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Research On Robust Optimal Dispatch Of Microgrid With Distributed Energy And V2G

Posted on:2020-01-16Degree:MasterType:Thesis
Country:ChinaCandidate:S P LiFull Text:PDF
GTID:2392330578968675Subject:Systems Engineering
Abstract/Summary:PDF Full Text Request
Vehicle to Grid(V2G)technology can provide support for the local consumption and stable grid connection of renewable energy.At the same time,the renewable energy can be effectively absorbed in the form of microgrid or merged into the large grid to effectively solve the volatility of renewable energy.The impact on the grid.At the same time,the randomness and volatility of electric vehicle(EV)charging power and renewable energy generation in the microgrid prompted us to explore an effective strategy to improve the safety and economy of distributed generation systems.Firstly,according to the research direction and modeling method of V2G technology in recent years,this paper analyzes and classifies the V2G technology from the aspects of grid side,user side,energy storage system and environmental benefits.Systematic analysis of the application areas of V2G electric vehicles and statistics in tabular form.Aiming at the uncertain factors existing in the grid-connected microgrid in typical scenarios,the application of robust optimization in typical scheduling is emphasized.Irn order to prevent the over-conservative characteristics of traditional robust optimization,this paper introduces an adjustable robust optimization algorithm,which is intended to improve the economics of the system at the cost of reducing system robustness,thus finding a compromise between decision makers.Secondly,in view of the charging scenario of electric vehicles,this paper uses interval prediction theory to model the uncertainty of wind power output power and electric vehicle charging behavior.From the perspective of economic and environmental benefits,establish a multi-objective scheduling model to meet the microgrid.Improve the economics of the dispatching system on the premise of stable operation.The validity of the model is demonstrated by introducing examples,and the economics of the scheduling system under the two strategies and the immune function of the system to the uncertain variable interference are demonstrated by comparing the results of stochastic optimization and robust optimization.In order to avoid the over-conservative characteristics of traditional robust optimization,this paper introduces an adjustable robust optimization algorithm to compromise the robustness and economy of the system.The case study shows that the adjustable robust optimization algorithm can effectively solve the energy control problem involving electric vehicles and wind power intervention.Finally,for the V2G energy network,this paper constructs the uncertainty set of the charging and discharging behavior of electric vehicles based on the State of Charge(SOC),and discusses the performance of the scheduling system under the influence of three-way uncertain variables.Based on the comparison of the original methods,the adjustable robust optimization algorithm is used to analyze the energy flow control under large-scale V2G electric vehicles and wind power intervention.Based on the original algorithm,this paper combines interval prediction theory and adjustable robust optimization algorithm,and proposes a full-interval economic analysis method.The sensitivity analysis of the number of uncertain variables to the robustness of the system is carried out,the algorithm provides a theoretical basis for scheduling applications in the microgrid.
Keywords/Search Tags:Grid-connected microgrid, interval prediction theory, adjustable robust optimization algorithm, multi-objective dispatch, V2G electric vehicle, economic analysis
PDF Full Text Request
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