Data-Driven Optimal Battery Storage Sizing for Grid-Connected Hybrid Distributed Generations Considering Solar and Wind Uncertainty

A large-scale renewable-based sustainable power system requires multifaced techno-economic optimization and energy penetration. Due to the volatile non-periodic nature of renewable energy, uncertainty renewables combined with load uncertainties significantly impacts operational efficiency integration. The complexities in balancing demand, generation, maintaining reliability have introduced new challenges current distribution system. Most associated can be effectively reduced by using a battery storage (BESS) right techniques for handling uncertainties. In this paper, distributionally robust (DRO) technique linear decision rule is formulated unit commitment (UC) framework optimal scheduling network that consists wind farm, solar PV, distributed generator (DG), BESS. To cut cost per unit, BESS plays an important role storing at off-peak time on-peak-time use relatively lower prices. For all-time minimum overall systems cost, size connected provide DGs. Three case studies are IEEE 14 bus (converted from MW kW match available market) solved proposed achieve maximum operating point capacity BESS, i.e., wind, hybrid. Each study has its own 30-min interval schedule DGs along comparison without impact on start-up shut down reported all dynamic economic dispatch results, including battery’s state-of-charge profile. handle allows economical sizing comparatively computational processing complexities.