Configuration Optimization And Operation Optimization Of Combined Cooling,Heating And Power System Considering Source-Load Uncertainty

The Combined Cooling Heating and Power system(CCHP)is a multi-energy comprehensive supply system with cogeneration equipment as the core,including multiple distributed units such as power generation,load,and energy storage,and multiple energy forms such as cooling,heating,and electricity.The CCHP systems are attracting attention for their high energy utilization,high reliability,economy,flexibility in dispatching,and promotion of new energy consumption.However,the operational performance of CCHP system is closely related to the reasonable configuration and operation mode of the system.It is important to determine the optimal configuration scheme and optimal operation mode of CCHP system to give full play to the advantages of CCHP system.The main research contents of this paper are as follows.(1)Aiming at the problem of fuzzy C-Means(FCM)clustering algorithm that it is difficult to determine the fuzzy coefficient and the number of clusters,the FCM algorithm is improved.The core of the improved algorithm is to introduce the PFS index to evaluate the validity of the geometric structure of the data set and the Vp index to evaluate the validity of the membership degree on the basis of the traditional FCM clustering algorithm.And use the entropy method to weight the two to comprehensively evaluate the effect of clustering.Afterwards,the optimal number of clusters,fuzzy coefficients and the clustering results under the optimal parameters are found through the traversal method.The improved FCM algorithm was applied to the clustering of load and meteorological data,and the results verified its effectiveness.(2)Aiming at the problem of the optimal configuration of the CCHP system,a two-layer optimal configuration model of the CCHP system based on the improved FCM algorithm is constructed.First,build an outer optimized configuration layer with the goal of the lowest average annual conversion investment and operating cost of the system and the smallest annual carbon dioxide emissions.After that,build an internal operation optimization layer with the goal of minimizing daily operating costs.Finally,the internal and external models are nested into each other,and the clustering results of weather and load data based on the improved FCM algorithm are used as input,and the solution is completed by combining the NSGA-Ⅱ and PSO algorithms.According to the actual case application,the proposed method is used to optimize the configuration of Photovoltaic Power System,electric and thermal energy storage equipment,and the results verify the effectiveness of the method.(3)Aiming at the problem of optimal operation of the CCHP system,a multi-objective optimal operation model of the CCHP system based on chance constraints is constructed.First,build a multi-objective optimization operation model with the minimum daily operating cost and minimum daily carbon dioxide emissions as the goal.Later,in order to deal with source-load uncertainty,chance constraints were introduced into the constraint conditions of the optimization model,and probability constraints were used to replace traditional deterministic constraints.Finally,on the basis of obtaining the typical daily load and meteorological data,the NSGA-Ⅱ algorithm is used to complete the solution.For the actual case,the system operation is optimized based on the completion of the optimal configuration for scheduling.And the effectiveness of the method is verified by comparing with the traditional method.