基于改进蜜獾算法的风光氢储微电网容量优化配置方法

Capacity Optimization Allocation Method of Wind/Solar/Hydrogen/Storage Microgrid Based on Improved Honey Badger Algorithm

  • 摘要: 针对风光氢储并网型微电网的容量优化配置问题,构建以经济性、能源利用率、供电可靠性为目标函数的容量优化模型。针对传统求解算法求解速度慢、精度低等问题,提出一种改进的蜜獾算法。该算法在初始化种群阶段采用Bernoulli混沌映射的方式使种群具有遍历均匀性,在挖掘阶段和寻蜜阶段引入分段非线性递减参数,寻找最优个体附近有较好个体的情况,采用横向交叉策略产生新的解从而增强算法的搜索能力,并利用4种测试函数将改进的蜜獾算法、蜜獾算法、粒子群算法和蝴蝶算法进行对比。算例结果证明,改进后的算法比改进前的算法成本降低了7.44%,能源浪费率降低了21.79%,冗余度降低了3.89%。

     

    Abstract: Aiming at the problem of capacity optimization configuration of wind/solar/hydrogen/storage grid-connected microgrid, a capacity optimization model with economy, energy utilization and power supply reliability as objective functions is constructed. Aiming at the problems of slow speed and low precision of traditional algorithm, an improved honey badger algorithm is proposed. In the initial population stage, the Bernoulli chaotic map is used to make the population have ergodic uniformity. In the mining stage and the honey-seeking stage, the piecewise nonlinear decreasing parameter is introduced to find the case where there are better individuals near the optimal individual. The horizontal crossover strategy is used to generate new solutions to enhance the search ability of the algorithm. Four test functions are used to compare the improved honey badger algorithm, honey badger algorithm, particle swarm optimization algorithm and butterfly optimization algorithm. The results of the example show that the improved algorithm reduces the cost by 7.44%, the energy waste rate by 21.79%, and the redundancy by 3.89%.

     

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