CAJ | 학술논문

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.
침대전통우화산법재구해고유、복잡적제급수고단기발전우화조도시다약속조건난이처리、계산궤시장、역함입국부최우해등결함,제출료기우협진화적입자군우화산법,병건립료상응벌인자적평개궤제,재차기출상대협진화입자군우화산법진행료개진.통과실제산례험증료해방법적합이성화가고성.종이위고유、복잡제급수고발전우화조도제공료일충신적구해도경.
For high-dimensional and complex cascade reserviors,the traditional optimization algorithms are difficult to deal with multi-constraint condition,a long computing time,falling into local optimal solution easily and other defects.Combined with the optimal operation characteristics of short time cascade reserviors,co-evolutionary particle swarm optimization algorithm is proposed.At the meantime, a penalty factor of the evaluation mechanism is established and the algorithm is improved.The practical example shows that this method is reasonable and reliable,so as to provide a new way to solve optimal operation of high-dimensional and complex cascade reservoirs based.