Hybrid Quantum Particle Swarm Optimization Algorithm For Power Generation-Ecological Cooperative Optimization Of Cascaded Reservoirs

Optimal scheduling of cascade reservoirs is an effective means to improve water use efficiency and hydropower system dispatching efficiency,and it is of great significance and practical value for alleviating China's energy shortage and promoting China's economic development.With the completion and commissioning of large-scale hydropower bases,the cascade systems are becoming increasingly large,and the upstream and downstream water and power links are becoming more and more complex,which greatly increases the difficulty of modeling and solving."How to further develop effective hydropower dispatching theory and methods to achieve efficient allocation of water resources" has become a hot and difficult issue in the current research of hydropower dispatching.Thus,this paper studies the solution to the optimal scheduling problem of cascade reservoir,and the main contents are as follows:(1)A hybrid quantum particle swarm optimization algorithm(HQPSO)with coupled two-fold improvement strategy is proposed.By innovatively increasing individual extremum variation,external archive set and simplex search operator in the optimization process of standard quantum partical swarm optimization algorithm,the proposed algorithm improves the guiding ability of elite individuals and enriches the diversity of the population.(2)For the problem of power generation optimal scheduling of cascade reservoirs,an optimal scheduling model with the largest total power generation of cascade reservoirs is constructed and solved by the hybrid quantum particle swarm optimization algorithm.Taking the five hydropower stations in the Wujiang River as an example,different typical years are selected to verify the application effect of the algorithm.The comparison with different algorithms shows that the inproved algorithm has strong global search ability in the evolution process and can find better solutions.(3)For the problem of ecological optimal dispatching of cascade reservoirs,firstly,the common methods for determining ecological flow are summarized.Taking the cascade reservoirs in Wujiang River as an example,different hydrological methods are used to caculate three different ecological flow design schemes.Secondly,an ecological scheduling model with the smallest total water shortage of cascade reservoirs is constructed.Finally,under the different ecological flow design schemes,the hybrid quantum particle swarm optimization algorithm is used to solve the model and obtain scientific and reasonable scheduling results.At the same time,the effectiveness of the algorithm is further verified,which provides a new way to solve the ecological optimal scheduling of cascade reservoirs.(4)For the problem of power generation-ecological multi-objective optimization scheduling for cascade reservoirs,firstly,a power generation-ecological multi-objective scheduling optimization model for cascade reservoirs is constructed.The weight distribution vector set is set by binomial distribution weighting method,and multi-objective fuzzy optimization is adopted,which transforms the multi-objective problem into a single-objective problem.Then,it is solved by the hybrid quantum particle swarm optimization algorithm.Through multiple solving,several non-inferior solutions with different weights can be obtained.Finally,the power generation target and ecological target are analyzed.The synergy relationship between the two groups is that the decision of the cascade hydropower stations to properly consider the ecological demand target can greatly improve the ecological water shortage without seriously affecting the power generation efficiency,thus providing certain support for the cascade reservoirs dispatching.