多策略人工蜂群算法在梯级水电站优化调度中的应用

梯级水电站优化调度问题的准确、快速求解,是水利学科领域需解决的基本问题。针对该问题,提出了一种新的多策略人工蜂群算法。为更好地平衡算法的全局搜索与局部搜索能力,新算法在两个具有代表性的解搜索策略基础上,对其融合构成新的搜索策略,同时保留了原有的两个解搜索策略。新算法的三个候选解搜索策略,增强了对各类优化问题求解的适应性。为验证新算法的适应性及可行性,不仅在经典的基准测试函数中对其进行测试,并且将其应用于梯级水电站优化调度问题。实验结果表明,新算法具有适应性强、收敛速度快等优点。

Application of multi-strategy artificial bee colony algorithm on optimal operation of cascade hydropower stations

To accurately and quickly solve the optimal operation problem of cascade hydro-power stations is a challenge in the field of water conservancy.A new multi-strategy artificial bee colony algorithm was proposed in this study.In order to better balance the global search and local search capabilities of the algorithms,two representative solution search strategies were used in this new algorithm,and they were combined to form a new search strategy while retaining the original two solution search strategies.Therefore,the new algorithm contained three candidate solution search strategies in the process of searching new solutions,which was convenient to strengthen the adaptability to various optimization problems.The adaptability and feasibility of the new algorithm were tested in the classic benchmark function and applied to the optimal operation of cascade hydro-power stations.Experimental results showed that the new algorithm had the advantages of stronger adaptability and faster convergence speed.