王安华, 张浩. 基于改进鼠群算法的微电网优化调度[J]. 黑龙江电力, 2024, 46(3): 225-231,236. DOI: 10.13625/j.cnki.hljep.2024.03.007
引用本文: 王安华, 张浩. 基于改进鼠群算法的微电网优化调度[J]. 黑龙江电力, 2024, 46(3): 225-231,236. DOI: 10.13625/j.cnki.hljep.2024.03.007
WANG An-hua, ZHANG Hao. Optimal scheduling of microgrids based on improved rat swarm algorithm[J]. Heilongjiang Electric Power, 2024, 46(3): 225-231,236. DOI: 10.13625/j.cnki.hljep.2024.03.007
Citation: WANG An-hua, ZHANG Hao. Optimal scheduling of microgrids based on improved rat swarm algorithm[J]. Heilongjiang Electric Power, 2024, 46(3): 225-231,236. DOI: 10.13625/j.cnki.hljep.2024.03.007

基于改进鼠群算法的微电网优化调度

Optimal scheduling of microgrids based on improved rat swarm algorithm

  • 摘要: 为避免传统鼠群优化算法(RSO)在寻优时收敛速度慢,陷入局部最优,提出融合Circle混沌映射和纵横交叉策略的鼠群优化算法(HRSO)。利用Circle混沌映射和纵横交叉策略,加快全局收敛速度同时提高算法跳出局部最优的能力,选取Sphere、Rosenbrock等若干经典测试函数进行仿真测试,将HRSO应用于以总发电成本最低为目标且考虑安全性和稳定性的微电网优化调度模型中。结果表明:在4种测试函数下,HRSO与RSO相比,稳定性提高了12.45%,收敛速度提高了28.17%;在微电网优化调度模型中,微电网的总发电成本降低约8.43%。

     

    Abstract: In order to avoid the traditional rat swarm optimization(RSO) algorithm from converging slowly and falling into local optimum, we propose a rat swarm optimization algorithm(HRSO) that integrating Circle chaos mapping and vertical and horizontal crossover strategies. The HRSO is applied to a microgrid optimal dispatching model with the objective of minimizing the total generation cost as considering security and stability. The results show that HRSO improves the stability by 12.45% and the convergence speed by 28.17% compared with RSO under four test functions, at the same time the total generation cost of microgrid is reduced by about 8.43%, in the microgrid optimal dispatch model.

     

/

返回文章
返回