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Battery storage is widely regarded as an indispensable solution to the large-scale integration of intermittent renewable energy into the power grid. Being still too expensive by itself, battery storage is currently promoted in China for utility-scale grid-parity wind/solar projects with compulsive technical standards or voluntary allocation requirements for those additional renewable projects beyond grid integration capacity. Under mandatory policies, part of the revenue from renewable energy is used to pay for battery storage. Without a mature electricity market, the development of battery storage co-located with renewable energy would be largely dependent on policy design. This paper conducts a policy-driven system dynamics simulation on the development mechanism of battery storage co-located with renewable energy in China. The results show that the installed capacity growth of battery storage will mainly be driven by mandatory policies before 2024 and mandatory policies will become almost ineffective after 2028. However, mandatory policies may still dominate the development of battery storage after 2030 if the cost reduction is restrained. The conclusions provide theoretical support for the development of battery storage co-located with renewable energy in China. To minimize the adverse effect of mandatory policy, policymakers should keep close eyes on the advance in technology and power market and adjust the policy accordingly. [ABSTRACT FROM AUTHOR]

Given the pillar role of renewable energy in the low-carbon energy transition and the balancing role of energy storage, many supporting policies have been promulgated worldwide to promote their development. To achieve the ambitious goal of no less than 1200 GW of wind and solar by 2030, China has also introduced policies to encourage the deployment of energy storage for the grid integration of renewable energy. The national policy is conducive to enhancing system flexibility for renewable integration, but it will also add the costs of renewable energy, especially when counting the regional differences. This paper adopts an improved levelized cost of electricity model to examine the total costs of renewable power co-deployed with energy storage in different provinces of China. The results show that the nationally unified energy storage co-deployment requirement, namely, 15% capacity ratio of renewable installation and 4 h duration, will negatively affect the economics of renewable generation, leading to an average cost increase in 15% and 21% for wind and photovoltaic generation, respectively. The economics of co-deploying energy storage under current market mechanism is inferior, but it can be effectively improved when energy storage participates in ancillary services market. With the revenue of frequency regulation, the cost of renewable co-deployed with energy storage can be even less than that without co-deployment in most provinces, except for Hebei, Jiangxi, and Gansu. An independent market entity status is thus conducive to encourage the co-deployment. Our finding also implies for a province-specific energy storage co-deployment policy. [ABSTRACT FROM AUTHOR]

As a kind of renewable energy enterprise, wind power enterprise plays an important role in the energy transformation. However, its financing problems are also widespread. The purpose of this paper is to study the financing mode selection in order to improve sustainable development and future benefits of wind power enterprises. First, an evaluation index system is constructed through literature research and expert interviews, and the weight of each index is determined comprehensively by G1 and information entropy methods. On this basis, a financing mode selection model of wind power enterprises is constructed by using the prospect theory and hesitant fuzzy set. Next, this framework is used for case study. Financing patterns are ranked according to the comprehensive prospect value. The results show that financial leasing is the most suitable financing mode. Finally, the applicability and optimization of the model are proved by sensitivity analysis and comparative analysis. [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]

Facing the problem of energy shortage and the responsibility of carbon reduction, to achieve sustainable regional economic development, renewable energy must be vigorously developed. Technology can not only boost the development of renewable energy but be a new driving force for the economy. However, the development of the economy, technology, and renewable energy are interrelated, and the coupling and coordination among them lack sufficient evaluation and analysis. Therefore, an evaluation index system is constructed for the economy–technology–renewable energy ternary group. The evaluation model is applied to measure the coupling coordination degree, and a geographically weighted regression model is used to analyze the influence of key factors and their spatial differences. 30 provinces in China are used as examples for the study, and the results show that the coupling coordination degree is low in most regions, except for Guangdong, which has been maintained at an extremely coordinated level, and most provinces are in a fluctuating upward trend during the decade. Additionally, the results of the geographically weighted regression report that the influence of factors has spatial heterogeneity. The study provides a basis for relevant policy formulation in China, and the evaluation and analysis ideas can provide a reference for other countries or regions. [ABSTRACT FROM AUTHOR]

Dynamic optimization is likely to play an important role in the reliability, quality, and efficiency of future power system, specifically for microgrid with renewable generation. This paper presents an improved hybrid optimization algorithm, called information exchange particle swarm optimization (IEPSO), to deal with the problem of dynamic optimal control in a microgrid with multiple distributed generations (DGs), such as wind power, small hydro, and energy storage. Based on the actual application of DG in Southwest China, we propose an optimization model for grid-connected microgrid that introduces a contribution rate of energy storage into the model and incorporates practical engineering constraints. The performance of different optimization control strategies for active and reactive power is investigated, and the results indicate that the IEPSO algorithm is efficient for dynamic optimization, and the dynamic contribution rate control strategy for energy storage is more effective than static strategy. [ABSTRACT FROM AUTHOR]

The hydro-wind-solar hybrid power system of interest is in the upper reaches of the Jinsha River and is composed of the Gangtuo hydropower station, the Wanjiashan solar power station in Yanbian, and the Dechang wind farm. An analysis of the output characteristics of the three stations in the system is carried out. Based on a quantitative analysis of the output complementarity over a year (using a method of Pearson correlation) and a qualitative analysis of the output complementarity in a day, a mode of complementary operation is presented in this paper. On this basis, a real-time model is built using Visual BASIC and used to carry out complementary operational research. As a result, we ascertain the mode of reservoir operation required for a given total load on the power grid, wind power, and solar output. The research reveals the complementarity between the monthly and hourly energy outputs of pairs of the three kinds of energy sources. The complementarity between hydropower and wind power is found to be better than that between hydropower and solar power. Transmitting hydro, wind, and solar power together not only lowers the impact of negative factors but can also improve the efficiency of the energy delivery channels. This may help mitigate the impact on the environment and optimise the energy structure. [ABSTRACT FROM AUTHOR]

The rapid development of renewable energy (RE) has become a crucial strategy to mitigate climate change and promote sustainable development. However, financing RE projects is often challenging due to high upfront costs, complex regulatory frameworks, and lack of access to capital. Green bonds have emerged as a promising tool for financing RE projects and promoting sustainable development. This study evaluates the impact of green bonds on RE investment in China using a fuzzy analytical hierarchy process (FAHP) and a fuzzy weighted aggregates sum product assessment (WASPAS) method. The study identifies six factors, 18 sub-factors, and six investment strategies through extensive literature works. The FAHP method is used to evaluate various factors and sub-factors, while the fuzzy weighted aggregates sum product assessment (FWASPAS) method is employed to identify the key strategies for green bonds implementation in RE projects. The FAHP analysis finds that the financial impact of green bonds is the most significant factor with financial feasibility and cost of capital being the most important sub-factors in this category. The environmental, regulatory, and market are the most important sub-factors. The FWASPAS method indicates that green bonds can have significant impact on lowering the cost of capital, improving investor confidence, and supporting project certification of RE projects. [ABSTRACT FROM AUTHOR]

With the rapid development of renewable energy, the integration of multiple power sources into combined power generation systems has emerged as an efficient approach for the energy utilization. Pumped storage power stations, as large-capacity flexible energy storage equipment, play a crucial role in peak load shifting, valley filling, and the promotion of new energy consumption. This study focuses on the combined pumped storage-wind-photovoltaic-thermal generation system and addresses the challenges posed by fluctuating output of wind and photovoltaic sources. First, a K-means clustering analysis technology has been introduced to identify the typical daily scene output and load fluctuation patterns in an energy base in northwest China. Based on the operation constraints of each subsystem, aiming at the optimal comprehensive benefit, minimum generalized load fluctuation, and minimum carbon emission, an operation optimization scheduling model for the pumped storage-wind-photovoltaic-thermal combined power generation system has been established. When the optimization model has a configuration scale of 3000 MW for wind power and 2800 MW for photovoltaics, the pumped storage power station in the combined power generation system can achieve full pumping for 4 h and full generation for 5 h, which plays an obvious role in peak and valley regulation. Meanwhile, the combined system minimizes operating costs and carbon emissions, resulting in a minimum fluctuation of thermal power output by 6.6%. Furthermore, different capacity configurations demonstrate a non-linear relationship between the comprehensive benefits, carbon emissions, and the scene penetration rate. When prioritizing economic stability over carbon emissions, a thermal power capacity configuration of 7200 MW leads to the lowest total operating cost for the combined system, amounting to 26.38 million ¥. Results indicate that pumped storage effectively suppresses grid power fluctuations, promotes the consumption of renewable energy sources, and enhances the stability of thermal power output. [ABSTRACT FROM AUTHOR]

The challenge of harmonizing the integration of renewable energy in market-driven transactions and assured accommodations presents a predicament in the development of China's electricity spot market. Moreover, as renewable energy penetration escalates, the issue of reserve undeliverability due to transmission congestion diminishes the power system's capacity to utilize renewable energy resources. To address this concern, this study introduces a secondary clearing mechanism for the electricity spot market, taking into account the proportion of renewable energy consumption quotas. Based on the first clearing, when renewable curtailment occurs, the bid pricing of abandoned power units undergoes flexible adjustment through the optimization of the price correction coefficient, followed by the execution of a secondary clearing utilizing the revised bidding information to fulfill the stipulations of the renewable energy consumption quota ratio. Drawing on the outcomes of the two-stage clearing, an incentive-compatible settlement compensation mechanism is proposed to preserve the impartiality of the market operator. The spot market clearing model accounts for the transmission safety margin, effectively mitigating the likelihood of transmission congestion, reserve inaccessibility, and renewable energy curtailment issues in real-time dispatching. Finally, a modified IEEE 30-bus system serves to substantiate the efficacy of the proposed market mechanism. [ABSTRACT FROM AUTHOR]

Energy storage plays a crucial role in the safe and stable operation of power systems under high renewable energy penetration. Unlike conventional energy sources, the special physical characteristics of battery energy storage make it challenging to apply in practice. Some countries have been developing battery energy storage for a long time, and it is worthwhile to learn from the policies and market mechanisms for the development of battery energy storage to clear the obstacles for large-scale development and participation in the power market. This study focuses on the current status of battery energy storage, development policies, and key mechanisms for participating in the market and summarizes the practical experiences of the US, China, Australia, and the UK in terms of policies and market mechanisms. Then, the challenges of the current development of battery energy storage are analyzed, and suggestions are made in terms of policies and market mechanisms, so as to provide a reference for the development of battery energy storage in other countries or regions. [ABSTRACT FROM AUTHOR]

Offshore wind energy has been widely exploited as a promising renewable energy source in China in recent years. This renewable source's high curtailment rate due to strict wind energy penetration limits, however, remains a challenge of concern. Also, the difference between peak and valley loads of electric power systems continues to increase with economic and societal development. To address these issues, this study proposes a hybrid system composed of a high-capacity offshore wind farm coupled with a pumped hydrostorage (PHS) power system to absorb rejected wind power. The hydraulic energy stored by PHS system is expected to provide guaranteed energy during peak load demands on the main power grid. This study presents a multiobjective technoeconomic assessment model based on the principle of dynamic economy for optimizing the size of the PHS system. The conclusions can be summarized as follows: (1) the seasonal characteristics affect the utilization of wind energy; (2) PHS operating strategies have an influence on the PHS configuration, energy utilization, and economic benefit; (3) reducing the wind curtailment is the key to improve the system performance and economic feasibility; (4) the drop in water level has a negative effect on economic benefit and (5) provides clear guidance to set external financial parameters for a hybrid power station. The results show that a size-optimizing study is important in determining the system's economic feasibility and predicted performance. [ABSTRACT FROM AUTHOR]

To take full advantage of the complementary characteristics of various renewable energy sources, hybrid generation systems (HGSs) are used to accommodate the increased variability and uncertainty. In southwest China, there are many small cascade hydropower stations (CHSs) and PV power stations, which have spatial and temporal correlation characteristics and complementary characteristics. Pumped-storage units are considered as ideal large-scale energy storage elements for HGSs due to their fast response and long life. The purpose of this study is to increase the system reliability and water power utilization rate and maximize the economic benefits of a cascade hydro-PV-pumped storage (CH-PV-PS) generation system. Considering the reliability, economy, and water power utilization rate of the system, the CH-PV-PS system model with multiple objectives and multiple constraints is established. Then, a multi-objective stochastic numerical P system (MOSNP) is proposed. The external storage set and correction method in the MOSNP algorithm are introduced to ensure the diversity of the solution and improve the efficiency of the algorithm. The CH-PV-PS system is introduced in Sichuan Province, Southwest China. The simulation results show that (1) the MOSNP method can obtain robust and effective optimization results for the hybrid system; (2) the use of pumped storage units has increased the daily economy by 1018 CNY, and the total fluctuation of CHSs has been reduced by 29.3%, which makes the hybrid system safer and more economical; and (3) the uncertainty of PV and runoff will lead to frequent dispatching of CHSs, thus reducing the economic benefits of the system. [ABSTRACT FROM AUTHOR]

Although China is doing much on developing alternative energies, coal will still be the main energy resource for China in the near to medium term. Developing a green coal-electricity system in China is very important for reduction of carbon emissions and local air pollutants, while satisfying China's rapidly growing electricity demand. This paper first reviews the advancement in optimization models with endogenous technological change and spatial energy systems modeling. Then, present situation and technology strategy of coal-electricity industry in China are analyzed. Three interweaved issues are identified for the development of China's green coal-electricity system. It can be concluded that the future integration of spatial data with MESSAGE model is vital for the analysis of China's coal-electricity system. It will be helpful to study optimal spatial configuration and technology development strategies for the development of a green coal-electricity system in China. [ABSTRACT FROM AUTHOR]

As an important kind of renewable energy, China's photovoltaic (PV) industry has experienced many challenges in different historical stages. Many PV enterprises emerge in the stock market, correlate with each other, and form China's PV stock market network. However, the mutual influence between any two companies in the stock market is impacted by other enterprises and some external factors, which is not considered in the previous studies. In order to study the direct interdependence among China's PV stock markets, we propose the partial Granger causality network (PGCN) model. It is a first practice in the model to apply partial Granger causality to quantify the direct interactions between stock returns. The daily closing prices of 79 China's PV enterprises are selected, and the whole research period 2007.10.2–2016.10.3 is divided into four sub-periods according to three important time nodes. The PGCN in the overall period and four sub-networks are also constructed. Combined with the dynamic behaviors of networks' topological properties, the distribution of enterprise's influence, the conductive force of enterprises, and the stability of the stock market are analyzed. Meanwhile, the regional agglomeration development pattern is revealed, and top 10 influential enterprises are identified. [ABSTRACT FROM AUTHOR]

Because of the urgent requirement of maintaining a healthy environment, the quick development of economic growth, and the unstable price of conventional energy sources, generating electricity from renewable and clear energy in China will become the main trend in the near future. However, how to adopt a suitable strategic planning for different energy sources among stakeholders has not been comprehensively discussed in previous literatures and is becoming more important and complex. Accordingly, the current work employs a proposed method, which incorporates the benefits, opportunities, costs and risks and integrates quantitative and qualitative data to help analyze various impacts on the adoption of different primary energy sources. [ABSTRACT FROM AUTHOR]