Study On Optimization Method Of Combined Cooling,Heating And Power System

With the growing importance of climate change,it is critical to reduce the carbon emissions of the energy system.The combined cooling,heating and power（CCHP）system faces users directly,produces and supplies energy on the spot based on user needs,and consumes local renewable energy in real time,significantly reducing carbon emissions and improving energy utilization efficiency.CCHP system can supply users with cooling load,heating load and electric load.CCHP system’s core capacity units are gas turbines and waste heat recovery devices.CCHP system includes energy input,conversion,storage,and transmission,allowing for efficient energy use in the region.CCHP system has emerged as a power system development and research hotspot at present.The research direction of CCHP system is how to set up the equipment,energy flow mode,and energy scheduling scheme in the system to achieve maximum energy utilisation.In this paper,the overall operation scheme and capacity allocation of the system are deeply studied,and a new heuristic algorithm is proposed to solve the operation optimization problem of the system.The typical cities in different climate regions are selected for simulation and analysis.The following are the main contents:In order to model the supply and demand planning of a CCHP system,this paper divides the CCHP system into supply and demand sides.The supply side consists of renewable energy systems,carbon recovery systems,energy supply systems,and energy storage systems.The mathematical model of the corresponding equipment is established and its energy flow mode is set based on the characteristics of supply-side energy equipment and energy coupling mode.Demand side is a hotel,office,park,shopping mall,convention,apartment（HOPSCA）.The HOPSCA is divided into several areas,and the characteristics of the relevant areas are analysed to calculate the cooling load,heating load,and electric load.The economic index and emission index based on carbon trading are chosen as the optimization objectives,and the design and operation of a CCHP system is abstracted as a mathematical optimization problem.In order to solve the algorithm of fast convergence and insufficient search accuracy,this paper combines the multi-swarm and the Levy flight strategy with the particle swarm optimization algorithm and proposes an improved multi-swarm particle swarm optimization algorithm based on Levy flight.These improvements are as follows:（1）The initial particles are divided into several sub-populations,which are clustered and divided again at regular intervals.（2）After each iteration,the optimal particles of each sub-population are subjected to a Levy flight.To validate the superiority of the improved algorithm proposed in this paper,ten different types of test functions are assigned.The improved algorithm,particle swarm optimization algorithm and Cuckoo algorithm were respectively used to run the optimization for ten times,and the mean value,the optimal result,the worst result and the variance were analyzed.Through comparison,it is possible to conclude that the improved algorithm proposed in this paper outperforms the particle swarm optimization algorithm and the cuckoo algorithm in terms of optimization ability and stability.Aiming at the inconsistency between climate and renewable energy in China,this paper takes typical cities in four climate zones as research objects and puts forward four configuration schemes.Scheme 1 includes all subsystems and equipment.Scheme 2 is a reference system that only includes the renewable energy power generation system,gas boiler,and centrifugal water chiller.Scheme 3 cancels the lithium bromide absorption heat pump,and scheme 4 cancels the carbon recovery system and energy storage systems compared to scheme 1.The optimization results show that compared with the reference system,the total cost saving rates of the four cities in scheme 1 are-2%,1%,3%and 4%respectively.The total cost savings for scheme 3 are 1,1,2 and 1respectively。The total cost savings for scheme 4 are 4%,5%,4%and 5%respectively.The carbon emission saving rates of scheme 1 are 61%,57%,50%and 49%respectively.The carbon emission saving rates of scheme 3 are 29%,31%,35%and 35%respectively.In scheme 4,the carbon savings rates were 45%,47%,46%and 48%.Taking into account the initial investment,construction,maintenance,and environmental treatment costs during system operation,the CCHP system’s economy has not significantly improved compared with the referenced system,but its carbon emissions have been significantly reduced.As latitude decreases,the carbon emission saving rate of CCHP systems with carbon recovery systems and energy storage systems decreases,while the carbon emission saving rate of CCHP systems without carbon recovery systems and energy storage systems increases.As a result,the carbon recovery system and energy storage system quotas can be appropriately increased in high latitudes to reduce the system’s CO₂ emissions,while the quotas can be appropriately reduced in low latitudes to reduce the system’s total cost.In areas rich in renewable energy,the system can effectively use its own surplus electric energy to actively reduce its own CO₂emissions through carbon recovery devices during the heating season,and in these areas,the quota of carbon recovery devices can be appropriately increased to further reduce the system’s CO₂ emissions.Based on the research results,the configuration and energy scheduling schemes of each unit of the CCHP system in different climate zones are obtained,which can serve as a guide for future construction of CCHP systems in various regions.The research content of this paper provides ideas for the future development of integrated energy system operation optimization of CCHP system.