Improved genetic algorithm-based method for distributing and optimizing thermal and electrical load of steam extraction and heating unit

Abstract

The invention provides an improved genetic algorithm-based method for distributing and optimizing thermal and electrical load of a steam extraction and heating unit, and belongs to the technical field of energy saving and monitoring of a power station. The invention aims to distribute and optimize the thermal and electrical load of a plurality of heating units of the power station, optimally distribute the electrical load and the thermal load of the power station when the electrical load and the thermal load meet requirements of users, and reduce total energy consumption and save energy. An actual heat consumption and consumption difference curve of the unit is set, and a design heat consumption curve of the unit is obtained; the electrical load and steam extraction amount of each unit are acquired; and the electrical load and the steam extraction amount value of each unit are obtained based on the improved genetic algorithm when the total thermal consumption values of the units are minimum, and the electrical load, the steam extraction amount value optimal solution and the corresponding minimum total thermal consumption of each unit are output when the total thermal consumption values of the units are minimum by improving genetic coding and fitness function, and selecting, crossing and mutating the genetic algorithm under the condition that the optimization process meets constraint conditions. By the method, the speed of optimization process and accuracy of an optimization result are improved.

Description

technical field [0001] The invention relates to a method for optimizing thermoelectric load distribution of multiple heating units in a power plant, and belongs to the technical field of energy-saving monitoring of power plants. Background technique [0002] With the development of the economy and the improvement of the quality of life of the people, the urban central heating system has been developed rapidly, and the energy conversion efficiency of cogeneration has obvious advantages. Therefore, the heating and extraction unit has been vigorously developed. [0003] The steam extraction heating unit provides users with electricity and heating heat. The amount of heat and electricity provided by the power plant is controlled by the needs of heat users and electricity users. Therefore, the power plant must adjust the heat supply and extraction according to the needs of heat users and electricity users. The heat and electricity load of the steam unit. [0004] For a certain t...

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Problems solved by technology

The mathematical model assigned by the "point-by-point method" in this document has poor stability, slow calculation speed, and cannot be continuously optimized

At the same time, the equivalent heat drop method is more complicated to apply to the heating and extraction unit.

[0008] In the literature [2] (Ran Peng, Zhang Shufang, "Steam Turbine Technology", Volume 48, No. 1, 2006: "Optimization Calculation Method for Thermal Power Plant Load Based on Genetic Algorithm"), the method of using genetic algorithm to establish thermal power plant load optimization model solves the problem of When the scale of the problem is enlarged and there are many variables and constraints, it is easy to fall into the local optimum, which reduces the numerical stability and eventually leads to the problem of difficult convergence.

Although the literature [2] partly solved the problem in the literature [1], the genetic algorithm has the problem of slow calculation speed when the initial population is too large. At the same time, the algorithm does not realize the online real-time optimization function of the heating unit. It cannot be widely used, nor does it consider the influence of the actual operating conditions of the unit on the heat consumption

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