Optimal Sizing of Battery-Integrated Hybrid Renewable Energy Sources with Ramp Rate Limitations on a Grid Using ALA-QPSO

Higher penetration of variable renewable energy sources into the grid brings down plant load factor thermal power plants. However, during sudden changes in load, plants support grid, though at higher ramping rates and with inefficient operation. Hence, further additions must be backed by battery storage systems to limit rate a avoid deploying diesel generators. In this paper, battery-integrated that include floating solar, bifacial rooftop, wind are evaluated for designated smart city India reduce plant. Two variants adaptive-local-attractor-based quantum-behaved particle swarm optimization (ALA-QPSO) applied optimal sizing hybrid minimize levelized cost (LCoE), life cycle loss (LCL), supply probability (LPSP). The obtained results then compared four differential evolution. show out 427 MW potential, an set containing 274 rooftop PV, 99 60 supported 131 MWh batteries LPSP 0.005%, LCoE 0.077 USD/kW, LCL 0.0087. A sensitivity analysis through ALA-QPSO is performed assess impact damage unplanned appreciation, it found more sustainability.