基于改进蚂蚁算法的梯级水电站短期优化调度

Short-Term Optimal Dispatch of Cascaded Hydropower Stations Based on Improved Ant Algorithm

将改进型蚂蚁算法用于梯级水电站短期优化调度问题,并通过引入遗传算法的交叉和变异思想以及自适应搜索半径方法提高了蚂蚁算法的搜索能力．以最小耗水率模型为例,给出了梯级水电站短期优化调度问题改进型蚂蚁算法的数学描述和求解的算法步骤,并通过龙羊峡-李家峡梯级水电站实例验证了改进型蚂蚁算法的优越性．结果表明,与遗传算法相比,改进型蚂蚁算法获得了更优的调度方案．优化结果在取得更低耗水率的同时,减少了机组的启停次数,并且使所有机组连续高效运行,从而降低了机组的维护费用,并增加了梯级的经济效益．

An improved ant algorithm（IAA） is applied to the short-term optimal dispatch of cascaded hydropower stations. By using crossover and mutation of genetic algorithm and technique of adaptive search radius, the search ability of the ant algorithm is raised. The mathematical description and the procedure of the IAA are given with the minimum water consumption model as an example. Finally the superiority of the IAA is demonstrated by the application of Longyangxia-Lijiaxia cascaded hydropower stations. The optimal results of the IAA have lower water rate and fewer unit commitment times compared with those of the genetic algorithm. And it also ensures that all the units operate consecutively and effectively. Accordingly maintenance cost of the units reduces, and economic benefit of the cascaded hydropower stations increases.