基于改进二进制蝙蝠算法的独立型微网容量优化配置

该文围绕独立型风/光/柴/储微网的容量优化配置展开研究,以微网系统供电可靠性为约束条件,同时考虑微网经济性、环保性和可再生能源利用率3个指标,以加权后的年均综合费用最小为优化目标,构建微网容量优化配置的非线性整数规划模型。针对连续优化算法直接用于求解离散优化模型而导致的局部最优问题,该文提出一种改进的二进制蝙蝠算法(improved binary bat algorithm,IBBA),将差分进化(differential evolution,DE)算法的变异、交叉、选择操作与二进制蝙蝠算法(binary bat algorithm,BBA)相结合,增强BBA的全局寻优能力。算例结果表明,IBBA求解得到的配置结果在精度和稳定性上均优于遗传算法(genetic algorithm,GA)、粒子群算法(particle swarm optimization,PSO)和DE算法。

Optimal Sizing for Stand-Alone Microgrid Based on Improved Binary Bat Algorithm

This paper focuses on the optimal sizing for stand-alone wind-PV-diesel-battery microgrid. Using the reliability of power supply as the constraint condition and the minimum average annual cost after weighting as the objective function, this paper constructs a non-linear integer programming model for the optimal sizing of microgrid which takes economy, environmental protection and renewable energy utilization of microgrid into consideration. Aiming at the local optimal problem caused by directly applying continuous optimization algorithm into solving discrete optimization model, this paper proposes an improved binary bat algorithm ( IBBA) , which adopts mutation, crossover and selection operations from differential evolution ( DE) to improve the global searching ability of standard BBA. The results of a case study indicate that IBBA shows better performance in terms of both the solution quality and stability compared with genetic algorithm ( GA) , particle swarm optimization ( PSO) and DE algorithm.