Research On Load Restoration Strategy After A Blackout Considering The Uncertainty Of Renewable Energy Output

Power system reliability is improved by grid interconnection,but power outages caused by extreme conditions such as severe weather and man-made attacks are still unavoidable.It is necessary to formulate related recovery plans in advance to reduce outage time and load losses.During load restoration,large-scale renewable energy is connected to power system,which can provide additional power support for the system and improve load restoration efficiency.However,due to the fluctuation of renewable energy,the deviation between the actual output and predicted output may be relatively large,which may lead to active power deficiency in the system.In severe cases,it may even result in grid decomposition and black-start failure.It is essential to consider the uncertainty of renewable energy output during load restoration after a blackout.The Fuzzy model is applied to consider the uncertainties of renewable energy output and load increment during load restoration after a Blackout.However,it is difficult to guarantee the accuracy of the membership function.For these reasons,considering that the robust method can describe the uncertainty parameters without probability density and membership function,this paper based on the robust theory studied on load restoration strategy after a blackout considering the uncertainty of renewable energy output.The main research work of this paper is as follows:Firstly,the modeling of deterministic load restoration model was studied.With the maximum weighted load increment as the optimization objective,the frequency and power flow constraints that the generators and load must meet during the load restoration after a blackout were analyzed and the artificial bee colony algorithm was used to solve the problem.The IEEE 39 test system verified the model effectiveness and the disadvantages of the deterministic load restoration model were analyzed,which laid the foundation to establish a robust load restoration model considering the uncertainty of renewable energy output.Secondly,based on the branch flow model and robust optimization theory,a load restoration model after a blackout considering the uncertainty of renewable energy output was established.The uncertainty of renewable energy and load was expressed as the robust interval.And the model was linearized by duality theory and second-order cone programming.Thus,a single-layer mixed integer second-order cone robust optimization model was established,which can be efficiently solved by CPLEX.The IEEE39 test system was used as an example to verify the model validity.Thirdly,with the uncertainty budget and cutting planes method introduced,an adjustable robust load restoration model after a black out considering the uncertainty of renewable energy output was established.The types of the uncertainty set and the influence of different uncertainty budgets on the conservativeness of model solution results were studied.Then,the cutting planes method was applied to iteratively reduce the power flow error to ensure the accuracy of the branch flow model.The adjustable robust model was also solved by CPLEX,and its validity was verified by IEEE39 test system.Fourthly,the models proposed in this paper were applied to the actual system,and the effectiveness of the proposed models was validated by comparing with the non-linear deterministic model based on the AC power flow model,the deterministic load restoration model based on the branch power flow model,the deterministic load restoration model with renewable energy participation,the robust model with load uncertainty,the robust model with renewable energy uncertainty and the robust model with renewable energy and load uncertainty.