Research On Weak Decoupling Optimization Of Dynamic Matching Based Distributed Energy System

With the purpose of ensuring national energy security as well as the efficient utilization and sustainable development of energy,the distributed energy system are required to develop in both supply and utilization side.So combined cooling,heating and power(CCHP)system was investigated in this research.The matrix modeling was developed and expanded to decouple the strong coupling relationship between the heat and power demand and supplement.Thus,the dynamic matching problem of CCHP system is able to decompose into two major problems as load forecasting and the operation optimization.Firstly,a theoretical matrix optimization model which links the supply,conversion,storage and utilization of energy was established for the optimization of CCHP system under strong coupling conditions,.Then the matrix optimization and graph optimization methods were preliminary combined through the graph theory,which can provide a weak decoupling method for nonlinear optimization of CCHP system from methodological aspect.Secondly,for load demand,the characteristics of building load were analyzed based on the actual operation data.The input variables of load forecasting were selected by the correlation theory and the principal component analysis.The hourly load forecasting models in heating season and the cooling season with the network topologies of 6×8×1 and 5×8×1 using back-propagation(BP)artificial neural network intelligent algorithm were construct.Compared with the measured values,the average relative error of forecasting values was 5.43%in heating season and the average relative error of forecasting values varied from-10%to 10%mostly in cooling season.Then,based on the calculation of annual dynamic load demand,the capacities of equipment and the hourly part load ratio were selected as optimization variables,and the comprehensive criteria,including the economic,energy saving and environment perspectives was selected as optimization objective.The design optimization was conducted.Results showed that the CCHP sysem perfoemd best in the optimal operation strategy among the three operation strategies.While in the following thermal load strategy without electricity feed in tariff,the capacity of internal combustion engine and the comprehensive evaluation criterion were the smallest,however,the comprehensive performance was still better than that of separate system.Finally,based on the load forecasting results and the optimal system configuration,the hourly dynamic matching optimization and the load matching evaluation were conducted Results shown that the electricity purchased from the grid and the cooling/heating supply from the auxiliary ground source heat pump on weekdays were larger than that on weekends.Thus,the operation evaluation criteria were lower on weekdays.The on-site energy matching of electricity supply(OEM_e)was relative lower in heating and cooling seasons than that in transition season.However,the on-site energy fraction of electricity supply(OEF_e)shown the opposite results.In addition,the results of the on-site energy matching of thermal supply and the on-site energy fraction of thermal supply were just the oppsite of OEM_e and OEM_e.