Chinese Wind Power Research Articles

A wedge or a weight? The effect of policy on the productive efficiency of the Chinese wind power industry

Promoting wind power is at the top of the government's agenda in China because of the cleanliness and sustainability of this power source. Improving the productive efficiency of the wind power industry (WPI) is crucial to accelerating the transformation of China's energy structure. Yet the question remains whether policies can effectively stimulate the productive efficiency of the WPI. Using microdata from listed Chinese wind power enterprises from 2006 to 2019, we measure the productive efficiency of these enterprises and then assess the effect of policy on this efficiency. The results show that between 2006 and 2019, the Chinese WPI is inefficient. The average productive efficiency of enterprises in eastern China is 0.164, higher than that of enterprises in central and western China (0.129). Moreover, there is a significant negative correlation between economic policy and the productive efficiency of enterprises. Soft policy is positively related to productive efficiency, whereas the effect of regulatory policy is not statistically significant.

Can wind power policies effectively improve the productive efficiency of Chinese wind power industry?

ABSTRACT Due to the advantages of technical maturity, economic benefits and development potential, wind power is highly expected by China. In order to accelerate the development of wind power industry (WPI), the Chinese government has formulated a variety of preferential policies. Yet can policies effectively improve the productive efficiency of Chinese WPI has not been fully answered so far. Based on the micro-data of Chinese wind power listed enterprises from 2006 to 2019, this paper assesses the productive efficiency of enterprises in different links of wind power industry chain (WPIC) with DEA model. And then the fixed effect regression model is employed to identify the effect of policy on productive efficiency. The results show that, in the sample period, the overall productive efficiency of WPI is relatively low. The productive efficiency of upstream enterprises is the highest (19.8%), while that of downstream enterprises is the lowest (12.9%). And productive efficiency of midstream enterprises is 15.8%. Besides, the economic policy significantly inhibits the productive efficiency of WPI. The soft policy is an effective macro-control measure to improve the productive efficiency. And the effect of regulatory policy is time-dependent. Then the suggestions are provided.

Bridging energy and metal sustainability: Insights from China’s wind power development up to 2050

Concerns over anthropogenic climate change and sustainable development motivate rapid expansion of renewable energy in China. This paper explores metal demand caused by projected wind power developments in China up to 2050. Dynamic material flow analysis is combined with explorative energy scenarios to evaluate induced demand of base metals (copper, steel, aluminum, nickel) and rare earth elements (neodymium and dysprosium). The results indicate that annual demand of base metals for Chinese wind power is up to 12 times larger in 2050 than in 2018, and the cumulative demand is up to 23 times larger. Copper and nickel show greater supply pressure than aluminum and steel in the wind power sector. Cumulative copper and nickel demand of wind power sector are 9–11.9 Mt and 2.1–2.8 Mt respectively, which corresponds to 35–45.9% of copper reserves and 74–101% of nickel reserves in China. For rare earth elements demand, more than 18-fold increases are expected for annual demand in 2050 compared with 2020, and cumulative demand of neodymium and dysprosium are 1.6–3.3% and 1.4–2.8% of their reserves respectively. Recycling will play an important role after 2050 as a secondary supply of metal for Chinese wind power, and lacks noteworthy impacts on short-term future outlooks.

Resource misallocation in the Chinese wind power industry: The role of feed-in tariff policy

This article analyzes resource misallocation in the Chinese wind power industry by examining wind power development in relation to implementation of feed-in tariff (FIT), an electricity price subsidy policy. We construct a plant-level dataset to explore the extent of distortions exacerbating resource misallocation in the wind power industry from 2000 through 2013. Our results show that distortions have been exacerbated since 2009, when the Chinese government implemented FIT, and that the potential production improvement of the wind power industry was relatively high after 2009. FIT provides added incentives for low-productivity plants to enter the industry, especially in regions better endowed with resources. This suggests that the increased distortion in resource allocation of most wind power plants is largely due to government subsidies. In addition, higher FIT rates significantly lower average capital productivity of wind power plants while having no significant effect on average labor productivity. Plants with better production technologies face worse growth rates in the region most richly endowed with relevant resources and there is no significant difference in these productivity impacts between new and already existing power plants. We postulate that similar relationships between subsidies and efficiency are likely to occur in other renewable energy sectors receiving government subsidies.

The evolution of a collaboration network and its impact on innovation performance under the background of government-funded support: an empirical study in the Chinese wind power sector.

To accelerate the transformation and application of basic research results, the Chinese government has repeatedly mentioned in a government work report that it is necessary to support research and innovation collaborations between knowledge research institutions and enterprises. However, few studies have focused on the evolution of collaborations between these organizations and the impact of collaborations on innovation performance (IP) in the field of renewable energy under the background of government-funded support (GFS). Based on scientific publications, we construct a GFS collaboration network in the wind power field to investigate the evolution of network structure characteristics, attribute proximity variables, and applied research collaboration (ARC), and we study the impact of network evolution on the IP of actors. The results show that the focal actor of the collaboration network prefers to engage in ARC with partners who are familiar and have the same knowledge base in different provinces. This collaboration tendency will reduce geographical proximity and increase the direct ties, indirect ties, technological proximity, and ARC of the ego network. Among them, direct ties have an inverted U-shaped effect on IP, geographical proximity has a significantly negative impact on IP, and the remaining variables have positive impacts on IP. Taken together, when the direct ties is within a certain range, these collaboration tendencies in a GFS collaboration network positively affect the IP of research institutions and enterprises.

Research on Investment Benefit Evaluation Technology of Wind Power Project

Wind power projects have high investment costs and long payback periods, so comprehensive investment returns and wind power project assessments are essential. Based on the current status and development trends of Chinese wind power projects, this paper builds an index system and model for evaluating the investment benefits of wind power projects based on TOPSIS theory. The research results can provide reference and guidance for the comprehensive evaluation of investment benefits of wind power projects.

Functional clustering analysis of Chinese provincial wind power generation

China is a broad territory country. There are significant differences in the terrain, climate, and other environmental factors between different provinces, which affect wind power generation. In order to better analyze the situation of wind power generation in Chinese provinces, this paper uses the functional clustering analysis to classify the monthly data of wind power generation in 30 Chinese provinces from March 2013 to October 2019. The empirical results of this paper show that the wind energy generation in Chinese provinces can be divided into three categories, and the results are consistent with the actual situation. In this paper, functional clustering analysis is used to analyze monthly data, compared with the traditional clustering analysis to analyze annual data which are obtained by accumulated monthly data. Higher-dimensional data can be used for analysis to reduce information loss. Moreover, data can be viewed as functions, and more information can be mined by analyzing derivative functions, and so on. The analysis of wind energy generation has certain guiding significance for the development and utilization of renewable energy.

Are government subsidies effective in improving innovation efficiency? Based on the research of China's wind power industry

China's wind power industry has rapidly developed and the level of technological innovation has been improved greatly with the government's funding support. However, few studies have considered whether government subsidies are effective in improving the innovation performance of Chinese wind power industry. To answer the above problem, this paper uses the sample data of listed wind power enterprises from 2012 to 2018 to evaluate the innovation efficiency of Chinese wind power industry. We employ a stochastic frontier model based on the translog production function, analyze the impact of government subsidies and other enterprise characteristics on innovation efficiency. Our results show that, first, the innovation efficiency of China's wind power industry is relatively low, but the overall trend is upward. Second, in the long term, there is a U-shaped relationship between government subsidies and innovation efficiency, reducing government subsidies can improve innovation efficiency before the turning point. Third, the effect of ownership concentration and financial leverage is not significant, but employees' high quality and high profitability play a significantly positive role in improving the innovation efficiency of China's wind power industry. The conclusions also provide a reference to policy making for the sustainable development of Chinese wind power industry.

Effect of innovation policy mix on innovation efficiency: Evidence from Chinese wind power industry chain

Abstract Wind power (WP) is a long-term strategic energy alternative for China to cope with energy shortage and environmental crisis. Yet, how innovation policies precisely affect innovation efficiency (IE) of WP industry remains poorly understood. Therefore, based on the micro-data of Chinese WP-listed companies, this article measures the IE of enterprises in different links of wind power industry chain (WPIC), and discusses the effects of innovation policy and its mix on IE. The results show that there exists non-efficiency problems in Chinese WP industry during 2014–7, but the innovation of enterprises in the upstream of WPIC is DEA efficient. IE of enterprises in the midstream presents a U-shape, which fluctuates periodically in downstream. In addition, neither a single policy nor a policy mix has a significant impact on IE of enterprises in the upstream and midstream of WPIC, but has a significant negative effect on that of the downstream.

Review on China’s wind power policy (1986–2017)

As an important renewable energy source, wind power plays a key role in mitigating climate change and has become one of the fastest growing clean energies globally. In China, wind energy development has been a vital component of national energy transformation strategy. Over the years, the Chinese government has introduced a series of policies to promote the development of wind power and also to regulate this emerging industry. Base on examining all the key policy documents on wind power issued by the Chinese government over the last 30years, we find that China has built up a comprehensive policy system, and summarized the current framework of Chinese wind power policy systematically. Then, we analyze the policy objectives, policy tools, major measures, their results in each development stage, and the characteristics and trends of China's wind power policies. Finally, we discuss the limitations of the current policy and put forward corresponding suggestions.

Impact of substantial wind farms on the local and regional atmospheric boundary layer: Case study of Zhangbei wind power base in China

The environment-friendly development of wind power is complicated as the atmospheric impacts of wind farms are difficult to measure. Wind power has made contributions to emission reduction, but it is undeniable that the substantial wind farms (SWFs) have had a non-negligible impact on the local ABL. This paper aims to provide a reliable methodological scheme and practical data for human beings to objectively understand the development of wind power. Based on the data from one of the Chinese gigawatt-scale wind power bases in Zhangbei County of Hebei Province, the mesoscale simulations were conducted to explore the impacts of substantial wind farms on the local and regional atmosphere. The results show that: (i) the impact of substantial wind farms on the local area is significant and sustained, while this impact on the regional area is slight and occasional; (ii) it can bring about the seasonal and diurnal differences in the local ABL property; (iii) it can not only induce the horizontal turbulence directly caused by wind turbine wake flow, but also produce the vertical mixing in the near-surface ABL. A systematic analysis of wind power potential and its atmospheric impact is urgent to ensure sustainable development of wind power.

Achieving grid parity of wind power in China – Present levelized cost of electricity and future evolution

China has adopted an ambitious plan for wind power to achieve grid parity with the on-grid price of coal-fired power in 2020. Whether this target can be achieved is a great concern for policy makers as well as potential investors. To address this issue, we first estimate the future levelized cost of electricity (LCOE) of wind power using a learning curve method, and then determine whether grid parity can be achieved by comparing it with the on-grid price of coal-fired power. Specially, the effect of carbon pricing on the grid-parity is explored, and a sensitivity analysis on how the discount rates, learning rates, and curtailment rates affect grid parity is conducted. The learning rate of onshore wind power is estimated using a panel dataset consisting of information of 2059 onshore wind projects in China from 2006 to 2015. Based on this learning rate, the future LCOE of Chinese onshore wind power from 2016 to 2025 is calculated. The results show that the LCOE of onshore wind power decreases by 13.91% from 0.40 RMB/kWh in 2016 to 0.34 RMB/kWh in 2025. By comparing the LCOE with the on-grid price of coal-fired power, the grid parity of onshore wind power may be achieved in 2019. With the implementation of the carbon pricing policy, the grid parity will be achieved earlier. More specifically, with the carbon price reaching 10, 35, and 60 RMB/t CO2, the grid parity can be achieved in 2019, 2017, and 2016, respectively. The results of the sensitivity analysis show that in the case of high discount rates, low learning rates, high curtailment rates, high O&M cost and low capacity factor, the grid parity will be delayed, and a high carbon price will be required to achieve the grid parity.

An Anatomy of Mishaps – China's Wind Power Development

China has in recent decades expanded its wind power generation capacity and become the world leader. Still, despite robust government support, wind power in China is obstructed by various barriers (e.g. quality deficiencies, inability to export, missing grid connections, and permit delays from central government for grid construction etc.). This paper synthesises the literature that has discovered weaknesses in the Chinese wind power development and suggests improvements. One observation is that when the Chinese government sets command-andcontrol construction targets over new installed capacity, actors delivered to target – but with several power plants without grid connectivity and severe quality problems. The article contributes to the academic debate over the role of policy making in renewable energy development and argues that China should improve their incentive structure and coordination of regulations.

When socialists marketize: the case of China’s wind power market sector

ABSTRACTThis paper analyzes China’s attempt at maintaining and stabilizing the market framing of wind power development as ‘sustainable.’ Drawing on mixed data and new directions in the social studies of marketization, the analysis focuses on the Chinese government’s responses to the ‘quality crisis’ in the wind turbine industry. Employing five types of framing – goods, marketizing agencies, market encounters, price-setting, and market design and maintenance – the paper sheds light on flexible government interventions to steer the socio-technical assemblage around wind power towards a ‘turn to quality.’ In essence, this is a study of market construction in the context of Chinese wind power experiments. The paper contributes to new directions in market studies by (1) demonstrating the importance of attending to the contested algorithmic transformation of wind resources to wind power; (2) taking market studies to a transitional and developmental context, which renders marketization prone to constant overflowing; and (3) elucidating a particular Chinese model of experimental market construction ‘through embracing overflowing.’ The paper proposes new trajectories for future market studies with a focus on non-Western contexts, to reveal the wide variety of how marketization unfolds.

Corrigendum to “Quantitative Entropy Weight TOPSIS Evaluation of Sustainable Chinese Wind Power Developments”

Corrigendum to “Quantitative Entropy Weight TOPSIS Evaluation of Sustainable Chinese Wind Power Developments”

From feed-in tariff to renewable portfolio standards: An evolutionary game theory perspective

China is experiencing renewable energy support schemes evolution from feed-in tariff (FIT) to renewable portfolio standards (RPS) scheme, which can be significantly influenced by renewable and conventional electricity producers strategies. This paper applies evolutionary game theory and system dynamics (SD) model to examine electricity producers strategies in this scheme context. We utilize the data from Chinese wind power industry for simulation to represent evolution of strategies, and research impacts of scheme parameters (subsidy, quota, and fine) on electricity producers and tradable green certificate (TGC) market operation. The results show that, to ensure all the electricity producers willing to trade TGC, scheme parameters should be within a reasonable range. Moreover, the stage descent mode of subsidy and higher level of fine will help the electricity producers accept the RPS scheme as soon as possible and promote the scale of TGC transaction, but the quota requirement should be avoided too low. At the end of the paper, policy implications are offered as references for the government.

Quantitative Entropy Weight TOPSIS Evaluation of Sustainable Chinese Wind Power Developments

Based on a Driving Forces-Pressure-State-Impact-Response (DPSIR) model, this paper takes a macroenvironmental, socioeconomic perspective to build an evaluation model to address sustainable Chinese wind power developments and to quantize the development results. From a combination of entropy weight and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, the sustainable wind power development level in China is examined, the development trends analyzed, and the trends and underlying laws identified, all of which provides new information for Chinese wind power sustainability. It was found that Chinese sustainable socioeconomic wind power development has been growing year on year. However, the wind power ecological sustainability fell and then rose slowly, indicating that these subsystems both influence the sustainable development of wind power.

The Impacts of Chinese Wind Farms on Climate

AbstractAs a renewable energy resource, wind energy has developed fast in recent years, and its impacts on climate have received widespread attention. In this study, a new wind farm fleet scenario is designed based on Chinese wind farm data from the Chinese Wind Energy Association and Chinese cumulative wind power capacity data from the Global Wind Energy Council. A mesoscale numerical model is used to simulate the impacts of wind farms on climate. The results indicate that the wind farms in the designed scenario could impact the local and regional climate in China, causing changes in both lower‐level atmosphere (changes within ±0.5 K for 2‐m temperature) and upper‐level atmosphere (changes within ±30 m2/s2 for 500‐hPa geopotential height) over several specific areas. The momentum sink and the turbulent kinetic energy source generated by wind farms are first separated to evaluate their respective contributions to the impacts of wind farms on climate.

Gone with the wind: A learning curve analysis of China's wind power industry

This study examines how accumulation of experience and knowledge by wind farm developers and turbine manufacturers contributed to productivity gains in China's wind power industry during its rapid expansion phase between 2005 and 2012. A learning curve analysis is conducted on an original dataset of 312 Chinese wind farms under the Clean Development Mechanism. A key strength of the dataset is that it includes data on actual, wind-farm level power generation. The analysis, based on third-party verified data, reveals that the experience and knowledge accumulation did not result in improvements in generation performance, turbine size, or unit turbine costs of Chinese wind farms. Rather, generation performance was driven by capital investments (i.e., larger and more expensive wind farms performed better). Turbine cost reductions were achieved by intense price competition which hampered investments in technology improvement and quality assurance. The Chinese wind power case demonstrates how market expansion, in the absence of carefully designed innovation policies that complement deployment policies, does not necessarily lead to technological learning. Fostering the technological capability of local industry can take a long time. When scale-up happens quickly, it is crucial to develop and refine local technological capability.

Sustainable operation-oriented investment risk evaluation and optimization for renewable energy project: a case study of wind power in China

Renewable energy is playing an increasingly important role in energy security and environmental protection. As China has a huge demand for renewable energy and also has abundant wind resources, it is vital that government, investors and operators work together to ensure the sustainable development of the wind energy industry. Even though China is already a leader in wind power generation with the largest installed wind power capacity in the world, it has continued to build new wind power facilities. However, due to industrial immaturity and the need for significant investment, wind power investors and operators are faced with uncertainty about the attendant risks. To achieve risk mitigation and sustainability, this paper proposes an investment risk evaluation and optimization process for Chinese wind power projects. The Monte Carlo method is first used to evaluate the investment risks, after which a multi-objective programming model is built for the optimization. A specific case in western China is examined to demonstrate the proposed methodology, with the evaluation results indicating that the project has high investment risk. Based on the case study, the key risk factors are identified and optimization suggestions given for China’s wind power projects. The proposed methodology and findings contribute to research on the planning, investment and sustainable operation of renewable energy power generation projects in other areas in China.