Improved Artificial Bee Colony Algorithm And Its Application In Optimal Operation Of Cascade Reservoirs

The optimal operation of cascade reservoirs is a complex nonlinear problem with multi-reservoirs and multi-periods.Intelligent optimization algorithms have significant advantages in solving these multidimensional problems.As one of these algorithms,artificial bee colony(ABC)algorithm can be utilized to solve the optimal scheduling problem of cascade reservoirs regarding its fewer parameters and strong robustness.However,there are still some insufficiencies in ABC algorithm.In order to improve the performance of ABC algorithm,the following improvements have been made.Firstly,we incorporate the information of current global best solution and its gradient into the local search equation,which is good at exploration but poor at exploitation,to balance exploration and exploitation.Secondly,considering that the global detection strategy of ABC algorithm is relatively simple,we apply operators(crossover,mutation,and selection)to producing new candidate position at scout bees phase according to GA algorithm.Thirdly,selection strategy adopted by ABC is proportional selection.Selection probability is directly proportionate to the fitness of each solution.Trying to ensure the diversity of the population,we apply rank selection strategy in order that selection probability depends only on ranking value of the individual and not on the actual objective value.Based on the above three improvements,this paper presents a new artificial bee colony algorithm to solve the problem of slow convergence and low precision of ABC algorithm.Simulation results of several test functions show that the new algorithm,compared with other intelligent algorithms,is the best performance in the case.Then we try to use the new algorithm to solve short-term hydro-thermal scheduling(STHTS)problem and the model of long-term optimal scheduling for the energy maximization of cascade reservoirs.The improved ABC algorithm is used to test the classical four-reservoirs model in STHTS problem and the example of the cascade reservoir in the Yuan River basin.The results have been compared with the calculation results of other intelligent algorithms on two aspects of solving accuracy and velocity,which shows the applicability and superiority of the improved algorithm solving the optimal scheduling problem of cascade reservoir.