Solar Power In China Research Articles

Improving land-use efficiency of solar power in China and policy implications

Improving the power output of solar photovoltaic (PV) farms is critical to maximize the potential of PV power and reduce extensive land use in the context of large-scale deployment of renewable energy. In this paper we developed an integrated solar power potential assessment framework to quantify the gap between technical potential and actual generation of solar PV farms on national, provincial, and plant scales, and identify the key factors that cause the underperformance of PV farms. Specifically, to assess technical potential, hourly meteorological reanalysis data is adopted and the power generation-related parameters are calculated (i.e. optimal panel tilt, array spacing, packing factor etc.) with consideration of their spatial variability. For actual power generation, a detailed plant-level dataset is first established by this study which integrates technical, operational, and geospatial information from 145 solar farms across seven provinces in China. Our results show that the actual PV power generation per square meter is only 1/3 of the estimated technical potential. Technological factor is the primary factor, accounting for 48.43% of the underperformance, followed by engineering and management factors, accounting for 38.55% and 13.02%, respectively. The novelty of our study is revealing the underperformance level of solar farms in reality, identifying the causing factors, and highlighting the importance of integrating land-use efficiency indicators into solar power planning and development.

Short-term coordinated hybrid hydro-wind-solar optimal scheduling model considering multistage section restrictions

With the large-scale integration of wind and solar power in China, the consumption of these intermittent renewable energies is severely restricted by the capacity of the transmission channel, which leads to massive renewable energy curtailment. Therefore, it would be beneficial to use limited transmission channels to absorb as much renewable energy as possible. In this paper, we propose a chance constraint-based multistage nested hydro-wind-solar coordinated optimal scheduling model to aid peak shaving while ensuring maximum power generation. First, multistage partitioned section chance constraints are introduced to mitigate the power congestion of the transmission network. Then, based on the principle of using hydropower to complement the uncertainty of wind and solar power, the compensation chance constraints are considered. To quantify the uncertainty of wind and solar power, their prediction errors are analyzed using the Gaussian mixture model. Finally, the model is recast and linearized into a mixed integer linear programming model. A case study of a hydro-wind-solar base in Southwest China demonstrates that the proposed model can effectively leverage the regulation ability of hydropower to coordinate multiple power sources with the restrictions of multistage transmission sections, effectively alleviating the congestion of transmission channels and reducing the curtailment of renewable energy.

Assessing the technical and economic potential of wind and solar energy in China—A provincial-scale analysis

An accurate assessment of wind and solar resources is important for China's future transition to clean energy and the achievement of its carbon-neutrality goals. Based on climate data, geographical information, and the latest technical and economic information, this work estimates the total technical and economic potential of wind and solar power in China and their distribution by province. The main conclusions drawn by analyzing the spatial distribution and temporal evolution of the potential of wind and solar energy are as follows. (1) Both wind and solar energy have sufficient technical potential to support China's vision of carbon neutrality by 2060. (2) The potential is unevenly distributed spatially and is more concentrated in western and northern China, away from demand centers, with Xinjiang and Inner Mongolia accounting for >76% of the total technical potential of onshore wind and solar energy. The offshore wind potential is fairly equally distributed in coastal provinces. (3) In the near-to-medium term (5–10 years), fully utilized local wind and solar resources could help to meet the requirements of the non-hydro Renewable Portfolio Standard (RPS), and could significantly ease the urgency of building long-distance cross-province power transmission lines. For provinces with below-average RPS targets, the suggested non-hydro RPS targets could be further enhanced. (4) In the long term, the construction of adequate west-east and south-north transmission lines will remain essential to the construction of a national carbon-neutral power system.

Potential assessment of floating photovoltaic solar power in China and its environmental effect

Potential assessment of floating photovoltaic solar power in China and its environmental effect

A novel metric for assessing wind and solar power complementarity based on three different fluctuation states and corresponding fluctuation amplitudes

Assessing complementarity is a foundational work to combine wind and solar power to mitigate their fluctuations. Correlation coefficient is the most commonly used index to assess complementarity. But correlation coefficient mainly quantifies the synchronous and reverse correlations between wind and solar power. Moreover, it ignores the fluctuation amplitudes of wind and solar power, which would misestimate the complementarity. To address the issue, a novel complementarity index is proposed considering both the fluctuation states and corresponding fluctuation amplitudes. The present study firstly divides the fluctuations of wind and solar power into synchronous, reverse, and discrepancy fluctuation states. Then the degrees of the three different fluctuation states are obtained according to the score rules considering the fluctuation amplitudes. Finally, the novel complementarity index is jointly determined by these fluctuation degrees. Validation results show that the proposed index successfully avoids the misestimation scenarios caused by using correlation coefficient to assess complementarity. Then the proposed index is applied to analyze the complementarity of wind and solar power in China on hourly, daily, and monthly time scales. The complementarity index is generally −0.11–0 on the hourly time scale in most regions of Jilin, Heilongjiang, Liaoning, Inner Mongolia, northern Gansu, southern Xinjiang, and the North China Plain, showing greater complementarity than other onshore regions. But the complementarity index is generally 0–0.3 in most of the aforementioned regions on the monthly time scale, implying that the complementarity on the monthly time scale is smaller than that on the hourly time scale. The complementarity indices in most offshore regions are −0.1–0, −0.12–0 and −0.2–0, respectively, on the hourly, daily, and monthly time scales. Further analysis reveals that the complementarity between wind and solar power would be overestimated once the fluctuation amplitude is ignored. Additionally, the proposed complementarity index can be used to optimize the installed capacity ratio of wind and solar power in a hybrid system. The proposed complementarity metric contributes to a better and more accurate understanding of the complementarity between wind and solar power. Furthermore, the proposed metric can be readily applied to assess the complementarity of other renewable power generations.

Prediction of the Share of Solar Power in China Based on FGM (1,1) Model

In recent years, fossil energy reserves have decreased year by year, and the development and use of renewable energy has attracted great attention of governments all over the world. China continues to promote the high-quality development of renewable energy such as solar power generation. Accurate prediction of the share of solar power in China is beneficial to implementing the goals of carbon peaking and carbon neutralization. According to the website of China’s National Bureau of statistics, the earliest annual data of China’s solar power generation is 2017, which leads to there being very few data on the share of China’s solar power generation. Therefore, the prediction accuracy of most prediction methods is low, and the advantages of the grey prediction model are shown. Based on the share of solar power in China from 2017 to 2020, this paper constructs an FGM (1,1) model, calculates r using the Particle Swarm Optimization (PSO) algorithm, and predicts the share of solar power in China in the next few years. r = 0.3858 and MAPE = 0.20% were obtained by calculation of the model. The prediction results show that the share of solar power generation in China will increase year by year, and it will reach about 4.2301% by 2030. In addition, it is found that the share of China’s solar power generation in 2021 is 2.1520%, and the predicted value is 2.1906%. It can be seen that the prediction error is small. Finally, the limitations and future research directions are elucidated. The prediction results presented in this paper will help to guide the development of solar power generation in China, and are of great significance in speeding up the pace of energy structural adjustment, accelerating the construction of a clean, low-carbon, safe and efficient energy system, and promoting sustainable development.

Development and Opportunities of Clean Energy in China

In the context of the energy crisis and global climate deterioration, the sustainable development of clean energy will become a new direction for future energy development. Based on the development process of clean energy in China in the past ten years, this paper expounds on China’s clean energy policy and development plan. The development of hydropower, wind power, and solar power in China in recent years is analyzed. On this basis, the Grey Forecasting Model is used to forecast the development and structure of China’s clean energy in the next 10 years, point out the direction and market opportunities of China’s clean energy development in the future, and put forward the implementation methods for the sustainable development of China’s clean energy. It provides a reference for the policy decision-making of China’s clean energy development.

Optimal power peak shaving using hydropower to complement wind and solar power uncertainty

Booming renewable energy development, such as wind and solar power, with their intermittency and uncertainty characteristics, pose challenges for power grid dispatching, especially for power grid peak shaving. In this paper, coordinated operation of hydropower and renewable energy in a provincial power grid is explored to alleviate fluctuation and aid peak shaving. Considering their aggregate effect, this study aggregates wind power plants and solar power plants into a virtual wind power plant and a virtual solar power plant, respectively, and the forecasted error distribution of wind and solar power is analyzed with kernel density estimation. Then, based on the principles of using hydropower to compensate for fluctuating wind and solar power, a day ahead peak shaving model with the objective of minimizing residual load peak-valley difference is built, which introduces chance constraints for forecast errors and coordinate hydropower operation with wind and solar power. To simplify the solution, the proposed model is recast as a successive linear programming problem. Day-ahead scheduling case studies of a provincial power grid system indicate that the proposed model can conduct peak shaving effectively, hydropower can compensate wind and solar power fluctuation, improve the stability of combined output, and make better use of renewable energy. Therefore, this study provides an alternative approach for peak shaving operation of power system with hydropower and increasing integration of wind and solar power in China and other places worldwide.

Economic potential to develop concentrating solar power in China: A provincial assessment

Concentrating solar power (CSP), a promising renewable energy technology, requires better policy support for its initial implementation, which, in turn, necessitates accurate forecasting of its economic potential. This study develops a model based on meteorological data and local policies to calculate the levelized cost of electricity (LCOE) in 31 provincial-level divisions in China. Based on land occupation, concessionary loan, and technology mode as the independent variables, the LCOE is estimated to be $142/MWh to $781/MWh in sites with direct normal irradiance above 1,800 kWh/m2/yr under current local policies and conditions (with and without thermal storage). Thus, this study lays a solid foundation for forecasting power generation and selecting economically feasible sites. It analyzes the CSP learning curve with respect to technologically advanced trends and scale expansion. With the proper optimization of the technology mode, it is reasonable to expect a significant LCOE reduction and grid parity in certain areas. A comparison of the current policies provides a reference for the Chinese government to formulate subsidy policies that would make CSP more competitive.

Incorporating critical material cycles into metal-energy nexus of China’s 2050 renewable transition

Renewables rely heavily on critical materials. Such material (metal)-energy nexus thinking is critical to guarantee global renewable transition. As the largest energy consumer, China aims to promote the unprecedented installation of renewables to significantly decarbonize energy system till 2050. However, the material constraints to those renewable targets have been widely neglected by current stakeholders in China. In this paper, a quantitative framework is proposed to identify and quantify the corresponding material constraints on energy transition from a material cycle perspective. Accordingly, the required critical material demand for China’s 2050 renewable transition and its flow, loss, and stock along the life cycle are quantified. It is found that the critical materials (i.e. Cadmium, Tellurium, Indium, Gallium, Selenium, and Germanium) required by solar power in China are all under high shortage and supply risk. Their cumulative demand from 2015 to 2050 will exceeded the present national reserve by 1.4–123-fold. Approximately 804–1056 thousand tons (kt) of Neodymium and 66–85 kt of Dysprosium are required to support the growth of wind power, which account for around 10% with the current reserve in China. Nevertheless, the limited scalability of rare earth production in China may still constrain wind power development. Hence, China should adjust its renewable pathways (e.g. more wind, less solar) based on the critical mineral endowment. Furthermore, recycling is preferred but has limited impact on material criticality mitigation before 2030, and it is then suggested more actions should be made on the international trade and material efficiency improvement along the life cycle to support future renewable needs.

Assessment of geographical distribution of photovoltaic generation in China for a low carbon electricity transition

Solar power is considered as one of the most promising low-carbon alternatives to fossil fuels for future electricity systems. The historical diffusion pattern of solar power in China is consistent with other energy generation approaches, which emphasizes the function of energy supply. Given that the electricity system in China is experiencing a low-carbon transition, the new installed capacity should be located in regions with an urgent need for carbon reduction, as well as good life-cycle performance. Therefore, indicators of carbon dioxide emissions and the carbon intensity of electricity consumption are employed to analyze the provincial demand for renewable power. Additionally, the life-cycle performance of solar power is assessed, grounded in the concepts of energy return on energy and carbon investments. On this basis, a comprehensive ranking of the provinces of China is provided. By considering carbon intensity as an indicator to assess the lifecycle performance of solar power, the results show that the distributed photovoltaics are suitable for installation in Shandong (1.06) and Jiangsu (0.98), which basically match the current layout, while some adjustments to the future distribution of centralized photovoltaic systems in China should be made, where Qinghai (0.45) and Ningxia (0.58) are not suitable as possible locations for newly installed capacity. Some policy implications for the future empowerment of photovoltaic generation in China are provided, including adequate life-cycle assessment, carbon pricing and financial subsidy.

Cost-benefit evolution for concentrated solar power in China

Abstract The prospective cost-benefit of CSP (concentrated solar power) is the attention focus for policy-making and investment decisions. In order to analyze cost-benefit evolution of CSP, the paper adopted the net present value and discounted cash flows techniques to develop a mathematical model, and calculated LCOE (levelized cost of energy) of CSP between 2018 and 2050 by taking the CSP industry of China as an example. The results show that: Firstly, CSP has a large potential in the LCOE reduction, and the values of parabolic trough and solar tower CSP systems reduce by 46%–57% and 47%–56% from 2018 to 2050, respectively. Secondly, predicted evolution for the LCOE of CSP strongly depends, not only on the cumulative installed capacity determined by the specific growth paths of Blue Map and Roadmap Scenarios, but also on the learning curves impacted by technical progress and experience accumulation. Thirdly, to select the sites with higher direct normal irradiation and land cost exemption is crucial to improve cost-benefit evolution of CSP. Lastly, the expected returns (i.e. discount rate) have important effect on the LCOE evolution of CSP, high expected returns lead to high the LCOE, and vice versa.

Cost-Benefit Analysis for the Concentrated Solar Power in China

In 2016, the first batch of concentrated solar power (CSP) demonstration projects of China was formally approved. Due to the important impact of the cost-benefit on the investment decisions and policy-making, this paper adopted the static payback period (SP), net present value (NPV), net present value rate (NPVR), and internal rate of return (IRR) to analyze and discuss the cost-benefit of CSP demonstration plants. The results showed the following. (1) The SP of CSP systems is relatively longer, due to high initial investment; but the cost-benefit of CSP demonstration plants as a whole is better, because of good expected incomes. (2) Vast majority of CSP projects could gain excess returns, on the basis of meeting the profitability required by the benchmark yield of 10%. (3) The cost-benefit of solar tower CSP technology (IRR of 12.33%) is better than that of parabolic trough CSP technology (IRR of 11.72%) and linear Fresnel CSP technology (IRR of 11.43%). (4) The annual electricity production and initial costs have significant impacts on the cost-benefit of CSP systems; the effects of operation and maintenance costs and loan interest rate on the cost-benefit of CSP systems are relatively smaller but cannot be ignored.

Status and future strategies for Concentrating Solar Power in China

AbstractChina is the world leader in several areas of clean energy, but not in Concentrating Solar Power (CSP). Our analysis provides an interesting viewpoint to China's possible role in helping with the market breakthrough of CSP. We present a short overview of the state‐of‐the‐art of CSP including the status in China. A blueprint for China's CSP development is elaborated based on China's 13th 5‐year program, but also on China's previous success factors in PV and wind power. The results of this study suggest that China could play a more prominent global role in CSP, but this would require stronger efforts in several areas ranging from innovation to policies.

Study on the statistical characteristics of solar power

Solar power in China has grown rapidly recently. It exists variation of solar power due to cloudy and dusty, which is not that much of wind. The way to evaluate the statistical characteristics of solar power is important to the analysis of power system planning and operation. In this study, a multi-scale spatial and temporal framework of evaluating indices was established to describe the variation of its own natural features and the interaction between solar and load, grids. Finally, we have a case study on the variation, comparison, penetration, etc.

A dynamic assessment based feasibility study of concentrating solar power in China

The technology of concentrating solar power (CSP) is a potential way to meet the increasing demand of electricity consumption and environmental sustainability. However, it is still difficult to determine the installed locations of CSP systems, electricity generation by the systems, and the cost of CSP electricity in China. After a comprehensive geographic assessment, this study analyzes the technical and economic feasibility of 100 MW CSP systems to investigate the development potential of three types of CSP systems (i.e. parabolic trough system, tower system and dish Stirling system) under Chinese conditions in the period of 2010–2050. Based on the geographic assessment in terms of solar resource, land resource, water resource and power grid analysis, six locations are selected as the representative sites of each potential region for installing CSP systems. The performance analysis is further carried out, and the results show that the six representative locations are suitable for installing CSP systems because the higher solar-to-electricity efficiency can be generated compared to the average one of CSP systems. Due to the high time dependency of the cost of CSP electricity, a dynamic assessment based on feasibility analysis method is applied to study the economic performances of CSP systems based on the predictions of CSP cumulative installed capacity in four scenarios proposed by International Energy Agency (IEA). It is found that the grid parities of parabolic trough system and tower system will be achieved as early as the next 10–20 years for the selected locations. The integration analysis of geographic assessment, technical and economic feasibility demonstrates that China has sufficient potential for the utilization of parabolic trough system and tower system.

Energy cost and greenhouse gas emissions of a Chinese solar tower power plant

It is commonly assumed that the application of solar power system can save energy and relief global climate change. Presented in this study is the account of energy performance and greenhouse gas emissions of a planned solar tower power plant in China based on the life cycle analysis method. The conservative estimation of energy cost for the concerned plant is 1.21 times of the electricity output, which is a relatively decent performance amongst power generation technologies. In order to analyze the greenhouse gas performance, a comparison is carried out between the solar tower power plant and conventional coal-fired power plant in China. Results show the application of this solar system obtains a net greenhouse gas emission reduction of 0.31E+06 ton CO2 equivalent, during its operating period of twenty years. It is believed that this successful example can lend solid support to a future wide use of solar power in China.

Concentrating Solar Power in China and India: A Spatial Analysis of Technical Potential and the Cost of Deployment

Coal power generation in China and India could double and triple, respectively, over the next 20 years, which would increase exposure to fuel price volatility, exacerbate local air pollution, and hasten global climate change. Moving to concentrating solar power (CSP), a growing source of utility-scale, pollution-free electricity, would help alleviate these problems, but its potential in Asia remains largely unexamined. In this working paper, Kevin Ummel uses high-resolution spatial data to identify areas suitable for CSP and estimates power generation and cost under various land-use scenarios.Total CSP potential in China is at least 16 times greater than current coal power output; in India, it is at least 3 times greater. A CSP expansion program could provide 20 percent of electricity in both countries by midcentury. Under conservative assumptions, the program will require subsidies of $340 billion in present dollars. Estimated costs are especially sensitive to the assumed rate of technological learning, making it especially important to form committed public policy and financing to reduce investment risk, encourage the expansion of manufacturing capacity, and achieve long-term cost reductions.

Concentrating Solar Power in China and India: A Spatial Analysis of Technical Potential and the Cost of Deployment

Coal power generation in China and India is expected to double and triple, respectively, over the next 20 years, increasing exposure to fuel price volatility, exacerbating local air pollution, and hastening global climate change. Concentrating solar power (CSP) is a growing source of utility-scale, pollution-free electricity, but its potential in Asia remains largely unexamined. High-resolution spatial data are used to identify areas suitable for CSP and estimate power generation and cost under alternative land-use scenarios. Total technical potential exceeds current coal power output by a factor of 16 to 23 in China and 3 to 4 in India. A CSP expansion program and attendant transmission requirements are simulated with the goal of providing 20 percent of electricity in both countries by midcentury. Under conservative assumptions, the program is estimated to require subsidies of $340 billion in present dollars; coal-associated emissions of 96 GtCO2eq are averted at an average abatement cost of $30 per tCO2eq. Estimated costs are especially sensitive to the assumed rate of technological learning, emphasizing the importance of committed public policy and financing to reduce investment risk, encourage expansion of manufacturing capacity, and achieve long-term cost reductions. The results highlight the need for spatially explicit modeling of renewable power technologies and suggest that existing subsidies might be better used through integrated planning for large-scale solar and wind deployment that exploits spatiotemporal complementarities and shared infrastructure.