DC Microgrid energy management with correlated uncertainties

A DC microgrid operator (DC & mu;GO) economically balances the load demand and generation within a DC-Microgrid (DC & mu;G) while satisfying different technical constraints. This paper deals with a multi objective (MO) day-ahead energy management scheme (EMS) for a DC & mu;G by leveraging different flexibilities available to the DC & mu;GO. 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 DC & mu;G components. Various flexibility resources like dispatchable and nondispatchable 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 DC & mu;G test network reveals that the proposed MO approach can reduce the expected OC in a day by & SIM;5.80% and the expected energy loss in a day by & SIM;1.01%.& COPY; 2023 Elsevier Ltd. All rights reserved.