Multi-objective distributionally robust optimization for hydrogen-involved total renewable energy CCHP planning under source-load uncertainties

Hydrogen is one type of clean renewable energy. By introducing hydrogen production, storage and conversion devices into the combined cooling, heating and power (CCHP) system to replace its fossil fuel components, the hydrogen-involved total renewable energy CCHP (H-RE-CCHP) system is formed, thus bringing an effective way to promote energy transition towards low carbon. However, the conflict between economy and environment, and interference of source-load uncertainties hinder the low-cost construction as well as economic, stable, and lowcarbon operation of H-RE-CCHP. In view of this, this paper proposes a multi-objective distributionally robust optimization (DRO) model for H-RE-CCHP planning. Firstly, a moment-based ambiguity set is constructed to define the possible range for the joint distribution of solar irradiation and multiple loads. Secondly, considering the worst-case distribution within the ambiguity set, the economic and environmental objective functions are presented for minimizing system construction, maintenance and operation costs while reducing carbon emission. Furthermore, the sizing- and operation-related constraints are formulated according to such principles as maintaining multi-energy balance when the forecasting errors of uncertainties occur. Finally, by applying strong duality and augmented epsilon-constraint for model solving, Pareto optimal solution set is obtained, and from which final planning and operation scheme is selected according to decision preference and interactions between objectives. Simulations mainly verify: 1) due to considering multiple objectives, H-RE-CCHP planning and operation reach the reasonable trade-off between economy and environment, that is, carbon emission/economic cost can be reduced by 99.81 %/66.70 % comparing with single economic/environmental objective; 2) with applying DRO in resisting uncertainties, 100 % renewable energy accommodation is achieved while meeting stable H-RECCHP operation; etc. Accordingly, this paper provides an effective approach for renewable energy system planning, thus contributing to the low carbon development of economic society.

Automated summary

This paper proposes a multi-objective distributionally robust optimization (DRO) model for H-RE-CCHP planning. By considering economic and environmental objectives, as well as resisting uncertainties, a balance between economy and environment is achieved, promoting the transition towards low carbon energy.