Optimization of Isolated Microgrid in the Presence of Renewable Energy Sources and Demand Response Programs

Abstract

This paper analysis the regions that lack of reliable electricity access and presents modeling and planning of an isolated microgrid. In fact, the optimization of microgrid component capacities is done in the form of six scenarios in the presence of renewable energies, pumped heat energy storage system (PHES), and demand response (DR) programs. The programs used in this paper include various time-based and incentive-based DR programs with the exponential model, which is one of the nonlinear models of DR programs and is more conservative than the linear model. The uncertainty of wind speed, solar irradiance, and demand load is modeled by probabilistic distribution functions. The Latin hypercube sampling (LHS) method is used to generate scenarios of wind speed and solar irradiance. Also, the K-mean clustering algorithm is used to reduce the number of scenarios. A rural region in India is chosen as a case study. At the end of the study, the results of different simulation scenarios are compared with each other, the effects of DR programs on the size of microgrid components are discussed and the best DR program is chosen.