| With the development of science and technology,mankind has made unprecedented progress,but the dependence on energy has also become more and more intense.However,many energy sources themselves are non-renewable,and scarcity will surely become a normal condition.At the same time,this kind of application also has a bad effect on the environment pollution.In the face of this form,the state has adopted a variety of regulatory strategies,for each of us,we should actively respond to the various measures formulated by the country,constantly save energy,reduce CO2 emissions.And we often use electricity and renewable green and sustainable energy to protect the environment and meet the needs of the use at the same time.In order to respond to the national call and the current development trend,this paper proposes to combine the secondary clean energy with renewable green energy solar energy to construct a compound energy heating system.Because the use of solar energy has the shortcomings of randomness and intermittence,so it is necessary to add other forms of energy.In this paper,the air source heat pump and electric boiler are combined to construct a complex system of various forms of energy.The system can satisfy the user’s demand for thermal energy,and can also make efficient use of energy and reduce the emission of pollution.In the running process of the system,it is necessary to use as little energy as possible,make use of the solar energy as much as possible,and make the energy efficiency ratio of the system as high as possible.In the severe situation today,energy conservation and emission reduction has become an important research content in this field.In this paper,the characteristics of the main equipment of the system are studied and the mathematical model is established.The multi-objective optimization model is established for the multi-objective optimization problem and the constraints are put forward.In the traditional multi-objective algorithm,the optimization of the objective problem only converts the multiobjective into a single objective,and many optimal solutions will be lost in the process of optimization,which is often not accurate.In the conventional multi-objective artificial bee colony algorithm,there are many shortcomings,for example,in the process of the algorithm,each new solution will be separately compared to determine the choice,which greatly reduces the optimization efficiency of the algorithm,and the use of external population on the preservation of excellent food sources greatly increases the operation space of the algorithm and other shortcomings.Aiming at these shortcomings of multi-objective artificial bee colony algorithm,this paper proposes an improved multi-objective artificial bee colony algorithm,these include the following three aspects: The quality of initial population is improved by replacing random sequence with chaotic sequence,and the operation efficiency of the algorithm is improved by optimizing foraging mechanism.The idea of Pareto domination and fast nondomination is introduced by using the idea of NSGA-II for reference.And the method of congestion degree calculation is improved by normalization,so that the optimization criteria of all optimization objectives are unified.This study selected actual cases to verify the feasibility of the scheme.On the basis of a full analysis of the case,the energy efficiency ratio data of the composite energy heating system before and after optimization were fully analyzed.The final results show that the optimized data has a higher energy efficiency ratio.The validation shows that the model and algorithm obtained in this study have a higher energy efficiency ratio than the traditional algorithm.This study can provide more effective guidance for the research in this field,and provide technical support for the large-scale promotion of composite energy systems. |
