LAUSR

Nowadays, the installations of photovoltaics (PVs) in the smart grid have been growing dramatically because the price of PVs is falling drastically. Undoubtedly, this is a great achievement for the recent smart grid technology. However, the colossal penetration of PVs’ power at the day-time changes the load demand of thermal generations (TGs) of a smart grid which creates duck shape load curve called duck curve. In a duck curve, peak and off-peak gaps are very large which increase the start-up cost (SUC) of TGs because the units of TGs must be turned ON and turned OFF frequently. Therefore, it is very significant to run TGs units optimally. Only an optimization technique is not enough to bring a good solution. This research considers concentrated solar power and pumped storage hydroelectricity (PSH) as the energy storages. Also, fuel cells are considered as the controllable loads in the demand side’s smart houses. In addition, this paper considers the real-time price-based demand response. The optimal unit commitment (UC) of TGs, PSHs, and other generators is introduced for saving the fuel cost and SUC of TGs. The optimal results of the proposed model are determined by using MATLAB® INTLINPROG optimization toolbox. To evaluate the effectiveness of the proposed method, simulation results have been compared with some other methods.