A Research On The Optimization Of Municipal Water Distribution Systems Based On Improve Particle Swarm Method

A perfect urban water supply system is an important infrastructure to ensure urban industrial production and residents’ daily lives.At present,since the urban water supply system mainly relies on manual experience for dispatching,the enterprise’s water supply management level is relatively backward,and the urban water supply system is imperfectly designed,causing unnecessary energy waste in the water supply process and increasing the water supply cost of the water supply enterprise.Under the condition of meeting the requirements of urban water supply,reduce the cost of water supply for enterprises as much as possible and realize the optimization of water supply are to maximize the economic value and social value.Therefore,the optimization of the urban water supply system will be the key research direction of the entire water supply industry.A correct and effective mathematical model of water supply system is the first condition to realize the optimal dispatch of urban water supply system.According to the actual water supply needs to establish proportional time macro-model,it takes the energy consumption cost of the enterprise in the water supply process as the optimization objective function,and it uses penalties in the optimization calculation,then to construct the new function-penalty function,which can effectively transform the constrained optimization problem into an unconstrained optimization problem,greatly simplifying the complexity of the problem.Particle swarm optimization(PSO)is an effective intelligent algorithm to deal with the most value optimization problem.The algorithm has the characteristics of simple initialization without setting too many parameters,simple concept and easy operation,so it is favored by the general scholar.Although the particle swarm optimization algorithm has been greatly developed since it was proposed by scholars,there are also some inherent shortcomings.They require further improvement and refinement of the optimization performance of the particle swarm optimization algorithm,and most of them are based on the standard particle swarm optimization algorithm for convergence time and jumping out of the local optimal aspects for related improvement work.In this paper,the particle swarm optimization algorithm is mainly improved in inertial weight adaptive dynamic nonlinear adjustment,linear increment of learning factor,introduction of penalty function,etc.,and the improved particle swarm optimization algorithm is applied to an actual water supply system optimization case in a southwest city.This paper studies the actual water supply optimal dispatch case in a city in southwest China,and uses the improved particle swarm optimization tool to calculate and process the objective function of water supply power consumption cost,so as to achieve the reasonable distribution of water quantity and pressure of two water plants to the city in six hours of the day,and analyzed the changes of water supply before and after the optimization of the city’s water plant,so as to achieve the purpose of saving the running cost of the water supply enterprise.This research method not only provides the corresponding basis for water supply enterprises to optimize their dispatch operations,but also provides a reference for the optimal dispatch of similar urban water supply systems.