Research On The Method Of Distribution Network Reconfiguration Considering Load And Distributed Generation Uncertainty

With the advantages of environmental protection, flexible and efficient, distributed generation as a kind of new energy power generation, have been widely used in society. It brings many conveniences to us, but also brings the complexity and uncertainty to the grid. With the Distributed generation being installed in the distribution network, the original power flow, power loss and voltage stability will be affected. Therefore, in order to ensure the safe and stable of the grid, it will have to take the uncertainty into account. The distribution feeder reconfiguration is an important technical means to ensure the safe and stable of the grid. Based on this, this paper will make a research on the method of intelligent distribution network reconfiguration considering the uncertainty of load and distributed generation.The traditional back/forward sweep distribution load flow algorithm is improved by taking advantage of a node-layer strategy. Different types of DGs are classified into PQ, PI, PV and PQ(V) type nodes. Then we can establish the models of four type nodes in power flow calculation. A back/forward sweep distribution load flow algorithm with DGs based on the node-layer is realized. The performance of the algorithm and the capacity for calculating power flow of the network with various types of DGs are also simulated and analyzed.An intelligent distribution network reconfiguration method based on adaptive modified particle swarm optimization algorithm is proposed. Nonlinear inertia weight is adopted to ensure that the algorithm can effectively deal with the nonlinear optimization problem of distribution network reconfiguration. The model of distribution network reconfiguration with the minimum network loss is established. According to the radial structure of distribution network, the integer coding strategy and the switch loop-sending end matrix is adopted, which reduces proportion of infeasible solutions and improves the convergence speed and efficiency of optimization. Simulation results show that the proposed method of intelligent distribution network reconfiguration is effective.A scenario-based method is proposed to deal with the problem of intelligent distribution network reconfiguration considering the system uncertainties. The solution methodology consists of two stages, which firstly, employs roulette wheel mechanism in conjunction with Weibull probability distribution function of wind/load forecast variations for random scenario generation wherein the stochastic distribution feeder reconfiguration problem is converted into its respective deterministic equivalents (scenarios). In the second stage, for each deterministic scenario, a formulation based on the adaptive modified particle swarm optimization is realized for each deterministic scenario of the first stage, and the final reconfiguration scheme is determined by the method of expected value. Simulation results verify the feasibility of the distribution feeder reconfiguration under the uncertainty factors, and analyze the impact of uncertainty on the distribution feeder reconfiguration.