Abstract: As one of the effective methods for integrating new energy sources, microgrids are an essential component of the new-type power system. This paper aims to minimize the operational costs of microgrids under high injection of renewable energy sources, establishing issues related to the forecast combination of renewable energy and microgrid operation optimization, and proposing methods to solve these issues. Initially, daily-ahead and intra-day dispatch models for microgrids considering prediction errors were developed. Subsequently, the problem of finding the forecast results that minimize costs was transformed into solving for the combination weights of various forecasting sub-models, and heuristic algorithms were employed to solve for the combined forecasting weights. Finally, by integrating real renewable energy data into a typical microgrid extended from the IEEE 33-node system, the proposed method was validated for its effectiveness in enhancing microgrid operational benefits, addressing the challenge of discrepancies between renewable power forecasting and microgrid optimization objectives.

Key words: microgrid scheduling, new energy prediction, composite forecasting, end-to-end optimization