Research On Optimal Scheduling Of Large-Scale Pumping Stations Based On Genetic And Particle Swarm Fusion Algorithm

Pump station is an important part of South-to-North Water Diversion Project and also a main energy dissipation unit.When pump station works,it is necessary to adjust the switch and blade angle of pump unit according to water flow rate,lift and other factors in order to achieve the optimum working condition and the highest efficiency of the device.These will directly affect the cost and economic benefit of the whole project.However,the current situation of pump stations in China is often too low-efficiency,and there is serious waste of resources,which to some extent promotes the optimization and modification of pump stations.The construction of mathematical model for optimal dispatching of pump station is more complicated.It is very important to select a suitable algorithm to solve the model.In the past optimization schemes,genetic algorithm is often used to solve the problem.This algorithm has the disadvantage of low computational efficiency while conducting a large space search,so particle swarm optimization fusion algorithm is introduced into genetic algorithm in this paper.Combining the advantages of the latter with high computational efficiency and a single evolutionary model,the overall performance of the genetic particle swarm optimization fusion algorithm is improved.Based on the theory of optimal scheduling and using various test functions to evaluate the performance of the fusion algorithm,it is verified that the genetic particle swarm optimization fusion algorithm is superior to the genetic algorithm and particle swarm optimization fusion algorithm.In this paper,the optimal scheduling scheme of pump station is analyzed and discussed deeply.According to the test performance data of pump station unit,polynomial fitting is adopted by least square method,and MATLAB software is used to draw the performance curve.On this basis,the optimum adjustment of blade angle is discussed under the condition of different lift of pump device.This paper takes the Gaogang Pump Station as an example,according to the characteristics of two groups of units with different regulating performance at the Gaogang pump station,introduces the theory of large system,aiming at the highest efficiency of pump station,and considering many constraints.A mathematical model of two-layer decomposition and coordination of optimal dispatching problem of pumping station is established.According to this model,the traditional genetic algorithm and genetic particle swarm optimization fusion algorithm are used to optimize calculation by MATLAB software,and the results were compared and analyzed.The experimental results show that the genetic particle swarm optimization fusion algorithm is better than the genetic algorithm to optimize the unit flow and switch assignment,the average installation efficiency is higher,and the calculation speed is faster.The applicability and effectiveness of genetic particle swarm optimization fusion algorithm for optimal dispatching of pump stations are verified.This paper analyzes the influence of the Yangtze River tidal level on the lift of Gaogang pump station.For the problem of large and frequent changes in the lift,the factors such as the lift and the electricity price changes in different periods are taken into account.An optimal Model for daily operation of pump station with minimum cost of electricity consumption is established.Considering the variation of lift and electricity price changes in different periods,the genetic particle swarm optimization fusion algorithm is used to solve the problem under different pumping flow requirements.The optimal operation strategy of the pump station is obtained quickly and accurately.The open combination and the blade angleof the fully regulated unit of the pump station is determined,and the lowest power cost of the daily operation is calculated.