基于量子蚁群优化算法的梯级水电系统经济调度

Economic dispatch of cascaded hydropower system based on quantum ant colony optimization algorithm

将量子计算理论引入到蚁群优化算法中,形成量子蚁群优化算法(QACOA),用于梯级水电系统经济调度研究中,以系统在调度期内实发电能和储蓄电能最大为准则构造优化目标函数。QACOA融入了量子计算理论的叠加态和概率表达特性,以量子态为基本信息单元,将量子比特的概率幅用于蚂蚁位置的编码,利用量子旋转门实现蚁群位置的更新,达到了比常规蚁群优化算法更好的优化效果。运用QACOA对梯级水电系统经济调度进行仿真,结果表明QACOA使调度期内实发电能和储蓄电能得到了明显提高。

The QACOA（Quantum Ant Colony Optimization Algorithm）,which combines the ant colony optimization algorithm and the quantum computing theory,is applied to the economic dispatch of cascaded hydropower system. Its optimization objective function is constructed to make the power generated and stored in the dispatch period maximum. QACOA adopts the superposition state and probability representation characteristics of quantum computing theory,takes the quantum states as the basic information cell,uses the probability amplitude of quantum bits to code each ant position and applies quantum rotation gate to update the position,which achieves better optimization effect than the normal ant colony optimization algorithm. Simulation is carried out for the economic dispatch of cascaded hydropower system and results show the real power generated and stored in the dispatch period is obviously increased.