| 基于CPSO算法实现电力综合能源协同优化的规划与研究 |
投稿时间：2019-09-16 修订日期：2019-09-20  点此下载全文 |
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| 中文摘要:针对电力综合能源系统中能源配置不合理的情况,将粒子群优化算法(CPSO算法)引用到电力综合能源协同优化方案中。通过以CPSO算法为基础,实现综合能源电能、热能、天然气能协同优化,通过采用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,然后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,进而最后得出经过比较后的最优值。试验表明,基于以CPSO算法的能源配置具有较好的稳定性,为后期配置的进一步研究提供有意义的技术参考。 |
| 中文关键词:电力综合能源系统 粒子群优化算法 CPSO算法 最优值 能源配置 |
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| Planning and Research of Collaborative Optimization of Power Integrated Energy Based on CPSO Algorithm |
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| Abstract:Aiming at the unreasonable energy allocation in the power integrated energy system, the particle swarm optimization algorithm (CPSO algorithm) is referenced to the power integrated energy collaborative optimization scheme. The integrated energy, thermal energy and natural gas can be synergistically optimized based on the CPSO algorithm. By adopting the CPOS algorithm, users can divide the information particle groups of different energy forms into different sub-populations, and then each sub-population. The particles in each seek their own optimal values, realize the sharing of various group particle information, and jointly calculate, evolve, and match until the optimal evolution algebra is realized, and finally the compared optimal values are 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. |
| keywords:Power integrated energy system particle swarm optimization algorithm CPSO algorithm optimal value energy allocation |
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