Optimal capacity expansion-planning of distributed generation in microgrids considering uncertainties

Abstract

Capacity shortage problem extensively occurs in the developing countries. Microgrids comprising of distributed generation provides a solution to this capacity shortage problem. However an optimal capacity expansion-planning of the distributed generation in a microgrid is necessary to satisfy the load demand most economically. In current research the capacity expansion-planning of distributed generation like wind, solar, diesel generation along with energy storage is carried out considering the uncertainties associated with wind speed, solar radiation and load fluctuation. The account of uncertainties is very important as it results in a more reliable and robust planning model. These uncertainties are estimated by using their expected values based on the probability distributions and the autoregressive model is used to generate the scenarios. A stochastic optimization approach is used for optimal capacity expansion planning with multiple objectives including the minimization of the total net present cost, emissions and non-renewable fraction in the presence of constraints. A microgrid in grid-connected mode is utilized for the example problem. Because of the conflicting objectives, the non-dominant and most near to the optimal solutions are presented using the Pareto fronts. The results from both stochastic and deterministic optimization approaches are compared. The results support the investment and hence the capacity expansion.