针对传统优化算法在求解高维、复杂的梯级水库短期发电优化调度时多约束条件难以处理、计算机时长、易陷入局部最优解等缺陷,提出了基于协进化的粒子群优化算法,并建立了相应罚因子的评价机制,在此基础上对协进化粒子群优化算法进行了改进.通过实际算例验证了该方法的合理性和可靠性.从而为高维、复杂梯级水库发电优化调度提供了一种新的求解途径. Aiming at the shortcomings of the traditional optimization algorithms in solving high-dimensional and complex cascade reservoir short-term generation optimal scheduling problems such as multi-constraints difficult to handle, computer time, easy to fall into the local optimal solution, the co-evolutionary particle swarm optimization algorithm is proposed and established The corresponding evaluation mechanism of penalty factor, and on this basis, the co-evolutionary particle swarm optimization algorithm is improved.An example is given to verify the rationality and reliability of the proposed method.Thus, it provides the optimal scheduling for high dimensional and complex cascade reservoirs A New Way to Solve.