Distribution Network Planning Method Under Uncertainty Load With Eletric Vehicle

With the continuous influx of new technologies and new equipment such as electric vehicles,uncertainty has become a factor that must be considered in the planning of distribution networks.Common uncertainties mainly include random uncertainty and fuzzy uncertainty.Considering the influence of uncertainty helps to improve the adaptability and reliability of the grid.However,existing research rarely considers mathematical indicators for assessing systemic risk levels,and thus does not quantify systemic risk and control risk.In addition,existing research rarely considers the coexistence of multiple uncertainties,or treats multiple uncertainties into a single uncertainty,but a single uncertainty cannot always accurately characterize the uncertainties of different mathematical characteristics.Therefore,this paper studies the problems existing in the research of distribution network planning,and proposes corresponding solutions.The main research contents are as follows:Firstly,the uncertain variables,uncertain programming and uncertain simulation methods in uncertain programming theory are summarized.The random variables and fuzzy variables from uncertain variables are introduced;Fuzzy expectation model,fuzzy chance constrained programming and fuzzy stochastic hybrid chance constrained programming of uncertain programming are introduced;The stochastic simulation,fuzzy simulation and fuzzy stochastic simulation of uncertain simulation are introduced.Secondly,from the perspective of considering systemic risk indicators,the distribution network planning model under fuzzy uncertain load is established,and the credibility index is introduced to evaluate the system security level under fuzzy uncertain load,and combined with the fuzzy chance constraint of credibility theory to achieve the role of quantifying risk and controlling risk.The equivalence theorem of credibility index is introduced,and the fuzzy chance constrained model is simplified into an interval model to solve the problem,thus reducing the difficulty of solving.The genetic algorithm is usedto solve the model.In the process of solving,the Monte Carlo simulation is used to sample the interval to check the system constraints in the interval form.Finally,from the perspective of various uncertainties in the distribution network,further considering the random uncertainty of the charging load of the electric vehicle and the fuzzy uncertainty of the general load,the bi-uncertainty grid planning model of distribution network with electric vehicles is established.The model aims to minimize the sum of the fixed investment of the distribution network and the fuzzy random network loss during the planning period,introduces the hybrid opportunity constraint to deal with the line power constraint and the node voltage constraint,and balances the relationship between investment cost and operation risks by setting two different confidence level parameter values.A genetic algorithm based on hybrid simulation is proposed to solve the model built in this paper.In this paper,the 25-node and 50-node power systems are taken as examples to calculate and verify the model.Through the example analysis,the two planning methods solve the problem of system security indicators and coexistence of multiple uncertainties.It makes the risk of the planning scheme quantified and controlled,and has better adaptability and practicability.