In this study, a heuristics-based optimisation methodology for a day-ahead unit commitment (UC) model in microgrids is proposed. The model aims to schedule the power among the different microgrid units while minimising the operating costs together with the CO(2)emissions produced. A storage device is added where the charge and discharge schedule is calculated according to both objectives. In addition, as a part of the demand side participation strategy, a charging schedule was determined for the electric vehicles (EV) in order to increase the system security and further reduce the costs and emissions. A congestion management approach is also introduced, which eliminates congestions by effective unit scheduling according to congestion signals provided by the distribution system operators. The complete day-ahead time horizon is divided in 96 time steps (each with a 15 min time span), which makes the UC problem more complicated. The studied system includes renewable energy resources, a storage unit, two microturbines, a fuel cell and EVs. The results demonstrate that the proposed model is robust and is able to reduce the microgrid operating costs and emissions by optimal scheduling of the microgrid units, and is able to take into account local congestion problems
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.