Vehicle-to-grid (V2G) feature in electric vehicles enables ancillary support to the grid due to its bidirectional power capability. This work mainly focuses on effective utilization of PEV’s storage capacity to suppress solar PV and load power fluctuations using PEV’s storage capacity. A win-win strategy between customer and utility is proposed by maximizing revenue for customer and to minimize demand fluctuations. Water Filling Energy Dispatch Algorithm (WFEDA) is used to optimally schedule PEV’s available energy. Adaptive neuro-fuzzy inference system (ANFIS) is designed and implemented to prioritize PEVs with revenue maximization and load flattening as the key objectives. © 2019, Springer Nature Singapore Pte Ltd.