Fixed head short-term hydrothermal scheduling in presence of solar and wind power

A probabilistic short-term hydro-thermal-wind-photovoltaic scheduling based on point estimate method (PEM) is proposed in this article. To model the uncertainties associated with wind and solar power, point estimate method is used. The Weibull and Beta distributions are employed to handle the uncertain input variables. The mean generation cost of the system is optimized based on an optimization algorithm named crow search algorithm (CSA). Three test systems have been taken, the first test system contains only hydro and thermal plants, and rest of the two systems are based on wind and solar including hydro and thermal unit to investigate the effect of renewable energy sources in the selected test systems. Furthermore, underestimation and overestimation of available wind power has also been included in the problem. The simulation results show that when the penetration of renewable energy sources increases, the mean generation cost decreases. The results obtained by CSA have been compared with other well-known methods. Moreover, the accurate distribution of generation cost for the next day-ahead can be found out using Gram-Charlier series expansion.