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The power industry in China is the foremost emitter of carbon, necessitating a clean transition in its power generation segment for successful decarbonization. Identifying and quantitative analysis the critical factors that shape the transition and their operational mechanisms will help achieve a secure low-carbon transformation of the energy system. Nonetheless, the body of extensive research in this particular field remains notably limited. To bridge this gap, this paper initiates by developing a comprehensive mechanism framework (REEP) for the transition towards cleaner power generation including Resource endowment (abbreviated as R), Electricity market (abbreviated as E), Economic development (abbreviated as E) and Policy implementation (abbreviated as P) four fields. This framework is based on monthly power generation data derived from four categories of power generation sources at the provincial level in China, spanning the years 2014–2019. It dynamically and quantitative elucidates the multifaceted impacts of various influencing factors on the evolution of the power generation structure. Based on the REEP framework, we observe the power generation structure evolution trends. The study's findings underscore the significance of resource endowment as a paramount internal factor influencing the clean evolution of the power generation structure, while economic development emerges as a pivotal external driving force propelling its transformation. Despite wind and solar power generation accounting for a relatively small proportion at the end of the 14th Five Year Plan period, it is imperative for China to continue promoting the extensive development of renewable energy. While we should coordinate national power transmission and distribution on the foundation of incentivizing technological innovation in emission reduction and the development of energy storage technology. This approach is essential to comprehensively advance the low-carbon and stable development of the energy system, ultimately facilitating the realization of the dual-carbon goal. [ABSTRACT FROM AUTHOR]

Green total factor productivity is a vital measure of sustainable progress, holding immense implications for attaining both economic growth and environmental preservation in a mutually beneficial manner. Focusing on green total factor productivity, this paper examines its nexus with low-carbon energy technology using the Instrumental Variable Generalized Method of Moments (IV-GMM) model, based on a panel dataset in China during 2005–2018. This paper also examines the asymmetric impact of low-carbon energy technology on green total factor productivity. In addition, the moderating and mediating effects are checked. The main findings are that (1) low-carbon energy technology is a promoting factor for green total factor productivity. (2) Low-carbon energy technology exerts a more prominent marginal impact on green total factor productivity when green total factor productivity is at higher quantile levels. (3) Renewable energy generation not only drives green total factor productivity directly, but also further increases the promotion effect of low-carbon energy technology on green total factor productivity, showing a positive moderating role. (4) Energy structure transition and industrial structure transition are two internal impact mechanisms between low-carbon energy technology and green total factor productivity. These findings suggest that the government can promote green total factor productivity development by developing policies related to low-carbon energy technology and fully releasing the effects of technology on sustainable development. • This paper assesses the level of low-carbon energy technology (LCET) in China. • This paper examines the effect of LCET on green total factor productivity (GTFP). • LCET plays a significant role in enhancing GTFP. • Renewable energy generation positively moderates the nexus between LCET and GTFP. • Energy structure transition and industrial structure transition are two mechanisms. [ABSTRACT FROM AUTHOR]

Factors influencing the development of renewable energy have emerged as a hot topic of policy discussion in recent years. However, the direct impact of natural resource dependence on renewable energy has been overlooked, especially in emerging economies. Using Chinese province data from 2005 to 2019, this study employs a nonlinear panel model and a Quantile Regression with Nonadditive Fixed Effects for Panel Data (QRPD) model to examine the impact of natural resource dependence on renewable energy development and explores the great importance of government policy support. The study indicates that the influence of natural resource dependence on renewable energy development supports the "conditional resource curse" hypothesis, showing a U-shaped nonlinear relationship. The effect of natural resource dependence and government policy support on the development of renewable energy shows a dynamic change trend. In the early stage of renewable energy development, policy support is crucial, while during the growing and mature stages, natural resource dependence exerts a stronger driving force. The results of the mechanism test indicate that natural resource dependence can boost renewable energy development through green technology innovation and environmental regulation channels. This paper's conclusion provides a theoretical foundation for fostering the sustainable development of the renewable energy industry and is vital to China's efforts to reach peak carbon and carbon neutrality. • Nonlinear panel and QRPD models are employed. • Impact of natural resource dependence (NRD) on renewable energy development is revealed. • Dynamic effect of NRD and government policy support is discussed. • NRD has a negative and then positive impact on renewable energy development. • Pathways to improve renewable energy development through NRD are identified. [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]

The supply chain of rare earth metals plays a crucial role in producing thin-film solar photovoltaics (PVs), which are vital for renewable energy generation. However, this supply chain is often characterized by opacity, inefficiencies, and security concerns especially since those rare earth metals come from mainly one supplier, China. Also, the solar PVs' certificates are purely technical and fail to consider the ethical sourcing and sustainable supply chain management conditions of mining. The working conditions of the miners are often neglected and are least prioritized. In this paper, a blockchain-based solution was proposed to leverage the intrinsic decentralized blockchain features including traceability, transparency, non-repudiation, and accountability in the supply chain of thin-film solar PVs, to safeguard not only the technical conditions of the mined products but also the ethical conditions of the workers during mining. Ethical mines must uphold good safety standards, pay their workers a fair wage, adhere to working hours, and legal working age. The solution paves the way to ethical mining where the certification of the PVs is not granted unless both technical and ethical conditions are met. The supply chain of thin-film PVs that goes from mining the rare earth metals in China, where more than 70% of the rare earth metals used are extracted from, to the disposal at the end-of-life (EOL) of the PVs was presented. Smart contracts to enable the on-chain traceability of the registration, manufacturing, assessment, delivery, and disposal of PVs were developed. The solution exploits the tamper-proof logs of the distributed ledger to ensure accountability and record transactions as part of the data provenance. The proposed solution includes a system design with sequence diagrams, smart contracts with algorithms, and a testing and analysis section. [ABSTRACT FROM AUTHOR]

The development of renewable energy is the key to tackling climate changes and ensuring energy security. Meanwhile, the process is usually associated with a huge investment and financing gap, especially for transitional countries like China. Hence, developing and innovating the traditional financial system is urgent. However, existing studies have mainly focused on traditional financial perspectives, and few papers have critically examined how digital financial inclusion affects the growth of renewable energy industries. To this end, using Chinese provincial data from 2011 to 2020 and applying Feasible Generalized Least Squares (FGLS) method, this study explores the effect of financial inclusion on renewable energy and its underlying mechanisms from the production and consumption perspectives. It is found that the impact of financial inclusion on the production side of the renewable energy industry is significantly better than on the consumption side, and there is heterogeneity effect in different energy resource varieties, different regional locations, and different financial regulation intensities. The financial inclusion on renewable energy has a significant pulling effect in photovoltaic and wind provinces, but not in large hydropower provinces. Then, its driving effect is particularly pronounced in the northern region. Nonetheless, it is not significant for renewable energy consumption in the southern region. Besides, this positive effect cannot be achieved without stronger financial regulation. The mechanism of action assessment finds that optimizes the consumption pattern, increase the competition of commercial banks, and improve technological innovation all contribute to the positive effect whereas, FDI shows the negative effect. This study provides new evidence on China's achievement of the energy transition, suggesting the need to further improve incentives for FDI firms and to strengthen consumption-side guidance. [ABSTRACT FROM AUTHOR]

Renewable energy is an effective solution to alleviate the energy crisis and achieve sustainable development, and is gradually growing into an important energy source to support economic and social development. Different renewable energy technical plans have different characteristics under multiple criteria. Therefore, before the further exploitation of renewable energy sources, it is of great significance to evaluate the comprehensive performance of different plans and then determine the best renewable energy sources. Given this background, this paper proposes a novel evaluation method for renewable energy technical plans based on improved rough set theory and grey cloud model. Firstly, based on the normalized evaluation data, self-organizing map (SOM) clustering algorithm and system clustering analysis are adopted to discretize the evaluation attributes indexes and decision attributes indexes, respectively. Next, the improved rough set conditional information entropy method is used to calculate the index weights. Finally, the grey cloud model is employed to determine the grade classification of each evaluated plan. At the same time, each grade is quantified by assigning a corresponding score, and the comprehensive performances of renewable energy plans can be calculated, and then the ranking of different plans is achieved. Based on the actual renewable energy development data from a province in China, experiments were carried out to evaluate the performance of the proposed method. The results show that the proposed method performs better than some evaluation methods for renewable energy technical plans. [Display omitted] • Propose a novel evaluation method for renewable energy technical plans. • Use self-organizing map clustering algorithm to discretize the attributes indexes. • Apply improved rough set theory to determine the index weights. • Achieve the complete ranking of plans, and classify the plans into different levels. • Compared with the existing evaluation method, the proposed method performs better. [ABSTRACT FROM AUTHOR]

The utilization of renewable energy sources to produce electricity is capable of relieving the pressure of limited natural resources and achieving the sustainability of future energy. This paper addresses a multi-period multi-feedstock multi-technology biomass-based power generation supply chain planning problem with parameter uncertainty, balancing economic, environmental, and social objectives simultaneously. However, the main challenges in optimizing this problem are correlated with multiple conflicting objectives and uncertain parameters. This study proposes a novel globalized robust goal programming model with goal constraints to balance three conflicting objectives using priority levels and characterize the uncertainty of unit emissions and social scores by inner–outer uncertainty sets. After transforming globalized robust environmental and social goal constraints into their equivalent forms, the tractable counterpart of the proposed model is obtained, which is mixed-integer linear programming (MILP). Finally, the effectiveness of the proposed model is demonstrated through a case study about the design of a sustainable biomass-based power generation supply chain (SBPSC) network in Hubei Province, China. Computational results reveal that by adjusting several parameters, environmental and social aspired goals consistently can achieve, whereas the economic objective is vulnerable to being influenced. Comparative studies with nominal goal programming model and robust goal programming model indicate that the proposed model is uncertainty-immunized and less conservative. Under investigated circumstances, the realized economic profit by the proposed model is approximately 42.5% higher than that of the robust goal programming model on average. • A pair of uncertainty sets is presented to characterize the parameter uncertainty. • Globalized robust environmental and social goal constraints are established. • Established goal constraints are transformed into their computationally tractable forms. • A novel globalized robust goal optimization method is proposed to balance three conflicting objectives using priority structure. • A case study shows the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

With the goals of carbon peaking and carbon neutrality, China's renewable energy has entered a stage of rapid development. The government gives financial and power-rate subsidies to clean power while putting great support on its construction. However, there is currently a big gap in the government's subsidy on new energy power generation, which is challenging to meet the demand for renewable energy consumption and sustainable development. In this regard, participating in the market is inevitable for renewable energy development, which is significant for promoting renewable energy power consumption and alleviating the subsidy dilemma. Considering the market-based mechanism, this paper regards the electricity market, the tradable green certificate market, and the carbon emissions allowance trading market as an integrated energy platform system that couples carbon emissions with electricity, linking generators and retailers. We consider two scenarios, including green electricity–green certificate separation and unity, and introduce the intermittency of new energy generation to construct the optimal pricing decision for this platform supply chain. We explore the optimal price of tradable green certificate for renewable power and the equilibrium demand for green power and thermal power in two circumstances. The results show that: (1) there is an equilibrium solution in various conditions. Moreover, the optimal price of green certificate in condition two, namely green electricity–green certificate unity, is higher when the on-grid price of green electricity and thermal one and the substitution effect of these two powers satisfy a certain constraint, which can stimulate generator and retailer to generate and consume green electricity as much as possible. (2) The price of carbon emissions and the responsibility weight of renewable electricity consumption both have a positive influence on the optimal price of green certificate and the share of equilibrium demands for green power, whereas intermittency of new energy generation has a negative impact on them. Adjusting the carbon price and incentive responsibility weights and taking relevant measures to reduce intermittency in different situations help to reduce thermal power demand and promote green power consumption. (3) When the prices of green certificates in diverse circumstances are in a certain interval, the impact intensity of changes in green certificate price on electricity demand will arise. It is conducive to performing the facilitative role of green certificate price on the power market better and stimulates the generation and consumption of new energy power in the carbon-electricity coupling market. • Through the carbon-electricity coupling perspective, the optimal TGC price was explored. • Introducing substitution effects of green power and thermal power to analyze optimal TGC prices. • A higher incentive responsibility weight of renewable consumption in scenario two can promote the retailer to consume. • Impact intensity of changes in green certificate price on power demand will arise when the price is in a certain interval. [ABSTRACT FROM AUTHOR]

In this paper, an improved hybrid MADM method based on interval Decision Making Trial and Evaluation Laboratory (DEMATEL) and interval regret theory are put forward to evaluate five renewable energy alternatives for Fujian province, China. Firstly, the volatility of the evaluation information and the subjectivity of experts or stakeholders are taken into account. Second, political factors are further considered based on existing research. Third, the influence of the subjective initiative of decision makers on the decision result has been paid attention to. Furthermore, the result of the analysis shows that the extended regret theory method should set different parameters to reflect the preferences of decision makers. The ranking results of renewable energy are different with different parameter settings. For example, when α = 0.1 , δ = 0.1 , the priority of clean energy in Fujian Province is hydropower, followed by wind energy, solar energy, geothermal energy, and biomass energy. Sensitivity analysis indicates that the model possesses good serviceability. Based on considering different parameter settings, the Fujian government should invest, in order of priority, in these renewable energy sources to obtain benefits. And the projects related to these renewable energy sources should be evaluated. [ABSTRACT FROM AUTHOR]

Under China's current Renewable Portfolio Standards (RPS) policy system, the provincial power grid is the assessment subject, and then the assessment is conducted on the user side. However, in the centralized clearing power market, renewable energy (RE) consumption on the user side cannot be accurately identified, so accurate value transmission cannot be formed to guide users to optimize their electricity consumption behavior. To improve this problem, this paper identifies the irreplaceable role of users in RE consumption through time series simulation. We construct a three-layer RPS assessment value transmission model of "power grid company - retailers - users" based on the identified unique contributions of each user. The equilibrium state of multi-market participants is obtained based on the decentralized training framework of reinforcement learning. The following conclusions are drawn through simulation analysis:(1) the user-side RE contribution identification method can effectively identify the user's contribution to RE consumption, which can reduce about 8% or increase about 7.48% of RPS cost allocation according to different contribution degrees; (2) the RPS value allocation mode can optimize users' power consumption behavior, achieve peak shaving and valley filling, promote RE consumption, and reduce about 0.6% of the abandoned wind power; (3) Under the RPS system, the effect of improving the response-ability of the user-side is better than increasing the RPS target and the peak shaving capacity. • Accurately identify the RE consumption of users under the unified clearing mode. • Construct a transmission mode of RPS assessment among grid, retailers, and users. • Construct a distributed training framework of multi-agent. • The research is helpful in promoting the consumption of new energy. [ABSTRACT FROM AUTHOR]

As the world's largest developing country, China has set the target of "reaching carbon peak by 2030 and carbon neutrality by 2060". China's power sector faces many challenges in reducing carbon emissions. This article forecasts electricity consumption from 2021 to 2060 by selecting five influential elements on power demand. Furthermore, the system dynamics model simulates the carbon emission system on the supply and demand side of the power industry. This paper innovatively incorporates the technology factor of carbon capture, utilization, and storage (CCUS) into the supply-side model. In this study, the process of carbon neutrality is separated into three stages, including carbon peak stage (2020–2030), deep low-carbon stage (2030–2050) and zero-carbon stage (2050–2060). The factors of energy storage technology and CCUS technology make significant contributions in the latter two stages. Based on the different development levels of the variables, three scenarios are set as business-as-usual scenario (BAU), low carbon scenario(LC) and ultra-low carbon scenario (ULC). Then scenario analysis is employed to simulate the carbon emission in the future. The scheme under the ULC scenario is the optimal solution to achieve carbon neutrality. Improving flexible transition of thermal power units and promoting the growth of renewable energy are China's primary strategies of achieving carbon peak and carbon neutrality. • System dynamics model is applied to simulate scenarios on carbon emission. • The carbon emission models of the power supply and demand sides are constructed. • Three scenarios for achieving the dual-carbon target are proposed. • The electric energy substitution and CCUS are investigated in the model. [ABSTRACT FROM AUTHOR]

Under China's current Renewable Portfolio Standards (RPS) policy system, the provincial power grid is the assessment subject, and then the assessment is conducted on the user side. However, in the centralized clearing power market, renewable energy (RE) consumption on the user side cannot be accurately identified, so accurate value transmission cannot be formed to guide users to optimize their electricity consumption behavior. To improve this problem, this paper identifies the irreplaceable role of users in RE consumption through time series simulation. We construct a three-layer RPS assessment value transmission model of "power grid company - retailers - users" based on the identified unique contributions of each user. The equilibrium state of multi-market participants is obtained based on the decentralized training framework of reinforcement learning. The following conclusions are drawn through simulation analysis:(1) the user-side RE contribution identification method can effectively identify the user's contribution to RE consumption, which can reduce about 8% or increase about 7.48% of RPS cost allocation according to different contribution degrees; (2) the RPS value allocation mode can optimize users' power consumption behavior, achieve peak shaving and valley filling, promote RE consumption, and reduce about 0.6% of the abandoned wind power; (3) Under the RPS system, the effect of improving the response-ability of the user-side is better than increasing the RPS target and the peak shaving capacity. • Accurately identify the RE consumption of users under the unified clearing mode. • Construct a transmission mode of RPS assessment among grid, retailers, and users. • Construct a distributed training framework of multi-agent. • The research is helpful in promoting the consumption of new energy. [ABSTRACT FROM AUTHOR]

As the world's largest developing country, China has set the target of "reaching carbon peak by 2030 and carbon neutrality by 2060". China's power sector faces many challenges in reducing carbon emissions. This article forecasts electricity consumption from 2021 to 2060 by selecting five influential elements on power demand. Furthermore, the system dynamics model simulates the carbon emission system on the supply and demand side of the power industry. This paper innovatively incorporates the technology factor of carbon capture, utilization, and storage (CCUS) into the supply-side model. In this study, the process of carbon neutrality is separated into three stages, including carbon peak stage (2020–2030), deep low-carbon stage (2030–2050) and zero-carbon stage (2050–2060). The factors of energy storage technology and CCUS technology make significant contributions in the latter two stages. Based on the different development levels of the variables, three scenarios are set as business-as-usual scenario (BAU), low carbon scenario(LC) and ultra-low carbon scenario (ULC). Then scenario analysis is employed to simulate the carbon emission in the future. The scheme under the ULC scenario is the optimal solution to achieve carbon neutrality. Improving flexible transition of thermal power units and promoting the growth of renewable energy are China's primary strategies of achieving carbon peak and carbon neutrality. • System dynamics model is applied to simulate scenarios on carbon emission. • The carbon emission models of the power supply and demand sides are constructed. • Three scenarios for achieving the dual-carbon target are proposed. • The electric energy substitution and CCUS are investigated in the model. [ABSTRACT FROM AUTHOR]

In renewable dominated power systems, the primary challenge is how to incentivize the utilization of subsistent renewable energy instead of how to incentivize the investment to expand renewable energy. This paper proposes an incentive policy named incremental green certificate (IGC) to cope with the challenge. The proposed IGC directly transfers voluntary consumers' payment to cover the premium of flexible resources to utilize more renewable energy. To make the IGC cooperative with power markets, a two-stage day-ahead market clearing model is proposed. In the model, the first stage follows on-going power market rules to clear the locational price, and the second stage reschedules the flexible resources to clear the IGC. Also, the incentive compatibility of the proposed policy is demonstrated, and the system dynamic model is built to quantify the long-term influence. Conclusions are drawn from the case studies on modified PJM 5-bus and a real-life provincial power system in China. The IGC would boost the investment of flexible resources, reduce the curtailment of renewable energy, and benefit renewable energy companies in the long term. • Proposed an IGC policy to reduce the curtailment of highly penetrated green energy. • A two-stage market clearance model is proposed to maximize green energy penetration. • Proved the incentive compatibility of the IGC policy. • Quantified the long-term effect of IGC on flexible resources using system dynamics. [ABSTRACT FROM AUTHOR]

With the global trend of clean and low-carbon energy transformation, China has put forward the 30·60 double carbon target. However, traditional energy still need to play a supporting role in the energy transition period. The purpose of this study is to optimize the dispatching order of thermal power resource, when clean renewable energy is given priority and fully dispatching, but still can not meet the energy demand of the whole society. Different from the traditional economic dispatching, the green thermal power dispatching evaluation mechanism proposed in this paper is oriented by cleanliness, supplemented by economy and reliability. This paper set up green power dispatching evaluation model through the comprehensive use of the Analytic Hierarchy Process, Entropy Weight Method and Grey Relation Analysis. And emergy method was used to solve the problem of environmental information quantification and evaluation. Finally, we established a set of green comprehensive energy efficiency evaluation system with 16 indicators. The results showed that the dispatch sequence has changed significantly under the new mechanism, which confirmed that the model has good effect and practical value for optimizing the cleaning dispatching of thermal power. [Display omitted] • Green energy dispatching is clean-oriented, supplemented by economy and reliability. • Quantified and evaluated environmental information using emergy analysis method. • Constructed a set of complete green energy efficiency evaluation index system. • Realized refined ranking different from the rough environmental constraints. • Thermal power dispatch sequence has changed significantly under the new mechanism. [ABSTRACT FROM AUTHOR]

Renewable energy consumption has a strong driving force for promoting energy conservation and emission reduction, and is a new way to achieve clean and low-carbon development. Based on this, this paper uses the data of renewable energy consumption, carbon productivity, GDP, population, energy efficiency and technological innovation of 30 provinces in China from 2011 to 2020, and empirically analyzes the impact of renewable energy consumption on carbon productivity in 30 provinces in China, using STIRPAT model, comprehensively considers spatial horizontally and temporal vertically dimension. The empirical results show that: (1) China's carbon productivity shows a significant spatial spillover effect, its impact can spill over to adjacent areas within 1000 km; (2) China's renewable energy power consumption plays a significant role in promoting the improvement of carbon productivity. (3) Renewable energy consumption in the western region plays the most important role in driving carbon productivity. Finally, according to the temporal and spatial relationship between renewable energy consumption and carbon productivity in different regions, we provide specific regional policy suggestions. • The STIRPAT model is employed to explore temporal and spatial impact, while it considers sub regions. • Spatialy, the impact can spill over to adjacent areas within 1000km. Temporally, the impact fluctuates and rises. • The positive role of renewable energy consumption is found in China's western region. [ABSTRACT FROM AUTHOR]

The spatial distribution of biomass resources is not uniform. At present, the zoning of biomass energy development suitability is primarily based on resource potential, whereas energy demand is ignored as an important factor affecting the degree of local energy self-sufficiency. Under the constraints of high transportation costs, solar energy with low geographical constraints can be a supplementary energy source for biomass despite its instability. Based on the energy utilization potential of solar energy and biomass resources, this paper evaluates the energy surplus factor (ratio of renewable resource potential to energy demand) of each city in the study area, takes meeting the specific energy surplus factor as the construction prerequisites of biomass combined heat and power (CHP) plants, calculates the biomass resource utilization rate and energy surplus factor in the study area under different conditions, and provides zoning suggestions and data reference for the unified planning of biomass CHP plants. The minimum energy surplus factor that is suitable for the development of biomass energy is set as the construction threshold of biomass CHP plants (The construction threshold is the minimum condition for the construction of biomass CHP plants. Only areas where the energy surplus factor reaches the preset construction threshold are allowed to build biomass CHP plants). The results show that the construction threshold is negatively correlated with the utilization rate of biomass resources. When the construction threshold is less than 1.4, the utilization rate of biomass resources decreases rapidly with the increase of the construction threshold; when the construction threshold is greater than 1.4, the utilization rate of biomass resources decreases slowly and tends to be flat. It is suggested that biomass resources should be developed in different regions and in stages, and priority should be given to developing areas with an energy surplus factor greater than 1.4. Areas with an energy surplus factor of 0.3–1.4 are considered secondary development areas, and areas with an energy surplus factor of less than 0.3 are not recommended for development; these can meet 31% and 59% of the total energy demand and reduce 50319380 tons and 180524400 tons carbon emissions so that the limited construction cost can meet higher energy demand and biomass resource utilization. • Priority development areas are identified based on solar and biomass potential. • Energy surplus factor is calculated to determine the development suitability. • Strategies for zoning and phased planning of biomass resources are proposed. [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]