Toward Day-ahead Reactive Power Optimization For Distribution Networks With Renewable Energy

In order to alleviate the pressure of fossil energy and environment,distributed generations(DGs)play a more and more important role in distribution systems.Due to the great influence of natural conditions on the output of DGs,the intermittent and fluctuating of DGs bring some challenges to the distribution network.Toward day-ahead reactive power optimization model considering the scheduling scheme of reactive power control equipment from the viewpoint of 24-h,in order to adapt to the fluctuating of output active power of DGs and load,frequent operation of the on load tap changing transformer(OLTC)and capacitor need to be done,which brings a lot of difficulties to operation and equipment maintenance of distribution system.In order to solve this problem,a three-stage reactive power optimization method is proposed to minimize the required number of operating control devices for a time horizon of 24 hours.The aim is to determine,via solving a mixed integer nonlinear programming(MINLP)problem,optimum setting values of transformer taps,capacitor banks and reactive power output of distributed generators(DGs)based on the day-ahead load demand and active power output of DGs satisfying the engineering and operational constrains.The first stage is assessment stage,which assessments the voltage magnitude and available deliver capability margin(ADCM)to identify the time period with violation for proper control actions.This stage ensures that the actions emerge only if violation occurs,which can fully exploited the capability of system to deliver the power from DGs to loads and remove unnecessary actions.The second stage is time-partitioning stage,which uses AP clustering to partition 24-h into several coherent time period based on voltage magnitude.The third stage is coordinated reactive power optimization,which can give the values of control variables during every time period.A modified IEEE13 case and IEEE123 case are used to verify the effectiveness of the proposed three-stage method.