Dynamic Differential Evolution Algorithm and Its Application in Optimal Operation of Cascade Reservoirs
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Abstract:
The standard difference evolution algorithm is often used to analyze the optimal operation of cascade reservoirs, but with the increasing of melting length, the performance of algorithm solution decreases, the population diversity at late evolution decrease, and thus the algorithm may only determine the local optimal solution. In this study, the parameter of individual difference was defined to perform dynamic control on the scaling factor of difference evolution algorithm, and the parameter of evolution possibility was defined to perform dynamic control on the selection mechanism of the algorithm. Two standard testing functions and optimal operation of the cascade reservoirs were solved using the standard difference evolution algorithm, progressive optimization algorithm, and dynamic difference evolution algorithm. The simulation results indicated that the global searching ability of dynamic difference evolution algorithm increases significantly compared to that of standard difference evolution algorithm
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