Multi-Objective Analysis of DER Sizing in Microgrids using Probabilistic Modeling

The intermittent nature of DERs like wind and solar designates them as random variables. As a result, their sizing problem may result in an unrealistic microgrid. In this paper, authors have proposed the use of probabilistic models to deal with this intermittency. An algorithm has been developed to estimate a DER resource-data matrix by fitting a time-series into a probability distribution both horizontally and vertically. The DER sizing has been modeled as a multi-objective optimization problem to simultaneously minimize the total net present cost of DERs and treatment cost of environmental emissions. Two types of resource-data matrices have been estimated based on forced and best fitting of time-series. Simulations have been performed by using HOMER Legacy. The multiple objectives have been converted to a single objective by using a judgment matrix and a comparison has been made among deterministic, probabilistic best-fit and probabilistic forced-fit resource-data matrices' based microgrid models.