A cost-optimized power management strategy for combined wind thermal-pumped hydro generation considering wind power uncertainty

The trend of today's power system is to incorporate more green power in the conventional grid to mitigate the power demand and to minimize environmental pollution. This paper proposes a multi-energy system with wind thermal-pump storage plant aiming to minimize the total cost of operation. In this paper, a forecasted data of wind speed is considered. Because of the variable nature of wind power, real-time generation scheduling may lead to deviation of forecasted thermal power generation. This paper works on a power management strategy (PMS) where the gap between the day-ahead scheduled thermal power and the real-time scheduled power is minimized optimizing the operation cost. Cultural algorithm (CA) is used here very efficiently in a modified UI 62 bus. It is observed from the simulation results that the proposed strategy can effectively reduce the power deviation fluctuations with reducing the operating as well as runtime cost. A comparison of total cost between CA and particle swarm optimization (PSO) is drawn in this paper to observe the efficacy of the proposed method.