CCHP System Operation Analysis And Scheduling Algorithm Improvement

Combined Cooling Heating and Power(CCHP)is one of the main forms of integrated energy system,which has received wide attention both at home and abroad in recent years because of its low energy consumption,high efficiency and environmental friendly features.With the development and application of technologies for the production,transformation,storage and use of cooling,heating and power,the structure and operation scheduling of CCHP have become more and more complex and become a research hot issue.In this paper,we first construct a new CCHP system containing distributed generation,CCHP,gas boiler,electric boiler,heat recovery,battery storage,heat storage,absorption cooling,electric cooling and cold,heat and electric loads,and analyze and establish the operation models of the constituent system components.Secondly,the optimal scheduling models of three commonly used operation modes-Following Electric Load(FEL),Following Thermal Load(FTL)and Following the Hybrid Load(FHL),and compared and analyzed the economic benefits of the same system under different scenarios.It is found that the FHL model is able to optimize the coordination of cooling,heating and power resources more fully and obtain better economic benefits because it is not constrained by human constraints.However,the absence of human constraints also enlarges the optimization search space of FHL mode optimal scheduling,which makes it difficult to obtain the optimal solution of scheduling efficiently.To address the problem of large solution space of FHL mode optimal scheduling,based on the analysis of the effects of cooling,heating and electric load demand,purchase and sale price of electricity,gas price,and operational,economic and environmental characteristics of each production,exchange and storage equipment in the system on the objective function,a method is proposed to reduce the solution space by eliminating the operation conditions that are obviously uneconomic,environmentally unfriendly and impossible at each time of the scheduling optimization.Then,the method is applied to the particle swarm algorithm for solving the optimal scheduling problem of the CCHP system in this paper,and it is demonstrated that the proposed method improves the computational efficiency by 24.60% and decreases the initial integrated operation cost by 56.15%,thus increasing the possibility of obtaining the global optimal solution.