Water supply control method and system

Abstract

The invention discloses a water supply control method and a water supply control system, wherein the method comprises the steps of: analyzing historical data to establish a water supply predication model and a function between the parameters of an input layer and the water supply amount output at an output layer; establishing a target function, wherein D(X) = is time interval, T is time, M(T) is a time-varying function of the price of power consumption per unit cost, D(X) is total power consumption and X[T] is solution; and calculating an optimized scheme for X[T] by means of genetic algorithm under restricted conditions; according to the water supply control method and the water supply control system, historical data is analyzed to establish the water supply predication model and the water supply function, the target function is established to perform combined optimization on water supply scheduling, optimization for the solution is achieved by means of genetic algorithm under restricted conditions, relatively high efficiency is obtained in optimization by simulating the principle of biologic evolution and the problem of complex combined optimization can be settled, and the stability and practicability of optimization method are verified by introducing the restricted conditions for research on water supply model, so as to realize stable supply during the water supply procedure of waterworks and the most economical energy-saving optimization control.

Description

technical field [0001] The invention relates to an industrial control system and method, in particular to a water supply control method and system. Background technique [0002] In tap water treatment, due to the complexity of the urban pipe network and the uncertainty of changing water conditions in the water supply link, the range of water supply load varies greatly, making the operation of water supply equipment unstable and energy-consuming. At present, domestic research on water supply load forecasting mainly focuses on traditional forecasting principles and methods, such as exponential smoothing, time series analysis and regression analysis. Traditional forecasting methods require an explicit forecasting model of water supply load composed of certain influencing factors. Since the urban water supply system is a complex large system with coexistence of uncertainty, nonlinearity and time-varying nature, establishing an explicit forecasting model of water supply load not...

AI Technical Summary

Problems solved by technology

Since the urban water supply system is a complex large system with coexistence of uncertainty, nonlinearity and time-varying nature, establishing an explicit forecasting model of water supply load not only requires a large amount of historical data of water supply load, but also requires a large amount of relevant data, including temperature, humidity and population, etc., the search and recording of these data is particularly cumbersome, and it is difficult to ensure the integrity of the obtained data. Therefore, it is not easy to obtain an accurate explicit prediction model by using traditional prediction methods. The accuracy of the prediction model is difficult to guarantee, and it lacks adaptability. sex and flexibility

In addition, the accuracy of traditional forecasting methods based on stochastic processes and mathematical statistics principles is not ideal, and the forecasting accuracy is not high.

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