An inexact fuzzy chance-constrained fractional programming model is developed and applied to the planning of electric power systems management under uncertainty. An electric power system management system involves several processes with socioeconomic and environmental influenced. Due to the multiobjective, multilayer and multiperiod features, associated with these various factors and their interactions extensive uncertainties, may exist in the study system. As an extension of the existing fractional programming approach, the inexact fuzzy chance-constrained fractional programming can explicitly address system uncertainties with complex presentations. The approach can not only deal with multiple uncertainties presented as random variables, fuzzy sets, interval values, and their combinations but also reflect the tradeoff in conflicting objectives between greenhouse gas mitigation and system economic profit. Different from using least-cost models, a more sustainable management approach is to maximize the ratio between clean energy power generation and system cost. Results of the case study indicate that useful solutions for planning electric power systems management practices can be generated.

In order to peak emissions before 2030 and to achieve the net‐zero ambition around 2060, China urgently needs to accelerate low‐carbon transition, especially in the power system. Previous studies were mainly focused on deterministic optimization, with some of them being followed by sensitivity analyses. To tackle the gaps and to support the net‐zero ambition, this study develops a multi‐region power system risk management (MPRM) model to analyze composite effects of renewable energy development and inter‐regional electricity transmission under uncertainties, and their combinations to achieve carbon neutrality by 2060. In detail, MPRM can (a) reveal the downward trend in costs of renewable energy and the increasing in inter‐regional electricity transmission; (b) tackle the uncertainties expressed as intervals; (c) support the low‐carbon transition of the power system. Under the renewable‐dominated power structure, 90% of China's electricity demands can be derived from non‐fossil sources by 2060. Inter‐regional electricity transmission will continue to expand due to the dramatic decreases in the costs of renewables and fast‐growing demands for electricity. Northwest and east regions will be the main exporter and importer of renewable electricity. Carbon emissions from power system will peak in 2030 (about 6.21% above the 2020 level) and be eliminated by 96% (of 2030 levels) by 2060. These results can provide support for expansion of renewable capacities, acceleration of low‐carbon transition in power structure, elimination of barriers in electricity trading across regions, and exploration of the trade‐off between system costs and risk.

This study is intended to investigate the relation of China's economy expansion and renewable energy output. Expressing electricity production using renewable resources as the growth rate of renewable energy electricity output by category and the growth rate of renewable energy share, while denoting economic growth as GDP growth rate and electricity consumption per unit of GDP, the research examined the panel data from 2002 to 2020 with OLS model, and the robustness tests and heterogeneity analysis were completed. Research finds that China's renewable energy generation growth has a two-way relationship with economic growth. For heterogeneity analysis, the panel data of province GDP growth and electricity generation growth rates were used. The findings suggest that the classification criteria for provinces or the control factors that affect the findings need to be improved and taken into account. The finding shows that under the precondition that developing countries' rising energy usage benefits their economies' progress, optimizing the energy structure and promoting green transformation and sustainable development will both temporarily and permanently aid in the economy’s development.