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Under the trend of global low-carbon development, reasonable and accurate prediction of electricity consumption plays an essential role in vigorously adjusting power system structure, promoting electrification, and other energy-saving and emission reduction measures. Considering the development trend of energy consumption, this paper introduces the Logistic model of energy structure into the system structure, and establishes a novel grey prediction model with system structure. According to the division of energy factors with similar attributes, this model seeks the internal relationship of the development of electricity consumption and describes the interaction between related factors and multiple main factors in the form of equations, which makes the model have better applicability and stability. In the validation part, the ten types of energy are divided according to their attributes, and the main factor group and the related factor group are distinguished. The model proposed in this paper is used for simulation and prediction, and is compared with the three types of models (six models). In the two cases, the simulation error of the new model is as low as 3.9790%, and the prediction error is 0.5645%. Compared with other models, the new model has shown good performance in the case of electricity consumption forecasting in China. The effectiveness of the optimization of the model in structure, background, and application is verified. At the same time, based on the analysis and prediction of China's consumption data, this paper gives relevant policy suggestions for developing China's power structure. • A novel model based on energy background (EPMGM(1,M,N)) is established. • The relationship of factors in the system are characterized by the equations. • A Logistic model based on energy structure is introduced to the new model. • China's electricity consumption is effectively predicted by the model. [ABSTRACT FROM AUTHOR]

Accelerating the energy transition of rural households in mountainous areas is an important step to improve energy poverty and mountain ecosystems and to help achieve carbon peaking and carbon neutrality. This paper explores the transformation of rural cooking energy in mountainous areas based on field investigation data from six villages in Chongqing. It systematically reveals the transformation process, driving factors and carbon emission changes in household cooking energy consumption in mountainous areas in the past 20 years by using mathematical statistics, multinomial logit models and the emission coefficient method. The results are as follows. (1) There has been a significant transition in the consumption of rural household cooking energy in mountainous areas. There has been a significant change in the proportion of different energy sources, including fuelwood (59.2%–1.9%), coal (16.5%–0%), gas (12.6%–15.5%), natural gas (6.8%–51.5%) and electricity (4.9%–31.1%). (2) The main driving factors of the household cooking energy transition in mountainous areas are income per capita, householder age, and householder education level. (3) The average annual household carbon emissions from rural household cooking energy decreased remarkably. The average annual household carbon emissions decreased from 6.80 t to 2.62 t in fuelwood (5.40–0.91 t), electricity (0.19–1.28 t) and natural gas (0.03–0.25 t) emissions during the study period. The contribution of this study is to investigate how the household cooking energy transition contributes to carbon peaking and carbon neutrality from a micro perspective. At the same time, this paper explores the mechanisms between the cooking energy transition and the ecological dividend of urbanization and proposes future reform initiatives for rural energy in mountainous areas to help achieve the goals of carbon peaking and carbon neutrality. [ABSTRACT FROM AUTHOR]

In order to deal with the rapid growth in residential electricity consumption, residential peak-valley pricing (PVP) policies have been implemented in 12 provinces in China. However, being inappropriate, the residential PVP policies have delivered no significant results. The challenge to China's PVP policy research lies in obtaining high-resolution electricity consumption data and modeling residents' behavior. By simulating household electricity load profiles, an electricity price policy response model and a residential PVP policy optimization model, are constructed and applied in this paper to simulate the effect of the current residential PVP policy and optimize the policy. The results show that the peak-shaving capability (represented by the reduction in peak load) of the PVP policy in 11 provinces is less than 3%, while the PVP policy in Gansu Province has increased household electricity bills by about 5.7%. In addition, the optimized PVP can reduce household electricity bills by 3% and reduce peak electricity consumption by about 9%. The 12 provinces should adopt the 3-phase division method and optimize the electricity price in the peak and valley (i.e. off-peak) periods respectively. This paper promotes the research on China's residential PVP policy and provides an effective reference for the design of the PVP policy. • An electricity demand model based on household characteristic is presented. • The peak-shaving effect of the current PVP policy in 11 provinces is less than 3%. • Optimized PVP can significantly reduce peak power usage and increase benefits. • The PVP policy needs to be optimized from the price and time period division. [ABSTRACT FROM AUTHOR]

In order to deal with the rapid growth in residential electricity consumption, residential peak-valley pricing (PVP) policies have been implemented in 12 provinces in China. However, being inappropriate, the residential PVP policies have delivered no significant results. The challenge to China's PVP policy research lies in obtaining high-resolution electricity consumption data and modeling residents' behavior. By simulating household electricity load profiles, an electricity price policy response model and a residential PVP policy optimization model, are constructed and applied in this paper to simulate the effect of the current residential PVP policy and optimize the policy. The results show that the peak-shaving capability (represented by the reduction in peak load) of the PVP policy in 11 provinces is less than 3%, while the PVP policy in Gansu Province has increased household electricity bills by about 5.7%. In addition, the optimized PVP can reduce household electricity bills by 3% and reduce peak electricity consumption by about 9%. The 12 provinces should adopt the 3-phase division method and optimize the electricity price in the peak and valley (i.e. off-peak) periods respectively. This paper promotes the research on China's residential PVP policy and provides an effective reference for the design of the PVP policy. • An electricity demand model based on household characteristic is presented. • The peak-shaving effect of the current PVP policy in 11 provinces is less than 3%. • Optimized PVP can significantly reduce peak power usage and increase benefits. • The PVP policy needs to be optimized from the price and time period division. [ABSTRACT FROM AUTHOR]

The increasing pressures of global warming, population growth and epidemic occurrence are causing challenges in meeting the growing requirements for water, energy and food. In particular, the contradiction between the supply and demand for water, food, and energy is exacerbated by inefficient resource utilization and carbon emission increase. Incorporation of the interlinked aspects of water, energy, food and carbon emissions from agricultural systems into one water-food-energy-carbon nexus facilitates integrated resource management. Biochar application to farmland is a potential strategy for carbon management and agricultural productivity improvement. The integration of biochar systems and the water-food-energy-carbon nexus is an efficient and coordinated alternative method for sustainable agricultural management and a crucial strategy for addressing water, energy and food security issues. Accordingly, this paper proposes an approach for the synergistic regulation of water, land, energy, and carbon emissions in a circular agricultural system by balancing water supply and demand, land allocation, electricity consumption, and economic upgrading principles. A two-stage circular agriculture framework is constructed, with biochar and electricity generated from agricultural residues at the first stage and employed at the second stage. Economic-environmental-energy harmonization is considered in the methodology, and the agrotechnical potential of biochar is quantified via crop yield increase and greenhouse gas emission reduction functions. This approach can assist decision makers in providing the best policy options given certain agricultural resources to achieve the maximum economic performance of the system while minimizing environmental side effects. In this paper, the model framework is applied to the Sanjiang Plain in northeastern China to verify the feasibility of the approach. The results indicate that the external electricity demand is reduced by 87.8% due to the generation of biofuels. Cropland greenhouse gas emissions are reduced by 34.09%–67.06% via the application of biochar. This study proposes an optimization method with important implications for the improvement of regional cropland management techniques and development of sustainable circular agriculture. This methodology can be extended to other agriculture-centered regions with limited resources and environmental problems. • Carbon cycle is integrated in agricultural water-food-energy-carbon (AWFEC) nexus. • An AWFEC nexus based model is developed for agricultural resources recycling. • Biochar and electricity are optimized sustainably for circular agriculture. • Analysis of resources recycling on economic-environmental balance is performed. [ABSTRACT FROM AUTHOR]

To address the global challenge of climate change and achieve sustainable development, decarbonizing the electric power system in China is considered the most imperative since the power sector is highly related to the decarbonization of other sectors. Significantly, China faces the dual challenges of rapidly growing electricity demand coupling with its commitment to of emission mitigation. This study examines the low-carbon transition and sustainable development of China's power system through 2035 using a multi-stage mixed-integer linear programming generation planning model by matching future demand growth trajectories with the least-cost power supply path. The electric power installed capacity, power generation, carbon emission, power-generating cost, and abatement potentials are analyzed through various scenarios. It is found that China's electricity demand will reach 9800–13300 Terawatt-hours in 2035 due to rapid electrification. Every 1 TWh increase in electricity demand requires 0.41–0.53 GW of newly installed capacity. Reducing the proportion of coal-fired power generation and replacing it with renewable energy is inevitable. However, for every 1 GW of coal power retired, 3.7 GW of renewable energy needs to be built. Incorporating electricity demand-side management is crucial to developing an effective decarbonization pathway for China's power sector, along with inclusive policies and technologies to meet China's requirements for dependable, affordable, and sustainable electricity. The results of this paper can provide a reference for policy makers in China as well as other emerging economies. • China's electricity consumption will continue to rise until 2035 and China will reach emission peak of power sector before 2030. • Meeting China's decarbonization requires gradually reducing coal-fired power capacity by up to the year 2020's 40.5% ty. • Every 1 GW of coal-power retirement requires the construction of 3.7 GW of renewable power capacity. • Demand-side management is crucial to easing high electricity demands for an effective power decarbonization trajectory in China. [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]

As China's largest source of carbon emissions, the power sector's transition to lower levels of carbon emission intensity is critical to achieving China's carbon emission (CE) reduction commitments. In this paper, the CE intensity of electricity generation (CEIE) in 30 provinces from 2000 to 2019 is calculated, and the temporal evolution and spatial distribution characteristics of CEIE are discussed. Then, the spatial spillover effect of each driving factor on CEIE is calculated using the spatial Durbin model. The CEIE reveals a first increasing and then decreasing trend, and the regional differences gradually decrease. Simultaneously, the CEIE has a significant positive spatial correlation, and the overall spatial distribution pattern is high in the northeast and low in the southwest of the country. Economic development and foreign trade both inhibit CEIE, while electricity consumption, research and development, unit operation level, and power structure all promote CEIE. Each driving factor's influence on regional CEIE exerts a spatial spillover effect. Among them, the spatial positive spillover effects of industrial structure and environmental protection investment are the most obvious, while the spatial spillover effects of other driving factors are not apparent. Furthermore, these findings provide practical insights into policy adjustments and the coordinated interregional development of low-carbon electricity. [ABSTRACT FROM AUTHOR]

In the context of global climate change and energy security pressures, biomass power generation has been regarded as an effective way to supplement the energy supply, reduce fossil fuel consumption, and alleviate environmental pollutants. This paper presents an integrated modeling framework to address the regional biomass power generation planning to facilitate biomass utilization in developing countries. By combining the geographic information system, multi-criteria decision-making approach, as well as the type-2 fuzzy inexact programming method, the proposed integrated framework could assist the optimal decision-making for the specific site and size selection of biomass power plants in the whole region as well as the optimal operation strategies under deep uncertainties. The proposed modeling framework is applied to the particular context of Henan, an agricultural province in China with great biomass potential. The results suggested that biomass power plants with a total capacity of 2.4 GW could be established, which could satisfy 6% of local electricity consumption and avoid 18.51 Mt of carbon emissions. The sensitivity analysis of the main economic parameters indicated that lower investment and operation costs were essential to stimulate the utilization of local biomass energy. A higher feed-in tariff is not encouraged due to the limited incentive effect but is a heavy burden for the government. Furthermore, the optimal strategies for biomass power generation planning under uncertainties could be suggested for different decision makers with various risk preferences to achieve a tradeoff between system cost and risk. [ABSTRACT FROM AUTHOR]

To fulfill the goals of sustainable development and emission reduction, China has established the consumption side renewable portfolio standards (RPS) and domestic nationwide carbon emission trading (CET) scheme. However, there are intricate interrelationships between the two mechanisms as they overlap in policy goals and implementation measures, which might lead to policy synergy or policy ineffectiveness. Therefore, investigating the coupling effects in the context of policy coexistence is imperative for policy optimization and realization of the policy objectives. In this study, a simulation model cooperating the electricity market, the excess consumption trading market, the tradeable green certificates (TGC) market and the CET market, based on the system dynamics (SD) methodology is proposed. The paper comprehensively investigated the complex relationship between the four markets and conducted experiments with different scenario settings in RPS quota goal and carbon quota goal. The results illustrate that: (1) Both mechanisms can facilitate the expansion of renewable electricity and improve the power supply structure. (2) The quota goals of the two policies should be reasonably set as they contain both the abovementioned overlapping effects, as well as conflicts in the effects on the total electricity supply and electricity price. (3) The consumption side RPS is conductive for market absorption of renewable electricity with a proper higher RPS quota goal. (4) The TGC market is oversupplied, and the price keep decreasing under the consumption side RPS, more demand incentive mechanisms are required for TGC market. • Implementation mechanism and effects of the consumption side RPS are investigated. • Policy coordination between the consumption side RPS and CET in China are examined. • The effects of consumption side RPS and CET have both overlaps and conflicts. • Ratio of renewable electricity consumption is positively correlated with RPS quota goal. [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]

To fulfill the goals of sustainable development and emission reduction, China has established the consumption side renewable portfolio standards (RPS) and domestic nationwide carbon emission trading (CET) scheme. However, there are intricate interrelationships between the two mechanisms as they overlap in policy goals and implementation measures, which might lead to policy synergy or policy ineffectiveness. Therefore, investigating the coupling effects in the context of policy coexistence is imperative for policy optimization and realization of the policy objectives. In this study, a simulation model cooperating the electricity market, the excess consumption trading market, the tradeable green certificates (TGC) market and the CET market, based on the system dynamics (SD) methodology is proposed. The paper comprehensively investigated the complex relationship between the four markets and conducted experiments with different scenario settings in RPS quota goal and carbon quota goal. The results illustrate that: (1) Both mechanisms can facilitate the expansion of renewable electricity and improve the power supply structure. (2) The quota goals of the two policies should be reasonably set as they contain both the abovementioned overlapping effects, as well as conflicts in the effects on the total electricity supply and electricity price. (3) The consumption side RPS is conductive for market absorption of renewable electricity with a proper higher RPS quota goal. (4) The TGC market is oversupplied, and the price keep decreasing under the consumption side RPS, more demand incentive mechanisms are required for TGC market. • Implementation mechanism and effects of the consumption side RPS are investigated. • Policy coordination between the consumption side RPS and CET in China are examined. • The effects of consumption side RPS and CET have both overlaps and conflicts. • Ratio of renewable electricity consumption is positively correlated with RPS quota goal. [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 the downward pressure of the economy, China's extensive economic growth that relies on factor input is difficult to sustain. Scientific analysis of the industrial restructuring and energy consumption has become the key to realizing China's economic growth from high-speed to high-quality. Based on the fully-modified least square method and panel vector error correction model, this paper explores the equilibrium relationship and Granger causality among the industrial restructuring, energy consumption and economic growth at aggregated and disaggregated levels. The results show that: (1) The effect of industrial structure rationalization on economic growth is higher than that of industrial structure upgrading. When emphasizing industrial structure upgrade, the more reliable industrial policy to achieve China's sustainable economic growth is to pay attention to the industrial structure rationalization, especially in western China. (2) The impacts of natural gas and renewable energy consumption on economic growth are much smaller than coal and electricity consumption; more energy policies should be designed to encourage clean energy development. • The industrial structure rationalization has highest contribution to the economic growth of eastern China, followed by central and western China. • There exists unidirectional causality from industrial structure upgrading to structure rationalizing in western China and bidirectional causality between them in central China. • Effects of natural gas and renewable energy consumption on economic growth are much smaller than coal and electricity consumption. • Unidirectional long-term causality from renewable energy to economic growth exist in each sub-region. [ABSTRACT FROM AUTHOR]

This paper aims to examine the causal relations between economic growth, electricity consumption, and urbanization indicators. Heterogeneous panel data techniques are performed to help shed light on the importance of the heterogeneity among three economic regions within China from 2000 to 2017. Our results show that the three indicators are all stationary and cointegrated after the first difference. Heterogeneity of the Granger causality is found between these three variables varies across the eastern, central, and western economic regions in China. In the long run, the eastern region presents a similar trend as the national level that long-run Granger causality of the three variables is found. Conversely, there is a unidirectional long-run causal relationship from economic growth to electricity consumption in the central region, while there is a bi-directional long-run causal relationship between economic growth and electricity consumption in the western region in China. Our empirical findings highlight the "urbanization ladder" effect which implies that as development, urbanization factor in the eastern region may play a promotion role in the tri-variate system when the urbanization reaches a higher level, while it may lack the influence in the central and western regions of China. From a regional perspective, it is further indicated that the improvement of urbanization can be practical measures in the central and western parts of China in the long run. • Economic growth, electricity consumption, and urbanization are cointegrated in eastern, central, and western China. • Granger causalities between the three variables vary across the three economic regions in China. • Urbanization does not have a causal effect on economic growth & electricity consumption in central-western China. • It is essential to accelerate the urbanization process in the central-western areas in China in the long run. [ABSTRACT FROM AUTHOR]