Design And Algorithmic Optimization Of Energy-Saving System For Water Conservancy Pumping Station

With the acceleration of urbanization,urban management requirements for water system management are also increasing.Among them,the pump station project needs to consume a lot of resources and time,and most pump stations in China have the disadvantages of low operating efficiency and waste of resources.Therefore,research on energy-saving and economic operation of pumping stations is important and necessary.Pumping station research mostly focuses on pumping units.Most of the pumping stations in China are axial flow pumps with adjustable blades.These pumps can control the blade angle of the pump when given the head and target pumping flow.Based on Changshu Water Conservancy Project,this paper designs a set of energy-saving information system for water pumping station.When the administrator gives the head and flow,the system can give the pumping station energy-saving and economic operation start-up scheme,so that the energy consumption of the pump station can be reduced and the efficiency can be maximized.The specific research work of this paper is as follows:1.The existing economical operation guidelines of pumping stations are analyzed,and the mathematical model of energy saving optimization of pumping stations is established.Introduce the concept of domain ontology,correlate the hierarchical relationship of the basic elements of pump station operation,and construct the domain ontology of economic operation of pumping station Based on the Jena platform call to build the pump station body and customize the energy-saving rule base to infer the boot combination,so that in the case of the known head and target flow,the platform can infer the optimal start-up that meets the conditions and the economic operation of the pump station.combination.2.This thesis introduces the basic principle of simulated annealing algorithm and combines it with traditional particle swarm optimization algorithm.The improved simulated annealing particle swarm optimization algorithm can make up for the shortcomings of traditional particle swarm optimization algorithm.Based on the actual working condition data of Changshu Water Conservancy Project,the performance curve of the pump is fitted with cftool tool,and the head flow rate and flow efficiency equation are obtained at various angles.Then the improved particle swarm optimization algorithm is used to optimize the start-up angle of the reasoned start-up combination,and the optimal start-up scheme for energy-saving operation of pumps is obtained.The advantages and disadvantages of the standard particle swarm optimization algorithm are analyzed,and compared with the optimization algorithm,which shows the energy saving advantages of the optimization algorithm.3.This thesis discusses the basic structure and principle of BP neural network,and then establishes the neural network model of pumping station.The model is used to train the optimized start-up scheme.The aim is that under the similar lift flow conditions,the neural network can quickly predict the unit power of the optimized scheme and realize the real-time optimization of the pump station.4.A set of energy-saving system for water pumping station is designed,and the test is carried out under given head and target flow.The most economical and energy-saving start-up scheme is solved by this system.We can log in to the query optimization result through the front-end interface,and you can perform historical boot plan query and log writing.