Near-zero carbon stochastic dispatch optimization model for power-to-gas-based virtual power plant considering information gap status theory

Purpose This study aims to form a new concept of power-to-gas-based virtual power plant (GVPP) and propose low-carbon economic scheduling optimization model for GVPP considering carbon emission trading. Design/methodology/approach In view the strong uncertainty wind photovoltaic generation in GVPP, information gap decision theory (IGDT) is used measure tolerance threshold under different expected target deviations decision-makers. To verify feasibility effectiveness proposed model, nine-node energy hub was selected as simulation system. Findings can coordinate optimize output electricity-to-gas gas turbines according difference electricity prices market natural at times. The IGDT method be describe impact solar GVPP. Carbon rights trading increase operating space (P2G) reduce cost Research limitations/implications considers electrical conversion spatio-temporal calming characteristics P2G, integrates it with VPP into uses then proposes near-zero random based on IGDT. Originality/value designed novel structure integrating storage device basic goal minimizing costs. At last, this constructed stochastic