Application Of Reduced Order Modelling Based On Finite Element Method In Semi-physical Distributed Energy System

With the increasing demand for energy and constraining of pollutant and carbon emission around the world,the development of new type energy systems which are efficient and environmentally friendly is particularly important.Distributed energy system,as a clean and efficient energy production mode among energy supply,has been attached great importance at home and abroad and becomes one of the key research and development directions in the field of energy.Dynamic characteristics simulation,optimization and control of distributed energy systems have become a popular research direction,as a result,it is of great significance to establish accurate and efficient dynamic mathematical models for the system and its components.In the research of distributed energy systems,semi-physical research method have unique advantages.However,due to the existence of physical components and mathematical models in the system,these models are required to have strict real-time performance.The model established by finite element method can shows the distribution of internal parameters in detail.However,limited by computer performance,the finite element model consumes a lot of computing resource so it can’t be used in real-time simulation.On the contrary,The mathematical model in the distributed energy semi-physical system cannot obtain detailed information of the internal physical field due to real-time calculation.Therefore,this paper proposes a reduced order method combine proper orthogonal decomposition and galerkin projection in the semi-physical simulation system,which unified the finite element model with the semi-physical system.The main work of this paper includes: Firstly,establish the full order model of heat exchanger and verify the algorithm.On this basis,solve the full-order model of heat transfer process in the heat exchanger and collect internal temperature distribution in the plate at the sampling point.and The function space of the collected samples is taken as the space of the reduced-order model located,and a set of orthogonal basis functions of the space is obtained and truncated by the proper orthogonal decomposition method.Secondly,the full order model is projected into the reduced-order space by the Galerkin projection method,which reduces the model’s degrees of freedom.Finally,the real-time communication between the reduced-order model and the process simulation model established in APROS(Advanced Process Simulation)is realized through OPC protocol,and the real-time data exchange between them is realized.In the process,the calculation time and accuracy of the reduced-order model are verified and the dynamic characteristics of hybrid generation system with reduced order model.In this paper,the method of establishing the reduced order model is introduced and it can guarantee sufficient calculation accuracy under the premise of satisfying the real-time performance,and lay a solid foundation for the application of high precision and high speed real-time model in semi-physical system.