| Available Transfer Capability(ATC)reflects the power exchange capacity between different regions of the power grid and provides a reference for the stability evaluation of the power grid.With the development of the integrated energy system,the natural gas network is further coupled with the power grid,and the calculation of ATC will become more complicated,thus affecting the calculation efficiency of ATC.In view of the above problems,this thesis proposes an ATC calculation method for the electricity-gas integrated energy system(EGIES)based on the concept of Digital Twins.Firstly,the data-driven and model-driven methods are combined to fully mine the information hidden in the massive state data,thus simplifying the iterative calculation process of the traditional physical model and shortening the calculation time.Secondly,the digital twins model is constructed to process the continuously updated state data in the integrated energy system in real time,realize the online calculation of the maximum transmission capacity and extract the characteristics of the system operation state.Then,the extracted features are used to calculate the ATC of the integrated energy system.Finally,the effectiveness and efficiency of the proposed method are verified by IEEE30-NGS10 electric-gas integrated energy system.The main completed research contents are as follows:1)This thesis discusses the basic principle of digital twinning,analyzes the rationality and feasibility of applying the digital twinning concept to the state perception and index calculation of the electric-gas integrated energy system,and puts forward the specific application form of the digital twinning concept in the electric-gas integrated energy system and the corresponding idea of establishing the digital twinning model.2)The data produced by the current electric-gas integrated energy system has the characteristics of large amount of data and high dimension,and the construction of digital twin model needs to study and analyze these data and extract the data characteristics.It’s difficult for the current data analysis tools to complete this task,so this thesis introduces the neural network method,a powerful high-dimensional data analysis tool,and uses the neural network technology to improve the two main calculation links of the traditional available transmission capacity calculation,the maximum transmission capacity and the existing transmission capacity,to meet the two important technical indicators of accuracy and rapidity in the digital twin concept.While using neural network,the calculation logic in this thesis still uses the traditional available transmission capacity calculation logic,which ensures that the constructed digital twin model still has the interpretability of the mechanism model.3)This thesis expounds the calculation logic of the traditional available transmission capacity,and establishes the calculation model of the available transmission capacity using the optimal power flow algorithm.Through analysis and comparison,the maximum transmission capacity calculation link and the existing transmission capacity calculation link that needs to be improved by the neural network method are determined.First of all,the energy flow distribution calculation model of natural gas system and the model of gas turbine,the coupling element of the electric-gas integrated energy system,are constructed,and the coupling principle of the two heterogeneous energy systems,electric power system and natural gas system,as well as the influence mechanism between them are explained.Secondly,this thesis clarifies the improved method of using selforganized incremental learning network and convolution neural network to calculate the maximum transmission capacity and the existing transmission capacity respectively,and shows the operation principle and data flow path of the digital twin model built by using neural network method.Finally,this thesis takes IEEE30-NGS10 electric-gas integrated energy testing system as an example,The coupling of the natural gas system and the failure of the system are divided into four scenarios for verification.The verification results show the rationality and feasibility of the method in this thesis,and the accuracy change of the results obtained from the model is explained by introducing the data dispersion index.The main innovation points of this thesis are as follows:1)This thesis analyzes the applicability of digital twinning in the integrated energy system of electricity and gas,and proposes an application form of digital twinning concept with the goal of calculating available transmission capacity in the integrated energy system of electricity and gas.This form can be used to calculate real-time or predicted values that reflect the current operating status of other indicators of the system,laying the foundation for establishing an evaluation system with the goal of EGIES security assessment.2)This thesis proposes a method for establishing a data mechanism fusion model.On the basis of the traditional mechanism calculation logic of available transmission capacity,a neural network based data processing method is adopted to improve the long calculation time and slow iteration speed in the calculation of available transmission capacity,in order to meet the technical requirements of the digital twin concept.3)This thesis constructs a virtual model for calculating the available transmission capacity of an electric gas integrated energy system that meets the requirements of the digital twin concept.This model is data-driven and based on historical data as the prediction foundation,which can quickly and accurately predict the changes in available transmission capacity of the integrated energy system without electricity or gas. |
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