DC Microgrid energy management with correlated uncertainties

Abstract

A DC microgrid operator (DCμGO) economically balances the load demand and generation within a DC-Microgrid (DCμG) while satisfying different technical constraints. This paper deals with a multi-objective (MO) day-ahead energy management scheme (EMS) for a DCμG by leveraging different flexibilities available to the DCμGO. The objectives of the EMS are to minimize the operating cost (OC) and energy loss while meeting voltage and feeder current limits and other technical constraints associated with different DCμG components. Various flexibility resources like dispatchable and non-dispatchable distributed generation (DG), battery energy storage system (BESS), demand response (DR) participators, and DC soft open point (DCSOP) are considered in the developed model. Uncertainties of input random variables (RVs) are modelled using a probabilistic Point estimate method (PEM) approach. The correlation between the random variable (RV)s is incorporated using a Newton's Interpolation method embedded inverse Nataf Transformation (NT) technique. The MO optimization is solved using the epsilon-constraint method. Simulation studies on a ten-bus DCμG test network reveals that the proposed MO approach can reduce the expected OC in a day by ∼5.80% and the expected energy loss in a day by ∼1.01%. © 2023 Elsevier Ltd