Sustainable energy development of biomass-coal co-firing power generation system under ambiguous distribution information

Generating electricity from renewable energy sources can mitigate the constraints posed by finite natural resources and foster the sustainable development of future energy systems. This paper focuses on the design of biomass-coal co-firing power generation (BCPG) system with parameter uncertainties, which requires simultaneous consideration of economic and environmental objectives. However, the optimization process faces two challenges: (i) the trade-off between economic efficiency and environmental sustainability; (ii) the unpredictability of parameters in the system. Addressing these challenges is academically significant for advancing multi-objective robust optimization methodologies in energy systems. Under ambiguous distribution information about greenhouse gas (GHG) emissions, this paper constructs a new bi-objective globalized distributionally robust optimization (GDRO) model. By introducing a moment-based ambiguity set and integrating Lagrangian duality theory with the properties of positive semi-definite matrix, the proposed model can be transformed into a mixed-integer semi-definite programming (MISDP) problem, which can be solved using the Mosek solver. The feasibility and effectiveness of the proposed model are validated through a real case in Shandong Province. Computational results show that compared with the deterministic programming (DP) and distributionally robust optimization (DRO) models, our proposed GDRO model effectively addresses environmental uncertainties while achieving lower GHG emissions with enhanced flexibility and reduced conservatism.