An indeterministic fractional two-stage inter-regional energy system optimization model: A case study for the Province of Shanxi, China

The inter-regional power trade inevitably leads to transmissions of carbon and air pollutant emissions (CAEs), which is unfair for energy-dependent regions. Therefore, this study develops an indeterministic fractional two-stage inter-regional energy system (IFTS-IRES) optimization model for planning the energy system in Shanxi Province. The developed model can deal with uncertain parameters expressed as interval values and modify the pre-made policies, which could be an effective method to solve multi-objective optimization problems. Multiple mitigation-policy scenarios are analyzed based on imposing CAEs compensation taxes on electricity consumption regions (ECRs), adjusting renewable energy power targets, and upgrading traditional power plants with carbon capture and storage technology (CCS). The comparison results show that IFTS-IRES is able to detailly reflect the tradeoff between economic development and environmental protection, and the maximal amount of CO2 mitigation will be [1.80, 3.34] K tonne/million RMB. By 2040, wind and biomass would account for [24.55%, 29.02%] and [33.38%, 35.48%] of the power generation capacity, and renewable energy will gradually substitute traditional fossil fuels. Therefore, Shanxi's power system should develop renewable energy rather than upgrade with CCS to realize the goal of carbon peak and carbon neutrality. In addition, the future electricity export will keep increasing, among which the share of wind and biomass power will be [50.86%, 51.69%] and [21.25%, 21.78%]. It is suggested that the mitigation responsibility of inter-regional CAEs should be shouldered by ECRs through paying for compensation taxes. These findings could help decision makers analyze economic and environmental effects with multiple objectives under uncertainties. It provides new insight into regulating the mitigation responsibility existing in inter-regional power transmission grid. The developed model is expected to be applied to other regions heavily dependent on energy resources.