Apply three metaheuristic algorithms for energy storage-based integrated power system to reduce generation cost

This research applies new computing methods to optimize the operation of a typical hydrothermal system for one day. The consists thermal power plant (TPP) and pumped storage hydropower (PSHP). main target is determine amount water that must be discharged or back reservoir reduce total electricity production cost (TEPC) TTP. volumes in at beginning end points schedule same. Three meta-heuristic algorithms are applied, including Coot optimizer (COOT), aquila (AO), particle swarm optimizations (PSO) which COOT AO were proposed early 2021. results show effectiveness better than AO, PSO several previous studies. Hence, considered powerful tool problem.