Multi-stage active management of renewable-rich power distribution network to promote the renewable energy consumption and mitigate the system uncertainty

Abstract

This paper presents a multi-stage management scheme for renewable-rich medium voltage distribution network (MVDN) to promote the renewable energy consumption and mitigate the system uncertainty. In the first stage, a day-ahead (DA) dispatch model is proposed to promote the renewable distributed generation (RDG) consumption and decrease the power loss. In the second stage, a model predictive control (MPC) based rolling optimization model for intra-day (ID) operation is proposed to minimize the mismatch of the interactive power at the upstream Grid Supply Point (GSP) between the DA schedule and ID operation. Multiple active management elements such as network reconfiguration and soft open point are integrated and a novel second order cone programming (SOCP) model for the centralized optimal power flow in the DA and ID stages is presented. In the third stage, a decentralized P/Q(V) control strategy of RDG inverter for real-time (RT) voltage regulation is proposed to ensure system safety and mitigate the fast voltage fluctuation. The effectiveness of proposed management scheme is demonstrated in a test system integrating a standard network and real-world data of load and RDG output profiles.