The Probabilistic Reliability Evaluation Method Of The Electricity-gas Integrated Energy System Considering Correlations

Energy is necessity for human's survival and development.Despite solving the energy crisis,the large-scale utilization of renewable energy,such as wind power,also poses challenges to the dispatch capabilities of the power grid,because of the uncontrollable output of that renewable energy.Energy-interconnected systems with multiple complementary and multi-network integration can promote the efficient and safe use of renewable energy.The most common energy-interconnected system is the electricity-gas integrated energy system,which combines the natural gas network and the power network.With the enhancement of electricity-gas coupling and the expansion of the system size,the quantitative reliability evaluation of the electricity-gas integrated energy system is of great significance to ensure the safe and stable operation of that integrated system.There are numerous random factors in the electricity-gas integrated energy system because of the increasing penetration level of renewable energy and the rising number of various users.Meanwhile,there are also correlations between the wind speeds of adjacent wind power plants,and between the neighboring loads.If the randomness and correlations of renewable energy and loads are analyzed from the perspective of probability,and renewable energy output and load power are regarded as input random variables of the whole system,the output reliability indices are also random variables which contains a large amount of probability information.The above process is regarded as the probabilistic reliability evaluation.The purpose of this thesis is to investigate the probabilistic reliability evaluation method of the electricity-gas integrated energy system and to consider the impact of correlations on system reliability.Firstly,the probability distribution model of wind speeds and loads is established.Because there are correlations between input variables,and the traditional correlation matrix method is not suitable for non-normal variables,Nataf inverse transformation is employed to investigate those correlations.On account of the great difficulty of analyzing the correlation coefficients transformation process directly,an approximate one-dimensional polynomial equation is proposed by the Hermite series expansion,which greatly simplifies the solution of the process.The correctness and effectiveness of the method are verified by a case study.Next,probabilistic reliability evaluation methods based on the Monte Carlo method and the point estimation method are proposed respectively.The basic theory of the point estimation method is studied,and the applicability of the three-point estimation method is pointed out.Considering the traditional point estimation method cannot be applied to correlated variables,the variables are processed by the above Nataf inverse transformation.Then,based on the electricity-gas integrated energy system consisting of a modified IEEE RBTS-Bus6 feeder F4 system and a modified NGS10 natural gas system,the reliability evaluation is analyzed by the Monte Carlo method and the point estimation method respectively.The reliability indices of two methods indicate that the point estimation method is as accurate as the Monte Carlo method,but spends much less calculation time.Finally,the effects of correlations and electricity-gas coupling levels on system reliability are studied.