access icon free Day-ahead unit commitment model for microgrids

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 CO2 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.

Inspec keywords: power generation scheduling; air pollution; carbon compounds; renewable energy sources; demand side management; turbines; distributed power generation; optimisation; power generation dispatch; power system security; fuel cell vehicles

Other keywords: CO2; fuel cell; discharge schedule; heuristics-based optimisation methodology; microturbines; storage unit; congestion signals; unit scheduling; day-ahead time horizon; distribution system operators; day-ahead unit commitment model; congestion management approach; demand side participation strategy; microgrid units; system security; UC model; optimal scheduling; storage device; microgrid operating costs; renewable energy resources; electric vehicles; DSO

Subjects: Power system management, operation and economics; Energy resources; Distributed power generation; Fuel cells; Transportation; Optimisation techniques; Power system control

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