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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]

Accurate and credible operation data sets of wind and solar power stations are the basis of many research works. However, such data sets often contain abnormal data due to failure, maintenance, energy curtailment, etc. The existing identification methods fail to consider the operating characteristics of power stations and the forms of abnormal data, resulting in low identification ability. Therefore, an adaptive identification method of abnormal data (AIMAD) in the wind and solar power stations is proposed in this paper, including the bidirectional one-sided quartile method and double DBSCAN method to deal with unevenly distributed abnormal data; the improved K-means clustering method based on the distance between the cluster center and benchmark power curve to process the abnormal data that are densely accumulated and closely connected with normal data in the power scatter diagram. The proposed method can adjust adaptively according to the forms of abnormal data to realize accurate identification and has strong robustness for power stations. The operation data of 30 wind farms and 8 solar plants in China are taken as examples to verify the effectiveness and superiority of the proposed method. • BOQ and d-DBSCAN are proposed to deal with unevenly distributed abnormal data. • Improved K-means method is proposed for identifying stacked abnormal data. • AIMAD is proposed to realize accurate identification of abnormal data. • Operation data in 38 stations are used to verify the effectiveness of AIMAD. [ABSTRACT FROM AUTHOR]

Renewable portfolio standard is an effective administrative tool to guide the behavior of electricity producers and impact the renewable energy diffusion. However, currently the renewable energy quota is generally set to be static and the efficiency is limited. In this paper, we proposed a dynamic renewable portfolio standard policy and we aimed to analyze how it will impact the renewable energy diffusion in China. The connections between electricity producers were simulated under both the perfectly competitive market and monopoly market. And a networked evolutionary game approach is applied considering dynamic linking between the electricity producers. The results show that dynamic quota policy is effective in promoting the proportion of wind power generation from 20% to 59.17% and promoting the proportion of solar power generation from 20% to 79.25%. With the sensitivity analysis, we found that renewable energy quota and the on-grid price are the most influential parameters. The proportion will reach 76.47% if quota is 0.7 and 68.1% if on-grid price is 630 Yuan/MWh. And the influence of tradable green certificate prices and generation cost is limited in promoting renewable energy diffusion. This paper offers the Chinese government a potential implementation for the perfection of national renewable energy diffusion. [Display omitted] • Propose a novel dynamic renewable portfolio standard scheme. • Analyze the influences of different kinds of the electricity market. • Investigate parameters affecting the wind power and solar power generation. • Establish dynamic networked evolutionary game models. • Dynamic linking is considered when the connections of players change. [ABSTRACT FROM AUTHOR]

The issue of renewable energy curtailment poses a crucial challenge to its effective utilization. To address this challenge, mitigating the impact of the intermittency and volatility of wind and solar energy is essential. In this context, this paper employs scenario analysis to examine the complementary features of wind and solar hybrid systems. Firstly, the study defines two types of complementary indicators that distinguish between output smoothing and source-load matching. Secondly, a novel method for generating wind and solar output scenarios based on improved Generative Adversarial Networks is presented and compared against the conventional Monte Carlo and Copula function methods. Lastly, the generated wind and solar scenarios are employed to furnish complementary features. The testing results across eight regions indicate the proposed scenario generation method proficiently depicts the historical relevance as well as future uncertainties. This study found that compared to the Copula function method, the root mean square error of the generated data was reduced by 4% and 3.4% for independent and hybrid systems, respectively. Moreover, combining these two resources in most regions showed that the total output smoothness and source-load matching level cannot be enhanced simultaneously. This research will serve as a valuable point of reference for planning and optimizing hybrid systems in China. [ABSTRACT FROM AUTHOR]

The world's key renewable power markets are generally challenged by wind and solar power curtailment. Research on the influencing factors of curtailment improvement can provide a reference for the further penetration of renewable energy (RE) into the power system. Based on the logarithmic mean Divisia index (LMDI) method, this paper analyzes the factors influencing the wind and solar power consumption rate in China from 2015 to 2018, and four typical provinces are discussed in detail. By decomposing the consumption rate into six factors (transmission structure, generation proportion, power self-sufficiency, resource development, resource utilization, and power consumption), and focusing on the transmission structure factors, this paper further clarifies the contributions of local use, ultra-high-voltage (UHV) transmission, and conventional transmission to the improvement of curtailment. The results reveal the following. (1) At the national level, the power mixing effect and the resource development effect have played major roles in the change of the consumption rate, but the influences of these two effects have been decreasing. (2) The UHV power lines provide a robust resource for the inter-provincial deployment of renewable power (such as the RE power transfer in Inner Mongolia and Gansu), but the role of UHV transmission has not yet been fully utilized. (3) The impact of the electricity consumption effect on renewable power consumption is increasing year by year, but the local consumption capacity remains insufficient (both at the national level and in the four typical provinces analyzed), so it is necessary to further increase the share of renewable electricity in UHV power transmission and the local consumption capacity. (4) The expanding development of wind and solar power may be the reason for the curtailment in Shaanxi, and a reasonable renewable power development plan must be further formulated. [ABSTRACT FROM AUTHOR]

Wind and solar power are expected to play important roles in many countries to achieve carbon neutrality; however, their inherent instabilities pose significant threats to existing power grids. Because hydropower has been recognized as a viable compensatory resource for solar and wind energy uncertainties, many studies have sought to determine optimal scheduling strategies for hydro-PV, hydro-wind, and hydro-PV-wind systems. However, few studies have simultaneously considered the sizing and scheduling of large-scale hydro-PV-wind hybrid systems connected to long-distance transmission lines. Therefore, this paper develops a mathematical metric to measure the wind and solar output complementarity and incorporates it into a multi-objective sizing and scheduling model for a hybrid hydro-PV-wind system, in which resource complementarity, profit generation, system reliability, and power curtailment trade-offs are concurrently considered. The ɛ -constraint method is employed and decision makers' attitude parameters are introduced to transform the proposed model into its equivalent single objective form. A case study in China reveals that the maximum wind and solar power output complementarity rate can be at least 0.19 for the studied hybrid hydro-PV-wind system. The incorporation of wind enables the hybrid hydro-PV-wind system to provide 4.11% more load than a hydro-PV system. In addition, if 2% of power curtailment is permitted, 1.53% more load can be served and 14.9% higher profits can be earned. To better explore the application of hybrid systems, management recommendations are provided for system operators, the power industry, and management administrations. • Multi-objective sizing and scheduling method for the hybrid renewable system is proposed. • Mathematical metrics to measure wind and solar power complementarity is provided. • A complementarity rate of 0.19 can be reached with 100% reliable service and no curtailment. • Integrating wind power into the hydro-PV system can reliably serve 4.11% more load. • An optimal rather than minimal level of the renewable power curtailment is more efficient. [ABSTRACT FROM AUTHOR]

Summary. With the continuous expansion of grid-connected power generation from renewable energy sources, such as wind and light, the forms of power sources are more diversified. The coupling and uncertainty of multiple energy sources will cause significant changes in the characteristics of the power system. Problems like the complexity of the power system lack a scientific and complete explanation. This paper comprehensively considers the regional weather conditions, the uncertainty of the output of wind and solar energy sources, and the time and space complementary characteristics of multiple power sources. Based on the theory of complex adaptive systems, a systematic and holistic optimization planning method is studied. Combining the idea of complementarity because of differences, a multipoint layout planning and design method for multienergy power systems is proposed to give full play to the synergistic effects of natural resources, achieve optimal resource allocation, and provide a theoretical basis for improving the consumption of wind and renewable energy. Taking an actual provincial power system in China as an example, through the comparison of production simulation calculations and multiscenario analysis and planning methods, the proposed method can significantly increase the consumption of wind and solar renewable energy. [ABSTRACT FROM AUTHOR]

Hydropower, an excellent power source for peak shaving, can respond quickly to load changes, which helps to overcome the anti-peak characteristics of wind and solar power. However, complementary operation with wind and solar power changes the operating boundaries of hydropower stations, making the original operating rules no longer applicable. Considering daily peak-shaving demands, this paper proposes a methodology to develop operating rules for a hydro–wind–solar hybrid system (HWSHS). First, a multi-objective and multi-timescale operation model is developed to ensure energy generation and peak-shaving performance simultaneously. Second, the feasible and reasonable region of available energy-based operating rules is analyzed, and three rule forms are employed to explore the optimal operating rules. Last, NSGA-II is utilized to optimize the rule parameters. A decoupling method is proposed to handle the shape constraints of operating rules, and the multi-timescale simulation method for a HWSHS is developed as the fitness function. In the simulation method, a load reconstruction-based load shedding (LRLS) method is introduced to determine the hourly output of each hydropower station. A forebay elevation check method is performed to obtain the hourly forebay elevation and correct the hourly output. The Beipan HWSHS in Guizhou Province, China, is selected as a case study, and the optimal operating rules are determined. The results also show that (1) the standard operating rules with hedging and packing increase peak-shaving performance by an average of 4.31% and 2.03% compared to the standard operating rules and linear operating rules, respectively; (2) the peak-shaving performance can be significantly increased (6.70%) with a slight decrease (0.37%) in the energy generation through changing the seasonal distribution of water and energy of the cascade hydropower stations; (3) the LRLS method, which makes the interday energy distribution more uniform, increases the peak-shaving performance by an average of 9.17% compared to the traditional load shedding method; (4) the energy generation and peak-shaving performance of the HWSHS are affected by the transmission capacity, and it is necessary to increase the transmission capacity by 25% to 35% of the installed capacity of wind and solar power stations. • A methodology is proposed to develop operating rules considering peak-shaving demands. • A multi-objective and multi-timescale operation model is developed. • The feasible and reasonable region of available energy-based operating rules is analyzed. • A multi-timescale simulation method is designed to simulate the operation of a HWSHS. • The methodology significantly improves the peak-shaving performance. [ABSTRACT FROM AUTHOR]

The increasing generation of renewable energy and its concurrent technological innovation are driving the transformations of the energy sector, but little effort has been made at the regional level to specify the heterogeneous impacts of different types of renewable energy development on multi-dimensional energy security. Therefore, this paper establishes a four-dimensional energy security assessment system based on the current energy market situation and economic context of China. Renewable energy generation and technological innovation were simultaneously used as the core proxies for renewable energy development. Then, the panel quantile regression method was used to analyze the heterogeneity of the impact of solar, hydro, and wind energy on energy security, covering 30 provinces in China from 2006 to 2019. The empirical results show that renewable energy power generation generally promotes energy security, but it cannot be effectively applicable to all levels of energy security. Renewable energy technology innovation has surprisingly hindered energy security. These results can serve as a policy and practical guide, suggesting that provincial governments in China should implement energy security and renewable energy policies in line with local characteristics. • The redefined provincial energy security presents obvious spatial heterogeneity. • Panel quantile regression was applied to balanced provincial panel data. • Hydropower contributes only to medium and low levels of energy security. • Wind and solar power contribute differently to all levels of energy security. • Renewable energy technological innovation impedes energy security. [ABSTRACT FROM AUTHOR]

Fossil-fired power generation is the most significant contributor to China's carbon emissions. New energy such as wind and solar is rapidly deploying in China and is considered an alternative to fossil energy. This paper focuses on the comparison in financial performance between fossil-fired generation and new energy generation companies. To do so, we combine the listed companies' financial data from 2010 to 2020 with the catastrophe progression method to evaluate the financial performance of China's power generation companies. The results indicate that although the profitability of the fossil-fired generation industry has stagnated in the past ten years, its comprehensive financial performance is still better than that of the new energy industry. The profitability of new energy companies has increased significantly in the past decade, especially the wind energy companies, whose profitability has greatly improved from 2013 to 2020. Wind power generation also has outstanding operating capacity among new energy generations. [ABSTRACT FROM AUTHOR]

As the installed capacity of renewable energy continues to increase, the proportion of China's renewable energy power generation has increased year by year, and carbon emissions have been effectively reduced. However, there is still a big gap between this and China's promised carbon emission reduction target. It is important to explore the coordination and optimization of power supply structure with the goal of carbon emission reduction. In the power market environment, there are conflicts of interest among wind power companies, thermal power companies, and energy storage equipment. Therefore, it is necessary to comprehensively consider their economic and environmental benefits to formulate subsidy policies. In order to solve the above problems, this paper studies the key issues of smart grid operation model, input-output efficiency, market game behavior, and policy effect simulation based on production simulation, game theory, statistics, and other theories. Finally, Matlab and Gridview were used to calculate the model results, and policy recommendations on wind power subsidies, thermal power carbon tax, and thermal power feed-in tariff were put forward. To achieve the goal of carbon emission reduction, renewable energy generation should be encouraged, and the proportion of installed capacity of wind and solar energy in the power structure should be increased. The most effective way is that the government should actively guide the subsidy mechanism into the electricity trading market. Based on the calculation results of the RTS-25 system in this article, the following policy recommendations can be put forward: within the government's financial capacity, at least 1 yuan per kilowatt-hour of wind power subsidy is provided, and the maximum of thermal power feed-in tariff is set at 0.7 yuan, and the higher the wind power subsidy and the lower the feed-in tariff of thermal power, the higher the carbon emission reduction. At the same time, a thermal power carbon tax of about 0.36 yuan per kilowatt-hour should be set. The results of this study can provide suggestions for consuming renewable energy and formulating competition rules in power market transactions. This article can be further studied. The scope of subsidy prices can be narrowed, and more precise subsidy prices that balance the benefits of various systems can be determined on the basis of this research. [ABSTRACT FROM AUTHOR]

Transnational power cooperation contributes to promoting the large-scale use of renewable energies in Asia, but how to develop the structure of power transmission network deserves careful investigation. This paper thoroughly investigates the structure of power investment and transmission network in China and neighbouring countries, aiming to promote the large-scale use of renewable energies around Asia. Various power-generation and power-transmission technologies are considered in detail, and transnational power interconnection risk cost and carbon emission cost are embedded into a bottom-up optimization model. The future power-generation structures and networks installed under various policy scenarios are analysed in detail, and the corresponding economic, carbon emission reduction and renewable energy consumption benefits are evaluated. The results show that power transmission between China's internal regions and neighbouring countries can save $56.7 billion for the entire power system through the large-scale grid integration of renewable energy. The installed capacities of wind power, solar power, and hydropower renewable energy power generation could be increased by 141 GW, 163 GW, and 58 GW, respectively. The construction of transnational transmission lines from Central Asia to Northwest China, Mongolia to North China, the Russian Far East to Northeast China, and Northeast China to South Korea could effectively promote the utilization of renewable energy in the Russian Far East, Mongolia and Central Asia and further reduce carbon emissions in China, Japan and South Korea. • It examines how to construct a power investment and transmission network in Asia. • Various technologies, risks and costs are considered based on bottom-up model. • Huge benefits exist for power transmission between China and neighbouring countries. • Various power-generation structures and networks installed are analysed in detail. • Suggestions about power investment and transmission are given for Asian countries. [ABSTRACT FROM AUTHOR]

China has set a goal of carbon neutrality by 2060 and is determined to increase wind and solar power to 1200 GW by 2030, even though it already has the world's largest installed capacity of renewables. However, the lack of flexibility in the power system will limit the development of a higher proportion of renewable energy. This paper evaluates the applicability of different types of flexible power sources in China for the first time. Above all, it describes the current situation of China's power industry and the necessity of increasing flexible power sources, establishes an evaluation system from the perspectives of benefit, opportunity, cost & risk, then determines 19 evaluation criteria. The BOCR-ANP-TOPSIS method was used to evaluate the system, where the ANP method determines the weights and the TOPSIS method ranks the alternatives. The result shows that pumped storage hydropower has the highest overall ranking, followed by the flexibility transformation of coal-fired power. Coupled with sensitivity and comparative analysis, valuable findings that will help future energy policymakers are reported. • Evaluating the applicability of different flexible power sources in China for the first time. • The identification of criteria for the selection of flexible power sources was given. • Making recommendations for China's flexible power source development policy. • The BOCR-ANP-TOPSIS method adopted can be extended to select flexible power sources in different regions meticulously. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Intermittent renewable energy sources have been transformed from supplementary energy to dominant incremental alternative energy sources in the context of carbon neutrality target worldwide. For coastal countries, it is urgent to integrate abundant offshore energy into regional onshore renewable power sources economically and reliably considering the scarcity of land resources and negative environmental impacts. However, limited knowledge on the complex spatiotemporally synergy relationships between energy potential (onshore and offshore) is a barrier in making reasonable policies to promote collaborative development of onshore and offshore energies. This study presents a spatiotemporally explicit modelling framework for assessing the synergy potential characteristics of onshore and offshore renewable energy sources. The framework firstly estimates the technical potential of solar PV and wind energy across the country by using 40 years of hourly meteorological reanalysis data (1980–2020), and then investigates the long-term changes trend, stability, and complementarity of solar-wind energy potential spatiotemporally at both onshore and offshore sub-regions. We find that a considerable amount of solar PV and wind energy sources could be harnessed in China, and onshore potential across the country (178 PWh/yr) is approximate 20 times higher than offshore energy potential (8.9 PWh/yr). Overall, onshore solar-wind energy potentials exhibit statistically insignificant but slightly increasing trend over the past 40 years, while offshore wind potentials observe an opposite change trend for solar PV and wind energy production. Complementarity assessment showed the northeast and offshore parts of China present high complementarity effects for hourly and daily power production of solar-wind systems. Furthermore, inter-regional combination between offshore and onshore northwest regions also exhibits promising synergy effect for renewable energy power output. The results on resources dynamic and complementarity highlight the advantage of interregional resources cooperative configuration and electric power grid interconnections. The analysis performed in this paper could provide a global picture for the integration planning and collaborative development strategies formulation of on-/offshore renewable energy across the country. • Synergy potential of onshore and offshore renewable energy was evaluated. • Trend, stability, and complementarity of solar and wind potential were examined. • Onshore energy potential in China is 20 times higher than offshore potential. • Synergy development strategies of onshore and offshore energy were proposed. [ABSTRACT FROM AUTHOR]

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]

Renewable energy generation is a crucial route to achieve carbon neutrality. In this paper, a methodology integrating richness, stability, and complementarity to assess accommodable potential of solar and wind power generation was proposed and implemented in Ordos, a resource-based city in northwestern China. Results showed wind and especially solar resources were abundant, with maximum of 6.74 kWh/m2/day in summer and 6.9 m/s in spring based on hourly data from 1981 to 2020. Availability of solar (>60%) and wind resources (>80%) was best in the abovementioned seasons. A comprehensive evaluation of stability showed these resources were both stable in spring. Continuity of wind resources was stronger than that of solar (94.5% > 91.3%), and it's variability was also higher (1.9 > 1.4). Then, using correlation coefficients, complementarity degree of these resources was qualitatively identified as moderate. Aiming for stability, the optimal complementary ratio of solar and wind power generation was quantified at 1:0.27, with instability reduced by 10.4%–44.4%, and their power generation could be maximally accommodated by the grid. Scenario analysis predicted a maximum of 2.46% of Ordos land could meet the demand for renewable energy development in 2025. This study provides methodology and model research on orderly replacement of fossils by renewable energy in northwestern China as well as in similar regions globally. • An improved methodology was proposed to assess renewable energy generation potential. • Power stability can be greatly enhanced by this system's evaluation and selection. • Optimal complementary ratio of solar and wind power generation was 1: 0.27 in Ordos. • Resources of regional differences can get various optimal ratios by this methodology. [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]

China's hydropower, with a total installed capacity of over 390 GW, is currently considered to be the most reliable flexibility resources to support the grid integration of wind and solar power with a total planned capacity of over 1200 GW. Fully exploiting hydropower flexibility is of great practical significance to China. This paper preliminarily evaluates the feasibility of transforming cascade hydropower stations to a large-scale cascade hydropower energy storage system (LCHES) via adding a pumping station between two adjacent upstream and downstream reservoirs. The pumping station can utilize excess electricity to recycle water potential energy between the two linked reservoirs. Taking cascade hydropower stations of a large hydro-wind-solar clean energy base (HWSCEB) in China as the case study, a simulation model is developed to simulate annual operation of LCHES at hourly resolution. The simulation results for the multi-year average representative year (2017) indicate that LCHES can effectively reduce the energy loss of HWSCEB, and store excess electricity of power grid during valley-electricity-price periods to realize price arbitrage; the overall efficiency of LCHES is approx.65%; LCHES is economically feasible only when the pumping station efficiency is greater than 55%. The performances of LCHES are further verified in different typical years. • Energy storage of cascade hydropower stations achieved via a pumping station. • Feasibility of the large-scale cascade hydropower energy storage system is evaluated. • Excess electricity can be effectively utilized to recover water potential energy. • Pumping station efficiency is critical to the economic feasibility. [ABSTRACT FROM AUTHOR]

The rapid development of solar and wind power, with their inherent uncertainties and intermittency, pose huge challenges to system stability. In this paper, a grid-connected hybrid power system that fully utilizes the complementarity characteristics in hydro, solar and wind power sources is proposed, which is capable of realizing an economic, managerial, social and environmental equilibrium in daily generation scheduling. A multi-objective optimization model is then proposed to determine the best possible solutions under nine typical scheduling scenarios, with ɛ -constraint method and fuzzy satisfying approach applied. A real case from the large-scale demonstration project in Qinghai, China clearly proved that the grid-connected hydro–solar–wind power system can provide significant comprehensive benefits. Specifically, on sunny days of normal season, the highest economic benefits can reach 1205820 × 1 0 4 CNY , consumer surplus is up to 6760 × 1 0 4 CNY , and the carbon emissions are as low as 159 × 1 0 3 tonnes. Meanwhile, hydropower, preferred as a flexible renewable power source, can effectively conduct the peak regulation, making the residual loads deviation lowest of 740.447 MWh. Future studies can focus on the long-term perspectives, further analyze the storage technology, demand response and carbon taxes. • A grid-connected hydro–wind–power generation system fully considers the generation complementarity between the different power sources. • The multi-objective scheduling optimization is developed implementing the economic-managerial-social-environmental trade-offs. • Nine typical scheduling scenarios with trapezoidal fuzzy numbers are established to handle renewables uncertainties. • Reliability analyses for each power source under different scenarios are conducted. [ABSTRACT FROM AUTHOR]

As large-scale wind and solar power sharing hydropower transmission channels are put into operation in river basins to lower investment costs in China, joint operations of hydro-wind-solar energy sources have become an effective operating strategy in power systems. However, wind and solar output with uncertainties and volatilities are problematic and pose challenges for power grid optimal scheduling, especially for peak shaving of grid system. In this paper, a novel decision-making model based on the information gap decision theory method is formulated to optimize the complementary operation of multi-energy systems. First, with the objective of minimizing the variance of the residual load, a deterministic short-term peak shaving model for a hydro-wind-solar system as a base case is established. Then, to model uncertainties of wind and solar output in the hybrid system and analyze the impact of grid peak shaving, the risk averse and opportunity seeker strategies of information gap decision theory-based technique are developed. Finally, as a proficient multi-objective optimization method, the normalized normal constraint method is exploited to solve the information gap decision theory-based bilevel optimal problem, and a set of Pareto solutions is obtained for the decision maker. A hydro-wind-solar hybrid system in Guizhou Province in China, with seven hydropower plants, a virtual wind power plant and a virtual solar power plant, is taken as an example to demonstrate the effectiveness of the proposed model. The results indicate that, by considering the uncertainties of wind and solar output, the presented model not only reduces the load fluctuations but also increases the flexibility response to the system against operational risk. In addition, the calculation time and load variance of the system are greatly reduced in comparison with stochastic programming. • A hydro-wind-solar hybrid system alleviates the power grid fluctuation. • The IGDT method handles the uncertainties of wind and solar output. • The usage regions are found by robust averse and opportunity seeker strategies. • Impacts of uncertainty on the power grid peak shaving operations. [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]

More and more attention has been given to the role of electric vehicles in reducing the economic cost and carbon emissions of the power system through the vehicle-to-grid (V2G) mode, as well as helping to integrate renewable energy power. The promotion of V2G mode needs to consider the effectiveness of policy costs, so it is urgent to estimate the potential benefits of V2G. In this paper, a multi-regional power dispatch and expansion model is constructed from the perspective of power system by taking China's plan to reach 1.2 billion kW of installed wind and photovoltaic power generation capacity in 2030 as an example, combining with the development planning of electric vehicles and power systems. The results show that by 2030, the implementation of unidirectional V2G and bidirectional V2G in China can reduce the total cost of power system by 2.02% and 2.08%, reduce the annual carbon emissions of the power system by 2.27% and 2.95%, and increase the total proportion of wind and photovoltaic power generation by 1.33% and 1.28% in the power mix. An increasing proportion of electric vehicles participate in V2G increases the proportion of new-installed wind generation and decreases that of photovoltaic power. Due to the high cost of battery degradation and the current power mix dominated by coal-fired generation, additional benefits of implementing bidirectional V2G over unidirectional V2G are limited. • V2G reduces the total power cost, carbon emissions, and renewables' curtailment. • Increasing the proportion of EVs participating in V2G improves potential benefits. • V2G changes the proportion of newly installed wind and solar power generation. • V2G shifts the electricity production from high-cost areas to low-cost areas. • Additional benefits of bidirectional V2G over unidirectional V2G are limited. [ABSTRACT FROM AUTHOR]

The world has witnessed a surge in renewable power installed capacity in recent years, and there is an emerging trend of renewable penetration in electricity production. However, there is a lack of quantitative comparative study on disaggregated renewable power sources concerning their generation efficiency performance, regional heterogeneity, development potential, and influencing mechanism in the existing literature. In the case of China's 30 provinces, this paper evaluates the hydropower, solar power, and wind power generation efficiency by stochastic frontier analysis method, and then reveals the distribution characteristics and deployment potential of different renewable sources. Furthermore, from the perspective of spatial heterogeneity, geographical detector model is utilized to study the influence mechanism of the generation efficiency of different renewable sources. The main results are as follows. Firstly, production inefficiency prevails in hydropower, solar power, and wind power generation industries. The installed capacity, utilized hours, and auxiliary power consumption have positive impacts on the three renewable energy sources. Every 1% increase in auxiliary power consumption leads to 0.16% increase in solar power generation, which is quite larger than the increase in hydropower and wind power. Secondly, on average, hydropower has the highest level of generation efficiency, followed by wind power and solar power. Kernel density curves indicate the generation efficiency of hydropower, solar power, and wind power displays distinct aggregation characteristics. Different energy types show significant regional differences in deployment potential. Thirdly, annual precipitation accounts for 76% of the spatial heterogeneity in hydropower generation efficiency, followed by hydropower technology innovation and power structure. As for solar power generation efficiency, the most important influencing factors are electricity investment and economic development. By contrast, wind power generation efficiency is primarily affected by power structure, electricity investment, and urbanization. Additionally, there exist distinct synergistic effects among different variables. These results provide insightful policy support for the improvement of renewable power generation efficiency. The study can be extended to the global scale using country-level data. • Stochastic frontier analysis is performed to study renewable generation efficiency. • Production inefficiency prevails in three renewable power generation industries. • Hydropower generation efficiency is higher than wind power and solar power in China. • Different energy types show significant regional differences in deployment potential. • The driving factors of generation efficiency are examined by geographical detector. [ABSTRACT FROM AUTHOR]