Research On Steady-state Modeling And Interaction Effect Analysis Of Integrated Energy Systems

The integrated energy system,as an important physical carrier in the future,is significant in realizing the global energy internet and ubiquitous network of things.It can enable different types of energy to complement with each other,widely access ports and absorb high proportion of renewable energy and fully realize the cascade utilization.Due to the diversified structure of integrated energy system,it can tailor to various conditions and extensive access as to "plug and play",the development of integrated energy systems is closely related to policies,emerging markets and other outstanding technologies.This has led to the diversity and complexity of its steady-state modeling.This thesis will further discuss the problem in depth.Firstly,based on the structural characteristic categorization of the integrated energy system,it analyzes the main developmental problems.Then,the steady state modeling of the integrated energy system is combined with the correlation problem to clarify the internal operation and the correlation effects.The main innovations and achievements are as follows:(?)In view of the current research on pollution control and clean operation of integrated energy system,this thesis hopes to introduce a theory of total pollutant control into the modeling of integrated energy system,and propose a collaborative optimization model of environmental system.The optimal operation of the integrated energy system and the improvement of the regional environmental quality have been realized,which provides a theoretical method for the clean operation planning of the system.(?)Due to the strong coupling relationship between the multiple energy sources in the integrated energy system in transmission and conversion,the carbon emission is difficult to be clearly defined,and the total amount of carbon emissions cannot be accurately measured.Aiming at such problems and based on the principle of low-carbon operation,this thesis hereby proposes a life-cycle energy chain analysis method that combines carbon trading means to construct a low-carbon model,and analyzes the method for grid connection.The impact of the two modes of operation and off-grid provides a theoretical approach for integrated energy systems to participate in carbon trading and achieve low-carbon regulation.(?)Aiming at the electric vehicles in the integrated island energy system,the thesis puts forward a psychological risk assessment for users and constructs an independent island terminal integration system.Through simulated optimization,a reasonable electric vehicle quantity scheme can be seen,and the influence of different schemes on the system operation can be analyzed,which further provides a theoretical method for realization of the electric vehicle promotion and island electrification.(?)As a flexible user-side terminal,the inner-building integrated energy system is strong coupling with energy storage equipment and electric vehicles.In order to improve energy efficiency and reduce wastes,this thesis proposes a multi-directional interaction model of "source-network-load-storage" for integrated energy systems.In combining V2G technology and room temperature control,the inner-building integrated energy system for refrigeration,heat and electric load demand is modeled and optimized,and different scheduling strategies are proposed according to users-behaviors in order to reach an approach in multi-directional interaction mode.(?)Due to the coupling relationship between multiple load demands of integrated energy systems,traditional load forecasting methods are difficult to meet the mixed load forecasting requirements of integrated energy systems.Hence,this thesis proposes a multi-layer LSTM multi-task deep learning algorithm,combined with VIP technology and Spearman rank correlation analysis,constructs a hybrid energy load forecasting model for integrated energy systems,and evaluates the accuracy of prediction with RMSE.The results have shown that such prediction model effectively solves the problem,where hybrid energy load of the integrated energy system is difficult to predict due to strong coupling.Furthermore,this thesis hopes to shed light on a guiding ideology for the application of artificial intelligence technology used in the forecasting of comprehensive energy system load.