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In the context of carbon neutrality target, renewable energy sources have been transforming from "supplementary energy" to "main energy", which have promoted the green and low-carbon transition of global energy supply system. In-depth analyzing the spatial patterns and driving mechanisms of renewable energy expansion are of significance for optimizing the spatial layout of clean power, and avoiding the phenomenon of wind and solar power curtailment. In this paper, we proposed an ensemble learning model to examine the nonlinear effects of physical geography, resource endowment, and socio-economic factors on solar photovoltaic (PV) capacity at the prefecture-level city scale in China. Using the city-level multi-sources geospatial big data, we extensively collected a total of 175 related explanatory variables and cumulative installed capacity of solar PV power for 295 prefecture-level cities of China. The recursive feature elimination algorithm (SVM-REF) is firstly used to extract the optimal feature subset of urban PV capacity from multi-dimensional features variables. Furthermore, three advanced machine learning models (random forest, decision tree, extreme gradient boosting) are developed to identify the key influencing factors and nonlinear driving effect of urban solar PV power expansion in China. The results show that China's PV installation capacity is highly concentrated in Northern and Northwest parts of China, with the occupancy over 70% in 2019. Moreover, the XGBoost model has the best prediction accuracy (R2 = 0.97) among three methods. We also found that total amount of urban water resources, average solar radiation, and population density are the most important controlling factors for urban solar PV capacity expansion in China, with contribution of 35.6%, 17.7%, and 13.3%, respectively. We suggested that urban solar PV layout mode in China is recommended to gradually shift from resource orientation to the "resource-environment-demand" comprehensive orientation. The paper provides a replicable, scalable machine learning models for simulating solar PV power capacity at the prefecture-level city scale, and serves as a motivation for decision-making reference of the macro siting optimization and sustainable development of China's green power industry. • This study examines the impact of high-dimensional features variables on urban solar energy development. • Over 70% of solar PV installation capacity is concentrated in Northern and Northwest parts of China. • Water resources, solar radiation, population density have significant impact on solar PV distribution. • Solar PV distribution in China should shift from resource orientation to the comprehensive orientation. [ABSTRACT FROM AUTHOR]

Abstract Currently, wind and solar energy have not been well utilized in China, and the rate of abandoned wind and solar facilities in China is increasing annually. Renewable portfolio standards (RPS) are an effective system for promoting large-scale renewable energy integration and consumption and realizing the goal of renewable energy development. To clarify the interactive relationship between the different levels and multiple actors in RPS, this paper uses policy network theory to analyze the interactive relationship of stakeholders from the three aspects of network subject, network structure and network interaction. The policy network of the RPS consists of the policy community, professional network, intergovernmental network, producer network and issue network. Under the RPS, to meet their own needs, participants affect the formulation and implementation of the RPS through the actions of confrontation, alliance, competition and cooperation. In different stages of developing the RPS, the openness and integration of policy networks change accordingly. This study overcomes the limitations of past simple analyses of the actor relationship in the policy process and thereby offers certain reference significance. Highlights • The actors of RPS policy networks are analyzed. • This paper analyze the game relationship of the stakeholders from three aspects. • This research reveals the network relationship between multiple stakeholders. • This study breaks through the limitations of past analysis of actor relationship. [ABSTRACT FROM AUTHOR]

China and the United States are both major countries in the world in the production of and trade in wind energy products, and they are also important trading partners. Therefore, it is of great practical significance to analyze and evaluate the Sino-US bilateral wind power complementarity for re-examining their respective comparative advantages and re-understanding the benefits that trade liberalization brings to both countries, in an attempt to strengthen the trade relations between China and the United States and enhance trade complementarities in wind energy products under the global circumstances of fierce competition. In this paper, based on the trade data from the UN Comtrade database in 2007-2016, a quantitative analysis was conducted on the complementarity of Sino-US wind energy products, by adopting the quantitative research methods of trade combination degree index (TCD), export similarity index (SI) and trade complementarity index (TCI). The results shows that: i) the total trade volume of wind energy products between China and the United States has increased rapidly, and the trade surplus between China and the United States has been expanding year by year; ii) the overall trade balance of wind energy products trade between the two countries is generally stable, and the dependence of China's wind energy products on the United States is much higher than that of the U.S wind energy products on China; iii) the Sino-US wind energy products between China and the United States are highly competitive in the international market; iv) Sino-US wind energy products have different degrees of complementarity in bilateral trade. Finally, this paper proposed policy implications based on the findings of this study. [ABSTRACT FROM AUTHOR]

• An energy storage value estimation model in monopoly power markets is put forward. • Ancillary services model in the monopolized electricity market is proposed. • A novel value-drive policy is introduced and compared with two other mechanisms. • Energy storage value under different energy storage configurations is analyzed. Recent trend in increasing the penetration level of renewable energy challenges safety and stability of the power grid. Electrical energy storage (EES) has been deemed as one of the key elements needed to mitigate the fluctuant and intermittent nature of renewables, and is undergoing rapid development nowadays. However, there are still many questions regarding the benefits and drawbacks that EES technologies will present to society, as well as the economic feasibility of EES in monopoly power markets. Given this, this paper presents a grid-scale production cost model for monopoly power markets in which EES generates profits by offering both energy and ancillary services. The production costs of the power system with and without an EES power plant was compared in order to generate a value estimation. Results indicate that the value of EES is related to the unit fuel price and the start-up cost of thermal power units, the penetration level of wind power and size of the EES system. Based on these variables, a value-driven pricing mechanism for EES was put forward and compared with other policies. Economic viability analysis revealed that the pricing mechanism currently used in monopoly power markets are highly inaccurate in capturing the value generated by EES. [ABSTRACT FROM AUTHOR]

Abstract There is much discussion about whether the rapid expansion of onshore wind power in China is sustainable, given the decrease in feed-in tariffs (FIT). It is unclear whether the recently launched nationwide carbon pricing system, which will include 1700 power companies, can compensate for decreasing FITs and possibly provide new incentives for wind power developments. This paper investigates the ability of carbon pricing policies to compensate for declining FITs in support of onshore wind power investment in China. First, we constructed a dataset of 2059 onshore wind power projects from China's thirty provinces between 2006 and 2015 to estimate the levelized costs of electricity (LCOE). This dataset was used to assess the profitability of each wind project for different carbon prices, varying levels of FITs, curtailment rate, and discount rate. Our findings suggest that the carbon price can compensate partially for the revenue loss caused by declining FITs as well as improving the profitability of projects. However, current carbon prices in China's carbon emission trading pilots are not sufficiently high to compensate for the revenue losses, especially under the grid parity scenario. Consequently, without FITs, the sustainable development of onshore wind power in China is uncertain. A sensitivity analysis of the effect of the carbon pricing policy demonstrates that in the case of higher investment risk and more serious curtailment, the effect of carbon pricing policy on promoting the wind power investment seems to be more significant. Highlights • A dataset of 2059 onshore wind power projects in China is constructed. • The LCOEs are estimated and the profitability is assessed with carbon pricing. • The carbon pricing policy can improve the profitability of the wind power projects. • The effect of current carbon price is limited under the grid parity scenario. • The effect becomes more significant in case of higher risk and curtailment rate. [ABSTRACT FROM AUTHOR]

In order to assess the viability of wind energy projects in China, this paper takes a real options approach by accounting for flexibility over deployment of the technology in response to a stochastic non-renewable energy cost. The difference between the latter and the R&D-enhanced cost of renewable energy operation may be thought of as a benefit from using wind. On the other hand, the Chinese government provides feed-in tariffs to encourage further adoption of wind, which should be included as a cost. This work, thus, shows that there is substantial options value to China's wind energy program, which is bolstered if the cost of carbon dioxide emissions is internalized. Moreover, by varying the rate of feed-in tariffs, the model may be used to show plausible ranges for the feed-in tariffs, which could be a useful policy insight. Furthermore, the study hypothesizes that with the likelihood of renewable energy to replace non-renewable energy, wind power in China can potentially reduce CO 2 emissions by approximately 6.4% by 2020 comparing to the 2005 level and highlights the significant role of wind power in China's emission targets and energy security. This is a relevant paper, especially given the importance of a sustainable energy transition for China. More generally, using the real options approach from a policy perspective could provide insights about the viability of renewable energy programs and robustness of feed-in tariffs rates. [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]

China has been very successful in creating conditions for industry localization in solar and wind energy manufacturing. In terms of their competitiveness in foreign markets, however, Chinese solar photovoltaics firms have shown significantly greater achievements than their counterparts in the wind energy sector. Moreover, the success of China’s solar photovoltaics industry has come in spite of significantly lower levels of domestic market support. The paper argues that technology-related factors and their implications for international technology transfer are critical for explaining the different speeds with which Chinese firms have been able to catch up in the two sectors. This is supported by a comparative analysis of technology transfer in the two sectors. [ABSTRACT FROM AUTHOR]

China has the largest wind power installation across the world due to the tremendous inland wind capacity and the government has begun to pay much more attention to develop offshore wind power in recent years. During the shift from inland to offshore, it is very important to identify the difference of energy performance between them. This paper establishes 4 indicators; energy consumption intensity (EI), energy payback time (EPT), energy payback ratio (EPR) and energy return intensity (ERI) to measure the energy performance of wind farms. Meanwhile, coastal wind farms are introduced as a smooth transition cases from inland to offshore wind farms. Each of the 8 farms for inland, coastal and offshore wind are taken as the examples to assess. The results show that inland and coastal wind farms have the similar energy performance, which pose significant difference with that of offshore wind farms. Based on the relatively lower EI, EPT and higher EPR, land-based inland and coastal wind farms are better for energy efficiency. From the energy performance route of wind farms, the energy performance strength of offshore wind farms only appear after 9.2 years of operation when compared to the land-based wind farms. Therefore, it is wise to set a long-term moderate target for offshore wind power development in China, just as the highest ERI of offshore wind farms can only be obtained in a long-term period. [ABSTRACT FROM AUTHOR]

In 2009, the implementation of feed-in tariff (FIT) and attractive public subsidies for onshore wind farms aroused great investment enthusiasm and spurred remarkable development of wind power in China. Meanwhile, rapid learning-by-doing has significantly cut down the cost of wind turbines and the capital cost of wind farms as well. Therefore, it is the right time to examine the appropriateness of the existing FIT policy for wind power in China. In this paper, we employ the analytical framework for levelized cost of electricity (LCOE) to model the generation cost of wind power. Results show that the existing FIT policy is attractive to investors, but serious curtailment and turbine quality issues could make wind power unprofitable. Meanwhile, rapid substantial decreases in the cost of wind power have made it competitive to coal power in 2013, implying that it is possible and necessary to reform the FIT policy for new wind farms. In the future, energy policies for onshore wind power in China could be concentrated on reducing the integration cost, so as to reduce the overall system cost. [ABSTRACT FROM AUTHOR]

In recent years, China has successively issued relevant policies to support the development of distributed renewable energy sources such as dispersed wind power (DWP) and distributed photovoltaic (DPV). The capacity of DPV grows fast, but the progress of DWP deployment is limited. In this paper, the improved levelized cost of electricity (LCOE) model and the internal rate of return (IRR) are employed to evaluate the economics of DWP and DPV for case regions. We find that, under current market regime, the IRR of DWP in eastern and central regions is 8.81%–10.34% for the grid side, and which of DPV is 9.08%–12.8% for the user side. When the power market is restructured, the IRR of DWP for industrial and commercial user side increases to 12.73%–14.86%, higher than that the return of DPV. Policy implications on grid-connection, land expropriation, and financial support, planning and approval procedure are proposed to promote the development of DWP. Overall, this paper covers the research gap on the development of DWP in China with a technical/institutional economics perspective and a comparison with DPV. Furthermore, our efforts make a significant contribution to DWP policy by identifying the institutional factors that hinder the development of DWP. • Explore the technical & institutional factors around DWP deployment in China. • DWP and DPV gain comparable economic returns under current planning regime. • DWP can have better economic returns than DPV with electricity market reform. • Identify institutional factors that hinder DWP and propose policy implications. [ABSTRACT FROM AUTHOR]

Green bonds have increasingly been utilized around the world as a source of financing for renewable energy development, designed with compliance requirements and measurable economic returns to investors, while mitigating climate change. However, the efficacy of green bond arranged in the emerging economies for financing renewable energy assets and how the underlying risks are managed have remained to be explored. The paper aims to examine the evolving green financial system sponsored by both public and private institutions in managing such risks within China's emerging economy. A case study of green financing for a bundle of wind power assets led by a state-owned enterprise (SOE) reveals an alternative approach by structuring public–private collaboration while stipulating market-based financial incentives to institutional stakeholders under a political economy. This institutional consortium is composed of a state development bank, a commercial bank, credit rating agencies, institutional and private investors, regional power purchasers, and carbon trading entities. Financial stakeholders' risk in such emerging sustainable investment is moderated by these participating institutions and structured "upsides" from carbon trading aligned with the framework of green finance and standards for green bond development. The results reveal the potentials of scaling up the development of renewable energy by adequately managing and sharing key risks, while allocating substantial funding into renewable energy projects under such a green financial system that is to be complementary with a scalable post COVID-19 economic recovery. [ABSTRACT FROM AUTHOR]

• Potential scenarios of adopting UHS in different parts of China were reviewed. • Planning schemes for HPES in three different regions of China were presented. • Peak shaving and renewable energy consumption capabilities of HPES were discussed. • Application prospect of applying UHS in different parts of China was analysed. Underground Hydrogen Storage (UHS) is regarded as a promising approach to achieve seasonal energy storage in the future, due to its synergy with surplus renewable energy generation. This paper proposes the idea of implementing an Integrated Energy System (IES) with UHS and other hydrogen related technologies, called Hydrogen Penetrated Energy System (HPES), and presents an intelligent planning procedure applicable to the HPES. Depleted oil/gas fields and salt caverns are selected as the study objects to explore the ability of UHS to achieve seasonal peak shaving, facilitate the renewable energy, and improve the energy system efficiency. Firstly, three regions in China are analysed in terms of geological conditions, resource endowment and load characteristics, to illustrate the feasibility of building a HPES in each of the analysed region. A two-stage planning method for the HPES is proposed and a detailed UHS model is established where the process of cushion gas accumulation is emulated and the influence of the diurnal temperature range is considered. Comprehensive case studies are subsequently carried out for typical cities or regions in Eastern, Northern and North-eastern China and the results demonstrate that the HPES can lower the cost, improve the energy efficiency and reduce the level of carbon dioxide emission to some extent. A lateral comparison also shows that the combination of salt cavern UHS and offshore wind power has a broad application prospect in the east coast of China, and the investment in the HPES scheme for Jintan can be recovered within 8 to 9 years. In addition, compared with the benchmark scheme without UHS and large penetration of renewables, the HPES scheme for Jintan can improve the primary energy efficiency by 22.26% and 27.75% in the first decade and second decade, reduce the carbon dioxide emission by more than 96%, and consume an average level of 95.85% of the offshore wind power. Although the investment payback period of HPES cases in north and northwest China is relatively long (20 years or more), significant return and benefits can be obtained in the long term. [ABSTRACT FROM AUTHOR]