Reconfiguration Of Distribution Networks Containing Wind Power And Photovoltaic Considering The Uncertainty And Correlation

Reconfiguration is an important way to optimize the operation of distribution networks(DN),which can be used to reduce power loss and improve the reliability and economy of DNs.In recent years,with the depletion of coal,oil and other traditional fossil energies,and the increase of environmental pollution,renewable energies,such as wind power and solar power,have been widely utilized in the world.Unfortunately,these energies increase the uncertainty of power system planning and operation due to their inherent randomness of power generation while being accessed to DNs.In addiiton,the wind speed,solar irridiation and load demand have a cross-correlation characteristic due to the affection by similar climite factors,which leads to big challenges to the optimization of DN operation.Therefore,this thesis studies DN reconfiguration problem considering uncertainties and correlations with DNs containing wind power and photovoltaic as the research object.In order to analyze the impacts of uncertainties and cross-correlations among wind power,photovoltaic and load demand on DN power flow,a stochastic power flow model considering these uncertainties and correlations for DNs with wind power and photovoltaic is developed based on a Monte Carlo simulation method.Firstly,weibull,beta and the normal distributions are adopted to describe the uncertainties of wind speed,solar irridiation and load demand,repectively.Then,an improved correlation matrix method is used to model the cross-correlations among wind speed,photovoltaic and load demand.Finally,calculation of stochastic power flow for DN with wind power and photovoltaic have been conducted based on a Monte Carlo simulation method.A modified IEEE-33 DN is used as an example to analyze the impact of the cross-correlation on DN power flow.Simulation results have shown that the cross-correlation has a siginificant effect on the active power loss and node voltage.In order to analyze the impacts of uncertainties and cross-correlations among wind power,photovoltaic and load demand on DN reconfiguration,the Monte Carlo stochastic power flow is embedded into DN reconfiguration.A single-objective chance constrained DN reconfiguration model considering wind power and photovoltaic is then proposed.The model is built to minimize the expected value of active power loss,with the ability to take these uncertainties and correlations into consideration.Finally,an improved integer particle swarm algorithm is proposed to solve the problem.Based on the integer coding rule of basic loops,a methodology of judging and repairing the invalid solutions in the process of DN reconfiguration through the disconnection branch group vector is proposed.Modified IEEE-33 DN and PG&E69 DN are used as examples.Simulation results have shown that the DN reconfiguration model can not only reduce the active power loss as well as improve the voltage,but also can depict the impact of uncertainty and cross-correlation on the result of DN reconfiguration effectively.In order to reduce the computational amount of Monte Carlo stochastic power flow during the process of DN reconfiguration,based on the discrete model a scenario reduction method is proposed.A multi-objective coordinated DN reconfiguration model considering the active power loss and the number of switching operations is developed.The scenario reduction method can effectively reduce the computational amount of Monte Carlo stochastic power flow while ensuring the accuracy of the results.The multi-objective DN reconfiguration model takes into account the expected value of active power loss,the number of switching operations and load balancing index.The multi-objective particle swarm optimization algorithm which is based on Pareto optimal solutions is adopted to solve this problem.Modified IEEE-33 DN and PG&E69 DN are used as examples.Simulation results have shown that the proposed scenario reduction method based on discrete model can effectively reduce the size of scenarios and the computational amount of Monte Carlo stochastic power flow,leading to an improved efficiency of DN reconfiguration.Compared with the single-objective DN reconfiguration,multi-objective reconfiguration model could produce more solutions.