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Energy plays a vital part in stimulating economic progress, and the shift towards a cleaner energy system is highly significant for ensuring the sustainable development of the economy. China's energy structure urgently needs to be transitioned. The fast advancement and implementation of artificial intelligence (AI) has provided a new and important tool for promoting the transition of energy structure. So, what is the relationship between the application of artificial intelligence and the transition of the energy structure? This research introduces artificial intelligence into the energy sector, focusing on the relationship between artificial intelligence and energy transition. Since nonlinear models are better able to study the complex effects and phase differences of artificial intelligence. Using China's provincial panel data spanning from 2006 to 2019, this study employs nonlinear modeling to explore the stage differences in the process of AI in facilitating energy structure transformation. This paper derives the following findings based on empirical research. First, there is a U-shaped relationship between artificial intelligence and the transition of energy structure. Specifically, before the inflection point, the initial application of artificial intelligence, artificial intelligence may adversely impact energy transition. When the inflection point is passed, AI will help facilitate the energy transition. Second, the U-shaped relationship between AI and energy transition is more pronounced in coastal and non-resource-based regions. Third, energy intensity, government investment in science and technology, and informatization will moderate the U-shaped relationship between artificial intelligence and energy transition, changing the steepness of the original U-shaped relationship and even reversing it. Hence, it is imperative to effectively utilize the technological benefits of artificial intelligence through the development patterns and distinctive features of different regions, thereby facilitating the smooth transition of the energy structure. [Display omitted] • The role of artificial intelligence in the energy transition process is studied. • Stage differences in the role of AI are analyzed. • The nonlinear relationship between AI and energy transition is investigated. • Provide insights into the factors affecting the relationship between AI and energy transition. • This research helps the government to advance the energy structure transition. [ABSTRACT FROM AUTHOR]

As part of its energy transition strategy, China has set ambitious targets for increasing the contribution of renewable energy and, in particular, of wind power. However, the Chinese power sector has not undergone the necessary reforms to facilitate the integration and absorption of a larger share of variable renewable energy. This is evident from the difficulties in absorbing wind power from already commissioned wind farms and the resultant curtailment of wind power. Pumped storage hydroelectricity (PSH) is a flexible power source that can facilitate higher penetration levels of wind power as well as complement China’s growing nuclear power capacity. However, regulatory policy constraints have restricted the effective utilization of existing PSH capacity and discouraged investment in new PSH capacity. This paper examines these constraints and assesses the likely impact of new policies designed to address them. Finally, policy recommendations and concluding remarks are provided. This paper contributes to the literature on renewable energy integration from a new perspective. The lessons from China are relevant to other countries going through the energy transition. [ABSTRACT FROM AUTHOR]

[Display omitted] • Clean energy transitions based on the circular economy (CE) are analysed for a town in China. • This could reduce energy use, CO 2 emissions and PM 2.5 emissions compared to the BAU scenario. • COVID pandemic is a new opportunity to introduce circular economy measures. • Circular economy measures could accelerate clean energy transitions. This paper models the energy and emissions scenarios for a circular economy based clean energy transitions in a 140,000-population town in China, taking into account the new situation encountered by the COVID-19 pandemic. The modelled scenarios propose new clean energy transition roadmaps towards a sustainable urban system through the implementation of circular economy strategies. This is represented by the cascading use of industrial excess heat to form symbiosis between factories and to cover the growing building heat demand, as well as by the electrification of the transport sector and reusing the batteries for a second life as energy storage devices. The results show that for a circular economy scenario, during 2020–2040, an accumulated saving of 7.1 Mtoe final energy use (34%), a decline in 14.5 Mt CO 2 emissions (40%) and 592 t PM 2.5 emissions (43%) could be achieved compared with the business-as-usual scenario. The outcomes of the circular economy strategies are at least 7% better than the new policy scenario which simply has energy efficiency improvements. The outbreak of the COVID-19 tremendously impacts the socio-economic activities in the town. If taking the pandemic as an opportunity to enhance the circular economy, by 2040, compared with the scenario without introducing circular economy measures, the extra avoided final energy use, CO 2 emissions and PM 2.5 emissions could be 1.6 Mtoe (8%), 3.8 Mt (11%) and 229 t (17%) respectively. [ABSTRACT FROM AUTHOR]

• Mapped evolution of China's policy mix for sustainable energy transition 1981–2020. • Over time China forms complex policy mix by layering and packaging instruments. • China has increased the diversity and number of policy instruments used. • Rise in charges on emissions and decrease in subsidies for renewables is observed. • Policy experimentation dominates policy instruments used to reduce carbon emissions. Global warming and the acute domestic air pollution in China have necessitated transition to a sustainable energy system away from coal-dominated energy production. Through a systematic review of the national policy documents, this study investigates the policy mix adopted by the Chinese government to facilitate its energy transition and how that policy mix has evolved between 1981 and 2020. The chronological analysis emphasizes two dimensions of temporal changes in the policy mix: (1) changes in the policy intensity and density, and (2) the shift in policy instrument combinations. The policy mix has evolved from a few authority-based instruments to the current response that has a large density of instruments with a good diversity of instrument types. The Chinese government imposes an increasing policy intensity on air pollution abatement and a decreasing policy intensity on renewable energy support, and experiments with innovative policy instruments to reduce carbon dioxide emissions. The evolutionary trajectory features layering new policy instruments, calibrating existing ones and some degree of policy replacement and sequencing. Overall, the study shows that the Chinese government has adopted a complex mix of policy instruments to abate emissions (e.g. carbon dioxide and sulphur dioxide) in the coal-based energy system and to support renewable energy technologies. The study provides an in-depth understanding of Chinese policy design in the environment and energy fields and contributes to the public policy literature by filling a research gap – the comparative lack of empirical analyses on the temporal changes in the policy mixes. [ABSTRACT FROM AUTHOR]