Distributionally Robust Optimal Bidding of Energy Hubs in the Joint Electricity and Carbon Market

Abstract

To realize the lower carbon and more efficient operation of energy hubs in the joint electricity and carbon market, a day-ahead bidding strategy is proposed for the energy hub operator (EHO). Considering the uncertainties of prices, demands, and renewable energy sources, this strategy is formulated as a novel two-stage distributionally robust joint chance-constrained optimization problem. A total distance-based ambiguity set is proposed to preserve the mean value of uncertain factors. By introducing this indicator function, this problem is further reformulated as a mixed-integer linear programming (MILP) problem. Simulations are performed based on the electricity and carbon prices in Europe, and the relation between the carbon emission and operational cost is further investigated in the case studies.