Research On Building Matching Characteristics And Multi-objective Optimization Design Method Of Combined Cooling Heating And Power System

Since the Industrial Revolution,fossil fuels such as oil and coal have promoted the process of global industrialization and urbanization,but they have also caused environmental pollution and energy shortage.In order to achieve sustainable economic and social development,improving energy efficiency and the use of renewable energy have become effective ways to deal with energy and environmental problems.The integrated energy system of cold,heat and electricity can realize the efficient complementary utilization of fossil energy and renewable energy.It has become an effective means of energy supply in the future and has attracted extensive attention.However,due to the problems such as single energy source,unreasonable design and poor match between supply and demand,the spread and development of the technology are limited to a certain extent.This paper focuses on the optimization of high-efficiency solar and gas complementary cooling and heating cogeneration systems and the matching of energy supply and demand.From the capacity characteristics of gas cooling and heating integrated energy systems,the matching characteristics of building load demand and energy systems,solar and gas complementary integrated energy systems.The multi-objective optimization and decision-making methods were studied in depth.The research in this paper mainly focused on the combined heat and power system based on solar and gas internal combustion engines,but the research methods involved can be extended to other types of integrated energy systems.The main work of this article was summarized as follows:This paper conducted an experimental study on the operating performance of building-type combined heat and power plants and park-type combined heat and power stations,and analyzed the output characteristics,operating efficiency,and performance of key equipment of the distributed combined heat and power system.A mathematical correlation of relevant performance parameters was also established.For the building-type combined heat and power system,with the increase in power generation,the water-heat efficiency of the cylinder liner was similar to the change law of the heat recovery efficiency of the unit and the total efficiency of the unit and the water-heat efficiency of the cylinder liner.Among them,the total efficiency of units in heating mode was between 64.5%and 82.7%.The total efficiency of the unit in cooling mode was between 51%and 59.1%.For the park-type combined heat and power system,the main power range of the core combined heat and power unit was 3500k W-4300k W,the average energy utilization efficiency of the unit in cooling mode can reach 85.6%,and the average energy utilization efficiency of the unit in heating mode was 77.64%.The annual average power generation efficiency of the park's combined heat and power system was 42.54%,and the annual energy utilization rate was73.52%.The influence of building load characteristics on optimal design parameters and operation performance of gas-fired cooling,heating and power supply units is studied by statistical analysis method.The multi-factor variance analysis for building type,climate type and operation strategy was carried out,and the building type was the biggest factor that affects the performance of cold,heat and power supply units.Regression models of the operating performance and design capacity of the cold,heat and power supply system were established.R² values of all models reached more than 0.8,and key parameters affecting the unit performance and design capacity were screened out.In large-scale hotels,hospitals and nursing homes,the operating performance of the system was the best,with ATCSR(Annual total cost saving ratio)between 5.47%and 12.36%and PESR(Primary energy saving ratio)between 10.63%and 22.17%.In all climatic regions,the combined performance of cold,heat and power co-generation systems was optimal in cold and severe regions.Rational use of heat storage equipment can significantly improve the performance of the cooling,heating and power supply system.The solar energy and gas complementary cold,heat and power supply system was constructed,and the standard particle swarm optimization algorithm was improved by using linear inert factor and dynamic annular neighborhood methods,and the particle swarm optimization algorithm was formed for the solar energy and gas complementary comprehensive energy system.The optimal design and operation results of solar energy and gas complementary cold,heat and power supply system under five operating modes were analyzed.The corresponding PESR,CO₂ERR(CO₂ emission reduction ratio)and ATCSR reached 36.15%,53.73%and 4.16%,respectively.The influence of building load characteristics and operation strategy on the performance of solar and gas complementary cold,heat and power supply system were analyzed.FTL(Following thermal load)strategy was applicable to hotels and hospitals,while FEL(Following electric load)strategy was applicable to office buildings.The optimal comprehensive performance of hospital,hotel and office buildings could reach 28.95%,28.20%and 22.69%.Based on the standard particle swarm optimization(PSO)algorithm and pareto optimal theory,the external solution set storage and update strategy,global optimal selection strategy and global perturbation strategy were designed,and a multi-objective particle swarm optimization algorithm for solar energy and gas complementary integrated energy system was developed.Furthermore,the entropy weight method and TOPSIS(Technique for order preference by similarity to ideal solution)multi-attribute decision making were combined to form a multi-objective particle swarm optimization and decision-making method for solar energy and gas complementary integrated energy system.The results of single-objective optimization and multi-objective optimization were analyzed and compared.The optimal value of single index in pareto solution set was higher than that of single index obtained by single-objective optimization.The solution set can provide diversified optimization design schemes.Among the optimization results obtained by each method,the single index can't achieve the optimal value at the same time,but there was little difference between the optimal value of each index and the optimal value of the single index,and the absolute difference was within 7%.Latin hypercube sampling is used to generate simples of solar irradiation and energy demands,and the uncertainty problem is transformed into a scene analysis problem.The uncertainty optimization objective equation is designed,and the multi-objective PSO is used to optimize the uncertainty multi-objective problem.In the optimization objective equation,when the penalty coefficient is set to 700,a better performance value can be achieved and the standard deviation is reduced.Compared with the optimization result of the uncertain scenario,the PESR and CO₂ERR of the system under the uncertain scenario increased by0.24%and 1.46%,respectively.But the ATCSR decreased by 3.38%.The standard deviations of PESR,CO₂ERR and ATCSR decreased by 0.05%,0.05%and 0.23%.