Coordinated Operation of Multi-energy Systems With Uncertainty Couplings in Electricity and Carbon Markets

This paper proposes a distributionally robust optimal operation methodology to coordinate multi-energy interactions and facilitate the emission mitigation for multi-energy systems (MESs) with uncertainty couplings in electricity and carbon markets. A carbon recycling model is proposed to exploit the operational flexibility of multi-energy synergies to enhance economic profits of MES operators under market incentives. Then, a generalized cost model incorporating the lifetime cost of carbon capture and power-to-gas degradation is formulated to provide a quantitative analysis for the coordinated electricity and carbon trading. The co-movements of price fluctuations in electricity and carbon markets are explored through a tailored explainable neural network and uncertainty couplings in the markets are further revealed by a Clayton copula based joint probability distribution (PD) model of price prediction residuals. Moreover, a distributionally robust optimization method is formulated for the optimal coordinated operation of MESs to cope with uncertainties from interrelated fluctuating prices. Numerical studies corroborate the effectiveness and superiority of the proposed methodology in the enhancement of economic and environmental benefits.