Multi-level coordinated energy management for energy hub in hybrid markets with distributionally robust scheduling

Maintaining energy balance and economical operation is significant for multi-energy systems such as the hub. However, it usually challenged by frequently changing unpredictable uncertainties at different timescales. Under this scope, paper investigates coordinated management problem day-ahead intra-day conditions considering of source-load market prices concurrently. Note that precise knowledge distributions about may be unaccessible before decision-making in phase. A two-stage chance-constrained model based on distributionally robust approach with ambiguous moment information proposed to immunize scheduling strategies against worst-case probability distributions. The first stage dedicated obtaining more arbitrage flexibility optimizing bidding power, natural gas carbon markets. second focuses optimization expected cost. It provides a equipment load strategy reference subsequent arrangements. With respect variations electrical thermal components, an two-timescale coordination implemented step step. re-dispatched circularly minimize penalty costs. possible imbalance also compensated way. As program nonlinear, multi-stage, linearization dual transformation techniques are designed enhance tractability programs. Experimental results show developed multi-level framework emission decrease 37%, reduces cost averagely 3% compared corresponding contrasting cases. obtained validates good tradeoff between robustness optimality.