Distributed Generation and Load Modeling in Microgrids

Abstract

Solar PV and wind energy are the most important renewable energy sources after hydroelectric energy with regard to installed capacity, research spending and attaining grid parity. These sources, including battery energy storage systems, and well-established load modeling have been pivotal to the success of the planning and operation of electric microgrids. One of the major challenges in modeling renewable-based DGs, battery storage, and loads in microgrids is the uncertainty of modeling their stochastic nature, as the accuracy of these models is significant in the planning and operation of microgrids. There are several models in the literature that model DG and battery storage resources for microgrid applications, and selecting the appropriate model is a challenging task. Hence, this paper examines the most common models of the aforementioned distributed energy resources and loads and delineates the mathematical rigor required for characterizing the models. Several simulations are conducted to demonstrate model performance using manufacturers’ datasheets and actual atmospheric data as inputs.

Optimal Allocation and Sizing of Decentralized Solar Photovoltaic Generators Using Unit Financial Impact Indicator

“…In this work, the power demand profiles are generated according to the guidance in Reference [36], which studies the consumption trends with respect to consumer behavior. More specifically, the daily load profiles are generated from a realistic point of view, with two peaks per day at noon and evening times where relatively higher power demand levels are expected [37]. Please note that the profiles of the 24-h demand curves (each profile representing a day of the year) resemble each other and only differ in peak values due to seasonal variations in consumption.…”