基于改进萤火虫算法的梯级水库优化调度研究

梯级水电站水库群联合调度问题具有复杂的约束条件,受到发电、供水、防洪等目标的制约。作为多目标非线性优化调度问题,为了解决传统算法中存在结果受初值参数影响较大、容易陷入局部最优解、收敛速度不理想等问题,首次尝试将萤火虫算法引入梯级水库优化调度研究中。在传统萤火虫算法模仿自然界萤火虫捕食求偶行为的基础上,对其进行优化与改进,引入目标空间中解的Pareto支配关系比较萤火虫荧光亮度,比较其优化解,采用轮盘赌法确定萤火虫每次更新过程中的移动路径,利用精英保留策略建立多目标萤火虫模型。通过典型的梯级水电站进行仿真计算,研究结果表明,改进的多目标萤火虫算法在优化过程中具有较强的寻优能力,能更好地进行全局搜索和局部搜索,计算过程中具有良好的稳定性,并且计算效率较高,优于遗传算法(GA)、粒子群算法(PSO)和蚁群算法(ACO),为多阶段、多约束的梯级水电站水库群中长期优化调度问题提供了新的途径和新方法。

Improved firefly algorithm-based study on optimal operation of cascade reservoir

The joint-operation of cascade reservoir is restricted by the complicated constraint conditions of the targets such as power generation，water supply，flood control，etc. As the optimization made on the multi-target nonlinear operation，the firefly algorithm is firstly and tentatively introduced into the optimization of the operation of cascade reservoirs herein，so as to solve the defects in the conventional algorithm，i. e. ，the result is greatly impacted by the initial parameters and prone to fall into the local optimum，its convergence rate is undesirable，etc. On the basis of imitating the predatory and courtship behaviors of firefly in nature，the conventional firefly algorithm is optimized and improved，for which the Pareto dominance relations of the solutions in the target space are introduced to compare the fluorescent brightnesses of fireflies and their optimized solutions，and then the moving path during the each time of the renewal processes of firefly is determined with the roulette method，thus a multi-target firefly model is established with the elite preservation strategy. Through the simulative calculation made on typical cascade hydropower station，the study result shows that the improved multi-target firefly algorithm has stronger searching ability and can better carry out global search and local search with a better stability during the calculation，of which the calculation efficiency is higher and better than that of genetic algorithm ( GA) ，particle swarm optimization ( PSO) and ant colony optimization ( ACO) ，thus a new approach is provided for optimizing the mid-and-long-term multi-phase and multi-constraint operation of reservoir group for cascade hydropower station.