息的共享;通过共同计算、进化、匹配,直到实现最佳的进化代数,最后得出经过比较后的最优值。试验表明,基于CPSO算法的能源配置具有较好的稳定性,可以为后期配置的进一步研究提供有意义的技术参考。
Aiming at the unreasonable energy allocation in the integrated energy system,the chaotic particle swarm optimization(CPSO) algorithm is referenced to the power integrated energy synergy optimization scheme to realize the synergistic optimization of integrated energy,heat and natural gas. Using the CPOS algorithm,users can divide the information particle groups of different energy forms into sub-populations of different forms,and the particles in each sub-population each seek their own optimal value to realize the sharing of various group particle information. By calculating,evolving,and matching together,until the best evolutionary algebra is achieved,the compared optimal values are finally obtained. Experiments show that the energy configuration based on CPSO algorithm has better stability and provides a meaningful technical reference for further research of post-configuration.
作者
陆沈雄
LU Sheng-xiong(School of Management,Zhejiang University,Hangzhou 310058,China)
出处
《自动化与仪表》
2020年第1期91-94,99,共5页
Automation & Instrumentation
关键词
电力综合能源系统
混沌粒子群优化算法
最优值
能源配置
power integrated energy system
chaotic particle swarm optimization(CPSO) algorithm
optimal value
energy allocation
作者简介
陆沈雄(1982—),男,硕士,工程师,研究方向为综合能源服务,主要从事电力行业信息化软件工作。
