Hybrid Intelligent Algorithm In Cascade Reservoirs In The Long Term Optimal Scheduling

Reservoir operation is one of the core content of management, in particular, the optimal operation of reservoirs has been a research focus after a variety of intelligent algorithms introduced in the field of scheduling optimization model. Intelligent algorithm break down the traditional model of setting up a precise calculation mode.This intelligent method helps to solve the problem which can hardly be settled by traditional methods.The smart method to solve the optimal operation of reservoir is a new way of thinking. In this paper,on the basis of a case study Xiaowan and Manwan two hydroelectric station in the Lancangjiang River Basin, modeling and solving the model in different ways including genetic algorithm, ant colony algorithm, and those methods based hybrid intelligent method.This paper in-depth discusses various models, methods, analysis of their advantages and disadvantages and intelligent algorithms analyze combined with an example was analyzed emphatically, based on a large number of documents and papers about reservoir operation. Genetic algorithm, ant colony algorithms, simulated annealing algorithm interact other come up with a hybrid intelligent algorithm. This hybrid algorithm is applied for solving the reservoir operation optimization model, and developing programs on the Visual C++ platform including the genetic algorithm process, the genetic simulated annealing procedures, ant colony optimization procedures, climbing algorithm using improved ant colony algorithm procedures, improved ant colony algorithm program. Finally, the data of Xiaowan and Manwan Hydropower station was entered into process to calculate,analyze and compare. The results of the calculation reveal the accuracy and efficiency of hybrid algorithm for step reservoir operation can be gained preferable effect.The innovations in the dissertation as bellow: Simulated annealing fitness function of genetic algorithm for Cascade Reservoir was proposed, that is, optimization of reservoir operation in the cascade function based on the objective function, combined with making amendments to the constant and simulated annealing penalty function as the fitness function; This paper Reservoir issue will introduce the concept of ant colony algorithm fitness to update strategy of pheromone ant colony algorithm; Application of large mutation mechanism and simulated annealing principles, and to join the corresponding ranking selection mechanism, the formation of large variations for the reservoir operation simulation genetic algorithm; Change from one system consist of genetic algorithm, ant colony algorithm, hill-climbing algorithm, simulated annealing methods to another hybrid artificial intelligence method for reservoir operation.