Abstract A bi-level optimal configuration model considering stochastic optimal power flow of the distributed wind and photovoltaic generation in the active distribution network (ADN) based on chance constrained programming is proposed.The upper level aims at maximizing the annual benefits considering the investment income of the traditional distribution network and the cost of the distribution automation.The chance constraints of the static security are acquired by Monte Carlo (MC) stochastic simulation and forward and backward substitution power flow method.The lower level aims at minimizing the distributed generation (DG) output curtailment considering the static security chance constraints and the active management (AM) constraints,i.e. active power curtailment of DG,voltage regulation of on-load voltage regulating transformer,and power factor adjustment of DG.Then,Genetic Algorithm,MC stochastic simulation,and forward and backward substitution power flow method are combined to find the solution.The lower level model will be quickly launched when the conditions of the static security chance constraints of the upper lever are not satisfied.Simulation results suggest that the model can effectively avoid the adverse effect from small probability events within AM and chance constraints in a satisfying confidence level,and acquire the ADN planning scheme considering safety,economy and environment factors with a variety of capacity penetration boundaries.
Ma Rui,Jin Yan,Liu Mingchun. Bi-level Optimal Configuration of Distributed Wind and Photovoltaic Generations in Active Distribution Network Based on Chance Constrained Programming[J]. Transactions of China Electrotechnical Society, 2016, 31(3): 145-154.
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2016, Vol. 31 
