Centralized heating secondary side regulation and control method based on artificial intelligence and optimization algorithm

Abstract

The invention discloses a centralized heating secondary side regulation and control method based on artificial intelligence and an optimization algorithm. The method comprises the specific steps of collecting historical data and carrying out data preprocessing; according to the preprocessed historical data, establishing a deep regression model for training; and acquiring real-time data, inputting the real-time data and decision variables into the model together, and carrying out decision solving through the optimization algorithm. According to the method, the deep regression and the optimization algorithm serve as a technical framework, the heat loads of a heat exchange station and all units are predicted, the secondary side water supply temperature, the circulating pump frequency and the valve opening degree of each unit serve as the decision variables, and an optimal regulation and control strategy is optimized and solved. According to the method, various environmental factors are considered, and parameter evaluation of industry experts is not needed. The optimal regulation and control strategy composed of all decision variables can be output at the same time, and accuracy, stability and energy-saving potential are considered.

Description

technical field [0001] The invention relates to the technical field of central heating secondary side control, in particular to a central heating secondary side control method based on artificial intelligence and an optimization algorithm. Background technique [0002] Central heating is one of the infrastructures of modern cities and an important facility of urban public utilities. Vigorously developing central heating can not only provide cities with stable and reliable high-grade heat sources and improve people's lives, but also save energy, reduce urban pollution, beautify the city, and effectively utilize the effective space of the city. [0003] With the continuous advancement of industrial automation in recent years, my country's heating and heating industry has gradually transitioned from the manual control mode based on traditional experience to the self-control mode based on a complete set of automated facilities and equipment. With the promotion of standardized h...

AI Technical Summary

Problems solved by technology

[0004] The disadvantage of the existing technology is that the use of the step-by-step approach decision-making model based on logical judgment has two limitations. The control cycle is long, resulting in long-term fluctuations and instability; the lack of coordination from a global perspective results in discrepancies between the control units. conflict

The climate model based on theoretical derivation does not consider the influence of environmental factors, lacks flexibility in regulation, and relies too much on expert parameter evaluation, which is not conducive to the rapid deployment and practicality of the model

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