A multi-objective reconfiguration method for distribution networks considering the wind-photovoltaic-load uncertainty and correlation

Abstract

With the advancement of new-type power systems， the large-scale integration of distributed generation （DG） poses challenges to the optimal operation of distribution networks. In response， a multi-objective reconfiguration method for distribution networks is proposed， which takes account of the wind-photovoltaic-load uncertainty and correlation. The Copula theory is applied to construct a correlation model， and wind speed-irradiance-load correlation samples are obtained through Spearman’s rank correlation coefficient. By introducing complex network theory， the paper addresses the network vulnerability considering the intermittency of wind and photovoltaic output powers. To minimize network losses， network vulnerability， and switching times of switchgears at a certain confidence level， a multi-objective coordinated optimization reconfiguration model considering the uncertainty of wind， solar， and load output is established based on chance-constrained programming， and a parameter adaptive algorithm is applied to solve the model. Case studies verify that the proposed method can balance effectiveness and usability.

Keywords

• multi-objective reconfiguration
• correlation
• uncertainty
• copula theory
• network vulnerability