Research On Scenario Generation And Reduction Method Considering Temporal And Spatial Correlation Of Wind And Solar Energy

In the context of large-scale wind and solar renewable energy access to the power system,the uncertainty of its output sets new requirements for the operation and control of power systems.It has become an important subject for power systems with a high proportion of renewable energy to reasonably describe the correlation between wind and solar power output,and cope with the uncertainty characteristics.Based on this,the article focuses on the scenario generation and reduction of wind and solar energy.The main work and results achieved are as follows:Firstly,the spatial-temporal correlation between wind and solar power output is clarified,and the multivariate normal distribution is used to describe the temporal correlation of wind and solar output.In order to analyze the correlation characteristics of multi-dimensional variables,the R-Vine Copula function is introduced.This function can form the unique vine structure based on actual data,and complete the spatial correlation analysis according to the corresponding vine structure.Aiming at the shortcomings of the existing scenario generation methods that do not comprehensively consider the spatial-temporal correlation,the conventional sampling method is expanded to propose the vine structure sampling method of multi-dimensional variables in this article.On the basis of the scenarios with temporal correlation for each wind farm and photovoltaic power plant,the above scenarios are modified in combination with the vine sampling results of multi-dimensional variables.So that the generated scenarios satisfy both the volatility in the time series and the distribution characteristics of wind and solar power output.At the same time,the commonly used scenario reduction method is improved,and the internal characteristics of the remain scenarios are further restricted.The calculation time and accuracy are improved to a certain extent.In terms of the scenario evaluation,the scenario evaluation index considering the probabilistic distance is proposed,and the quality of the scenarios is evaluated from the two aspects of the fluctuation characteristics and distance of the generated scenarios and the measured values.In order to further verify the effectiveness of the scenario generation and reduction method proposed in this article,the day-ahead power system scheduling model is established in this paper.And generated scenarios are used to generate scheduling decisions for the power system.At the same time,the economics of each scheme is evaluated through comparative analysis.The risk of each scheme is assessed through risk indicators by establishing the risk assessment model for scheduling decisions.The economics and risk of scheduling decisions are comprehensively evaluated,and the superiority and practicability of the scenario generation and reduction method proposed in this paper are further verified.