Research On Matching Design Of Regional Distributed Energy Cluster System

Distributed energy cluster system is a multiple co-generation energy system based on the concept of "cascade utilization of energy",which densely arranges multiple co-generation systems of cooling,heating and power at the user end in the form of small capacity,decentralized and modular.It has the technical advantages of energy conservation and environmental protection.With the development of system clustering,the increase of the number of equipment and the diversification of user needs,the optimization calculation of the system is becoming more and more complex,which restricts the popularization of technology.Therefore,it is urgent to carry out in-depth research.There is a lack of quantitative matching analysis between load and system on the demand side,and a lack of comprehensive quantitative analysis of the impact of various factors of the system on performance on the supply side.Based on these problems,the calculation problem is solved by simplifying the model and using sparrow algorithm firstly.Secondly,taking the distributed energy system as a reference,the performance characteristics of the cluster system are quantified.Then,the demand side is analyzed,and it is found that there is a correlation between user load and performance index.Finally,the supply side is optimized and the impact of system factors on performance is quantitatively analyzed.The main work is as follows:Modeling and calculation.Through variable classification optimization and linear constraints,the model is simplified:(1)the optimization variables are divided into direct variables(internal combustion engine capacity and operation strategy)and indirect variables(equipment capacity and operation strategy other than internal combustion engine),so as to reduce the number of variables directly generated by the algorithm and reduce the amount of calculation;(2)The capacity and operation optimization process of equipment other than internal combustion engine are integrated into the energy exchange process of the system through the energy balance principle to linear the constraints and reduce the computational complexity.With the help of sparrow algorithm,the calculation speed is improved.The problems of long calculation time and difficult convergence of the model are solved.Quantitative analysis of the characteristics of distributed energy cluster system.It is found that the performance of the distributed cluster system is different under different loads,but it is always better than the distributed energy system: the operation and maintenance cost of the cluster system is reduced by 12.59%,the carbon emission is reduced by 16.90%,the energy consumption is reduced by 15.00%,and the comprehensive performance is improved by 14.41%.The reason is that under the same conditions,the optimal performance of distributed energy cluster system has a larger operation range,higher load rate of internal combustion engine,and more output of electric energy and waste heat energy.Demand side analysis.The primary screening method of high matching user load of the system is proposed.That is,tentatively screening the high matching user load of cluster system by using the negative correlation between the standard deviation coefficient of user load thermal power ratio and performance index.In addition,the demand side response optimization improves the comprehensive performance of the cluster system by 6.17%,and the user load response in winter is more sensitive.Supply side analysis.It found that,the performance of the cluster system is improved by storing energy and expanding the number of subsystems of the cluster system.The results show that energy storage makes the output ratio of electric energy and cold energy on the supply side of the cluster system more reasonable,so the comprehensive performance of the cluster system is improved by 4.73%.The deepening of the system network topology is conducive to the improvement of the comprehensive performance of the system: the number of subsystems is increased from one to four.Compared with the distribution system,the comprehensive performance is improved by 45.57%,56.57%,57.82% and 67.96% respectively.The main reason is that: increasing the number of subsystems expands the optimal performance operation range of the cluster system.