Gas-Electric Power Coupling Simulation Method for Integrated Energy System Based on Improved MCMC

The construction, operation and evaluation of an integrated energy system (IES) requires a large sample of data. However, the data generated by traditional Markov chain Monte Carlo (MCMC) simulation is random timing. Traditional MCMC simulation is difficult to ensure the coupling of gas and electric power data timing matching. A gas-electric IES power coupling simulation method based on improved MCMC is proposed in this paper. Firstly, the K-means method based on Dunn Validity Index is used to cluster the two-dimensional data of gas and electric energy. Secondly, two-dimensional state transfer matrix for various types of gas and electric energy is constructed, and the transfer matrix is coded in reduced dimensions. Then, Fitting the duration of the state matrix by inverse Gaussian distribution and a large amount of transition state is generated. By dimension-up coding and superimposing random fluctuation components, a large number of gas-electric power data with fluctuation characteristics of original data are generated. Finally, the coupled data simulation evaluation index is established, and a large number of actual data are used to evaluate the fitting data. The effectiveness of the algorithm is verified.