Research On Probabilistic Energy Flow Analysis For Electricity-Gas Integrated Energy Systems With Wind Power Correlation

With the trend towards large-scale grid integration of clean energy sources,the uncertainties in the integrated energy system are significantly increased by the influence of wind power.In particular,the correlation between wind farms belonging to the same region and spatially distributed in close proximity makes the calculated energy flows of the power system and the natural gas system connected through the coupling nodes deviate significantly from the actual results.Therefore,the probabilistic energy flow solution method of Nataf transformation combined with maximum entropy principle method is used to analyze the probabilistic distribution characteristics of state variables of the electric-gas integrated energy system under the correlation of input variables.The main research contents are as follows:1)The network framework of electricity-gas integrated energy system is constructed,and the physical models of power system and natural gas system are analyzed and then their mathematical models are sorted out.The steady-state energy flow equation of electric-gas integrated energy system is established,and the system operation state is obtained by solving and calculating,which lays a foundation for the probabilistic energy flow calculation of electric-gas integrated energy system.2)In order to cope with the impact of large-scale wind power grid connection on a large number of uncertain factors on the operation characteristics of the power-gas integrated energy system,two uncertain factors,electricity,gas load and wind power output,are considered as input variables.In order to solve the shortcomings of the existing probabilistic energy flow algorithm,under the framework of semi-invariant method,The principle of maximum entropy method to calculate comprehensive energy systems containing wind power-gas probability and energy flow,in the form of a central moment as input into the proposed algorithm fitting get state variables of the probability density function,and finally through the IES30-20 nodes integrated energy testing system to verify the proposed algorithm for the applicability of the large-scale wind power integrated energy system,The accuracy and rapidity of the algorithm are proved by the comparison of calculation time and accuracy.3)In order to solve the correlation probability of random variables on electricity and gas integrated energy system energy flow,the influence of processing method in this paper,using the correlation of random variables include the singular value decomposition of twice permutation and Nataf transformation of two major steps,first of all,twice permutation implements the random variable by the correlation coefficient matrix decomposition,Nataf transform to realize the random variables and the conversion between standard normal variables,the samples meet the specified requirements of the input variable is obtained after half invariants calculated,the premise of considering semi invariant computing,sensitivity matrix modified descendants of the node into matrix into the half invariant computing framework is obtained by the maximum entropy principle method fitting the probability distribution characteristics,Finally,the IES118-20 node integrated energy test system is taken as an example.From the perspective of calculation accuracy,the algorithm can still accurately fit the probability density function of state variables even considering the correlation of input variables.From the perspective of wind speed correlation on system operation characteristics,the correlation of wind speed will lead to the risk of over-limit in the electric-gas integrated energy system,and it also demonstrated that the proposed algorithm can be used to analyse the fluctuating characteristics brought about by large-scale wind power grid connection,providing comprehensive information for proper decision making.