Multi-timescale optimal scheduling of microgrids for generating new energy output scenarios based on correction error sampling intervals

Abstract

Microgrid can realize energy saving and emission reduction and multi-energy complementation, but the fluctuation of renewable energy output and the error of day-ahead scheduling will threaten the stability of microgrid operation. For this reason, this article proposes a microgrid multi-timescale optimal scheduling method based on new energy output scenario generation. First, the microgrid framework of this article is introduced, and an energy cycle emission reduction model taking into account electricity-to-gas conversion is designed; second, a new energy prediction error model is established based on the prediction box and Gaussian hybrid model, and the scenario of wind and photovoltaic power generation is generated by correcting the sampling intervals for error sampling; and then, based on the day-ahead scheduling plan, an intraday cooling, heating and electricity two-layer rolling optimization model is established to correct the day-ahead scenario. Finally, the example analysis shows that the cyclic emission reduction model can realize the recycling of resources, reduce the fuel cost and carbon emission, and the generation of scenarios for wind power can smooth out the fluctuation of new energy power, which, together with the intra-day two-layer rolling optimization, can reduce the day-ahead scheduling error and improve the stability of microgrid operation.