Multi-objective carbon neutrality optimization and G1-EW-TOPSIS assessment for renewable energy transition

Abstract

Successful low-carbon energy systems rely on good economic, environmental and energy efficiency indicators. Yet, the current energy structure has shortcomings in these aspects, hence the need to develop the renewable energy transition. This study proposes a three-phase dynamic energy planning framework based on multi-objective optimization, assessment and analysis. The optimization phase utilizes the NSGA-II to determine the optimal allocation of multiple energy sources by considering various variables and constraints. A comprehensive assessment system combining the G1 method and the entropy weight method is proposed, and the TOPSIS method is used to evaluate the rationality and superiority of the energy structure. The relative trends in electricity consumption and renewable energy penetration are also analyzed in order to predict CO2 emissions. The dynamic framework and comprehensive assessment are applicable to Guangdong Province. Results reveal that Guangdong province should prioritize the development of offshore wind power, ensure the stability of the power grid by steadily developing hydropower and nuclear power, and vigorously develop solar power at the end of the planning period. Guangdong Province can reach carbon peaking around 2028 and net zero carbon emissions by 2060, leading to carbon neutrality. The optimized dynamic energy planning framework can provide effective decision support to promote the transformation of regional energy structures.