Multi-objective Optimization Theory And Application Of Biomass-driven Multi-energy Complementary Combined Heat,Power And Biogas (BCHP) System

With the increase of carbon dioxide emissions,the air temperature rises year by year,which seriously threatens the life system in nature.To achieve the development goal of carbon peak and carbon neutral,China takes the initiative to undertake the responsibility of global green and low-carbon development.The ultimate aim is to making the pollutant emissions around the whole world from relative emission reduction to absolute emission reduction,and then zero emission.The combined cooling,heating and power(CCHP)system is widely valued all over the world for its various energy supply forms,high energy conversion efficiency,clean operation process,and huge environmental friendly potential.The biomass-driven CCHP system is composed of many types of equipment,which are interdependent and interact with each other.Once the configuration is improper,it would cause low efficiency and waste of resources of the system.In this paper,according to the characteristics and specific demands of the biomass-dominant combined heating,power and biogas(BCHP)system,considering the energy efficiency,air pollutant emissions and economic effect,the multi-objective optimization model of BCHP system is constructed.The model is applied to the households in rural areas in Lanzhou city,which is an example to verify the accuracy of optimization model.The sensitivity of the optimized BCHP system is analyzed from the perspective of technology and cost parameters.The process parameters with high sensitivity are regarded as the critical factors to study the dynamic influence of the parameters on the multi-objective optimization results.According to main research content,this paper can be divided into the following four parts.(1)An energy supply system with biomass energy as the main input energy is constructed,coupling advanced technologies such as air-source heat pump,anaerobic fermentation and internal combustion engine cogeneration system.Through energy,material and data flow,the multi-objective optimization mathematical model of the BCHP system is established,including system,evaluation,operation strategy and optimization model.(2)The extremum of relative evaluation indexes are regarded as the optimization objective.The demand side constraint,energy balance constraint and equipment operation constraint are considered as the constraint conditions.Combined the improved non-dominated sorting in genetic algorithm(NSGA-Ⅱ),the simulation program is compiled based on Visual Studio 2017 software C++,realizing the multi-objective optimization of the BCHP system.(3)Taking the capacity of internal combustion engine,heat pump and anaerobic fermentor as decision variables,the established simulation program is applied to solve optimization problem based on different optimization objectives.The influence of different optimization parameters on optimization results is analyzed and compared,moreover,the reliability of the model is verified by comparing the performance before and after optimization.The results show that the selection of population number and propagation algebra has a crucial impact on the optimization results,that is to say,balancing the calculation speed,time and accuracy is extremely necessary.Taking the maximum primary energy saving rate,emission reduction rate and annual cost saving rate as the optimization objectives,the comprehensive performance index increases from 0.269 to 0.299 when the three weight factors are all one in three,.Besides,the proportion of biomass energy input increases from 78.17% to 85.61%,which proves the reliability of the multi-objective optimization model.The comprehensive performance index based on three optimization objectives is significantly higher than that based on the two optimization objectives,furthermore,the each performance is relatively balanced.(4)The sensitivity of the optimized biomass gas cogeneration system is analyzed from the technical and cost perspectives,and the dynamic influence of process parameters on the multi-objective optimization results is studied.The results show that the most influential parameters of comprehensive performance index are power generation efficiency of power plant and thermal efficiency of coal furnace,and the most influential parameters of annual cost saving rate are biogas slurry price and unit cost of anaerobic reactor.When the process parameters change,the optimization results would vary accordingly.In addition,the changing trend of optimized results are closely associated with robustness of comprehensive performance index.In order to promote the large-scale application of biomass driven cogeneration system in China,investors should pay more attention to the government subsidies for biogas projects,adopt flexible price policies to improve the income of the system,and select anaerobic digestion system with high biogas conversion efficiency as far as possible.