Multi-objective optimization of regional power generation mix considering both carbon cap-and-trade mechanisms and renewable portfolio standards

The optimization of regional power generation mix is important to achieve the carbon peaking and neutrality goals. This study proposes a multi-objective optimization model for regional long-term electricity system planning considering both the carbon cap-and-trade mechanisms and renewable portfolio standards. Baseline scenario, strict policy scenario and loose policy scenario are designed to compare the optimization results of power generation mix. Furthermore, a green transformation comprehensive index (GTCI) is proposed to evaluate the effect of green transformation in power sector. The case study of Guangdong province in China is conducted, and the results indicate that, in the baseline scenario, the share of renewable energy generation would reach to 34.97 % in 2035, and the carbon emission would peak in 2030; in the strict policy scenario, the share of renewable energy generation would reach to 37.28 % in 2035, and the carbon emission would peak in 2025; in the loose policy scenario, the share of renewable energy generation would reach to 33.05 % in 2035, and the carbon emission would peak after 2035; the value of GTCI reflects that the power system of Guangdong province has good trend of green transformation. This study could support important reference for the power system transformation at regional level.