As renewable energy becomes more prevalent in transmission and distribution systems, it is vital to understand the uncertainty and variability that accompany these resources. Microgrids have the potential to mitigate the effects of resource uncertainty. With the ability to exist in either an islanded mode or maintain connections with the main-grid, a microgrid can increase reliability, defer T&D infrastructure and effectively utilize demand response. This study presents a co-optimization framework for a microgrid with solar photovoltaic generation, emergency generation, and transmission switching. Today, unit commitment (UC) models ensure reliability with deterministic criteria, which are either insufficient to ensure reliability or can degrade economic efficiency for a microgrid that has a large penetration of variable renewable resources. A stochastic mixed integer program for day-ahead UC is proposed to account for uncertainty inherent in PV generation. The model incorporates the ability to trade energy and ancillary services with the main-grid, including the designation of firm and non-firm imports, which captures the ability to allow for reserve sharing between the two systems. In order to manage the computational complexities, Benders' decomposition is applied. The commitment schedule is validated with solar scenario analysis, i.e., Monte-Carlo simulations are conducted to test the proposed dispatch solution.
- Stochastic programming Solar energy Power system reliability Power generation economics Day-ahead scheduling Mathematical programming
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering