Methods Study Based On Improved Genetic Algorithm To Geothermal Heating System Economy Optimization Evaluation

Geothermal energy as a new type of clean renewable and the most realistic one ofthe most competitive energy is being more and more national attention. Geothermalheating is the main way to use in our country. Therefore, the purpose of this paper is notonly to study the optimal method of geothermal heating systems in order to improving theutilization of geothermal energy, but also to achieve higher economic efficiency.In this paper, analysis based on the principle of geothermal heating systems, andusing an improved genetic algorithm (ie genetic simulated annealing algorithm) on theoptimization of geothermal heating system operation in order to explore the new methodof optimization for geothermal heating system.In this paper, it concluded as follows: The mathematical modeling of the geothermalheating system to optimize, in real engineering applications can get good results; Use theimproved genetic algorithm method in the geothermal heating system optimization;Using Matlab program to model and treatment geothermal heating system can greatlyimprove the geothermal heating system optimization.The innovation of this paper includes the following:1. Through the process the analysis and optimization of modeling of geothermalheating system, found that influential factors of optimization model of geothermalheating system: Peak Ratio and geothermal water temperature;2. Heating degree days using the least square method linear regression values, tocreate a geothermal heating system heating Peak mathematical model of heatconsumption, and thus calculate the peaking heat energy to heating and heat consumptionin heating base load and peak load calculations, and further calculate the fuelconsumption peaking, geothermal heating system for the optimization of reference;3. Geothermal heating system is a complex system affected by many factors,in thispaper, using one of the modern genetic that is the algorithm optimization methodsapplied to geothermal heating system optimization process works4. In this paper, based on their different search capabilities of genetic algorithm andsimulated annealing to improve the genetic algorithms in order to facilitate the ability of optimization model.5. Using the Matlab program genetic algorithm toolbox provides geothermal heatingsystem on the mathematical modeling, and using an improved genetic simulatedannealing algorithm to optimize the mathematical model.