Network reconfiguration under a stochastic optimisation framework for Day-Ahead Operation Planning for Future Distribution Networks

Abstract

This paper proposes a novel Active Network Management (ANM) framework for day-ahead operations planning of a medium-voltage active Distribution Network (DN) using a heuristic Network Reconfiguration (NR) algorithm with a Curtailment Minimisation Scheme (CMS) to maximise utilisation of renewable Distributed Generation (DG) resources. The reconfiguration scheme uses Back-to-Back Voltage Source Converters (BTB-VSCs) in the network as Soft Open Points (SOP) which are modelled mathematically using the Flexible Universal Branch Model (FUBM) developed previously in Durham University. Moreover, this day-ahead ANM framework takes into account the variable nature of RES outputs by adopting a stochastic multi-scenario formulation using the Inverse Transform Method and Stratified Sampling to generate power output realisations for the RES. Simulations carried out for a modified IEEE-33 distribution test system shows the proposed ANM framework is capable of reducing operational costs by 2.22% to the system operator whilst actively regulating the voltage throughout the network and reducing curtailment in medium and high power output scenarios.