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In the context of carbon neutrality, renewable energy, especially wind power, solar PV and hydropower, will become the most important power sources in the future low-carbon power system. Since wind power and solar PV are specifically intermittent and space-heterogeneity, an assessment of renewable energy potential considering the variability of wind power and solar PV with high temporal resolution in different regions will facilitate more accurate identification of the decarbonization pathway of power system. In this paper, the complementary output potential of wind-solar-hydro power every 15 min in 31 Chinese provinces is evaluated by developing a multi-objective optimization model based on Nondominated Sorting Genetic Algorithm II. The results show that the total annual complementary power generation potential in China is 17.57 PWh, of which the three components account for 47.8%, 25.3% and 26.9%, respectively. Inner Mongolia and Tibet are the major renewable energy source provinces with annual complementary power generation potential of 5330 TWh and 3907 TWh, accounting for 30.3% and 13.7% of the total power generation potential, respectively. The temporal potential of wind-solar-hydro power varies greatly, with daily potential is more volatile than monthly. Seasonal and spatial heterogeneity of the complemental renewable potential makes some provinces suffer power shortage during long-hours period especially in winter. Our findings will encourage a higher penetration of renewable energy, the promotion of multi-energy complementarity, and the development of inter-provincial power transmission and energy storage infrastructure in China's future power sector. • A multi-objective wind-solar-hydro complementary optimization model is developed. • Electricity supply and demand have gaps at different temporal and spatial scales. • Wind-solar-hydro complementary potential shows great temporal and spatial variation. • Renewable complementarity can improve China's future power system stability. [ABSTRACT FROM AUTHOR]

Due to the uneven distribution of renewable resources and electricity load centers in China, renewable energy usually needs to be delivered a long distance from the generation base to the load center. However, wind power and photovoltaic (PV) have to be bundled with flexible resources, such as thermal generators, to compensate for the generation uncertainty and variability. Concentrating solar power (CSP) is a controllable generation technology, and it is receiving great attention in the northwest China to be constructed in the 100% renewable energy generation base. This paper proposes a generation portfolio optimization model of a 100% renewable energy base supported by CSP. Firstly, a flexible operation model of CSP based on the interval theory is proposed. Then, a coordinated operation strategy of a 100% renewable energy base organized by CSP, wind power, PV and also energy storage is formulated. On this basis, a generation portfolio optimization model is established with the target of minimizing an extended levelized cost of energy (LCOE) considering the transmission cost. A case study of 100% renewable energy base in Qinghai Province, China, is conducted to verify the effectiveness of the proposed model. It is depicted that CSP plays an important role in the cost-effective portfolio and can be a better alternative to the combination of PV and storage. For the 100% renewable energy base in Qinghai, the LCOE with an optimal CSP, PV, wind, and storage combination is 0.5785 CNY/kWh, which is 20.3% lower than the case without the installation of a CSP station. • Building a 100% renewable energy generation base with a CSP, PV, wind, and storage combination. • A planning model with the target of minimizing an extended LCOE considering transmission cost. • A coordinated operation strategy of a 100% renewable energy base considering CSP's flexibility. • The LCOE of a 100% renewable energy base can drop 20.3% when equipped with CSP in Qinghai. [ABSTRACT FROM AUTHOR]

As a renewable energy, wind power has been improving energy structures and assisting in the maintenance of strategic energy security. Based on provincial level panel data from 2000 to 2018, this paper developed models to evaluate the effects of different policies on newly installed wind power capacity and investigated the market reform influences on wind development in eight spot market pilots. It was found that on a national level, while the pricing and government guideline policies significantly promoted wind power growth, present market reforms were having an opposite effect. The results also suggested that from a resource endowment heterogeneity perspective, there was a significant difference in the wind capacity promotion policy performances. Additionally, of the eight spot market pilots, market designs had led to a significant reduction in new wind power installations in Gansu and Inner Mongolia, and no significant wind power development effects were found in the other pilots. Based on the research results, a discussion on policy use and suggestions on policy improvements are given. • Effectiveness of different representative wind power policies are examined. • The panel models are developed using data that covers 30 provinces over 2000–2018. • Policy effectiveness varies by policy types and wind resource levels. • The current market designs show little impact on wind power development. • Implications on policy use and improvement suggestions are given. [ABSTRACT FROM AUTHOR]

The goal of carbon neutrality provides a new opportunity for the development of renewable energy, especially for wind power. In this paper, 11 regional climate models (RCMs) including CORDEX-EA and PRECIS at two different resolutions are used to evaluate the performance in simulating the spatio-temporal characteristics for wind speed and energy potential from 1981 to 2005. The results show that most models can reproduce the spatio-temporal patterns, and the simulation of the eastern region is better than that of the western region. Besides, most of the higher-resolution models had better simulation performance for spatial-temporal patterns and inter-annual variation. Then, the weighted multi-model ensemble is used to project the changes of the wind speed and the wind power density over China's mainland during the mid-21st century under the RCP8.5 scenario. In future, a decrease in wind speed is projected by most RCMs over China, although some regions, such as the southern parts of China, are projected to have more wind energy potential. The percentage variation of annual mean wind speed will remain in the range of ±4%. The wind power density will decrease in the north and the largest decrease will be found in the northwest. However, the annual mean wind power density in the southeast China will have an increase of 2.21% in the middle of this century. The inter-annual variation of the wind power density in most regions will increase by more than 20%. However, intra-annual variation in the wind power density is likely to decrease in most regions of China, ranging from about −20% to −50%. • A weighted multi-model ensemble was used to project the changes of wind power density over China. • The changes of annual mean wind power density vary in different sub-regions of China, ranging from −3.21% to 2.21%. • The inter-annual variation of the WPD in most regions will increase by more than 20%. [ABSTRACT FROM AUTHOR]

Renewable energy (RE) trade disputes have been rising in response to certain green industrial policies, i.e., policy mechanisms used to develop domestic RE industries and accrue associated local economic benefits. Since 2011, countries have been increasingly filing trade litigations to counter the use of green industrial policies by their trading partners so that they can expand RE industry competitiveness and the associated manufacturing jobs within their own countries. However, in the absence of systematic studies on the impacts of RE trade duties, evidence regarding their success in achieving these economic goals remains limited. In this paper, the effectiveness of RE trade duties in supporting employment, especially in manufacturing, is assessed. First, the literature on the motivations behind RE trade duties is reviewed, and then the case of trade duties imposed by the US on the imports of solar and wind energy components from China between 2011 and 2019 is examined. Although several factors may drive employment, no evidence is found for the increase in jobs in solar and wind manufacturing in the years after the trade duties were imposed. Meanwhile, downstream jobs in installation, operation and maintenance continued to grow, corresponding to increases in annual installation of solar and wind capacity in the US. These were driven by policy incentives and the declining costs of solar and wind technologies. Overall, this case study highlights the broader implication that trade duties alone are unlikely to promote local manufacturing industries, and countries would benefit from other well-designed policies. • Renewable energy (RE) related trade disputes rising but studies examining effectiveness of trade duties limited. • Literature on the goals behind trade duties on RE components reviewed. • A framework developed to assess the relationship between RE trade duties and manufacturing employment. • Framework applied to examine the case of trade duties by the US on the imports of solar and wind energy components from China. • Trade duties not effective to develop local RE industries; other well-designed policies needed to increase local RE manufacturing jobs. [ABSTRACT FROM AUTHOR]

In order to mitigate global climate change and air pollution, the Chinese government has assigned high priority to expanding low-carbon power generation in China. Recent studies have shown that wind power is one of the most promising renewable energy option in China. Although many studies have estimated the generation potential of onshore wind power, their results vary widely from 1783 TWh to 39,000 TWh. Therefore, we examine the different assumptions in these papers and identify three main factors influencing the results. The three influencing factors are: weather data set, land utilisation factor, and wind turbine configuration. For our model-based analysis, we define a reference scenario which is used to compare the results. Our analysis shows using a different weather data set increases the generation potential to roughly 35,000 TWh. This is 54% higher than the generation potential of the reference scenario. The land utilisation factor also has a large influence, ranging between −10% and −51%. The studies' assumptions and data should be subjected to careful scrutiny, as the calculated wind power potentials are widely used to develop decarbonisation strategies for the energy system. • Study results on wind power potentials in China vary from 1783 TWh to 39,000 TWh • Influencing factors: weather data set, land utilisation, and wind turbine configuration. • Model-based sensitivity analysis with nine scenario settings. • Chosen weather data set has the highest impact on the calculated results with a variation of 54%. [ABSTRACT FROM AUTHOR]