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The large-scale grid connection of renewable energy is an inevitable trend to realize the low-carbon development of the power system. Therefore, the impact of the uncertainty of high-energy enterprise load and renewable energy on the establishment of the maintenance strategy of power grid units cannot be ignored. Previous research methods usually only consider the grid side or the load side. Therefore, this paper proposes a method to determine the maintenance strategy of the unit through the information exchange between the grid side and the load side, while taking into account the impact of the uncertainty of renewable energy on the system. Introducing the tiered carbon transaction cost into the objective function can reduce the system’s carbon emissions and increase the consumption of renewable energy. When establishing the grid-side model, the relevant constraints of robust performance are added, and the influence of the uncertainty of the wind turbine is fully considered. The results of the calculation example show that the unit maintenance strategy established after considering the uncertainty of high-energy enterprises and renewable energy sources has good economic efficiency.

Following China and the United States, India is the third highest CO2 emitter in the world. With its fast rising population and an industry primarily reliant on coal and oil, the country's emissions will continue to rise unless appropriate measures are taken. In India generally the carbon sequestration is done by storing CO2 in sedimentary basins where it gets capped by the impermeable cap rocks. The study aims to unfold the other techniques of carbon sequestration in subsurface formations, except for narrating the different types of carbon capture and sequestration techniques along with its storage in different types of environments. For instance, abiotic and biotic environments for CO2 sequestration. It further talks about carbon injections of oceanic, geological, and terrestrial types, to name just a few. Types of carbon emission sources are discussed too. In this paper three different approaches are described for carbon mitigation, namely CarbFix, CO2 Plume technology and Carbon Trading. A prefeasibility study was done in order to implement the three techniques in Dholera geothermal region in Gujarat, India. In literature review, it can be seen how the three techniques can help in permanent mitigation of captured carbon through carbonate mineralization, power generation and industrial applications. For any project government and public participation is important. In this regard the study gives a brief understanding about the steps to be taken by government and the public to promote such projects for carbon mitigation. Besides, the steps to be taken in such projects for health and risk assessment were talked about in literature review too.

Integrated Energy System (IES) is far-reaching significance for improving energy utilization efficiency and reducing carbon dioxide emissions. However, due to the lack of consideration of construction sequencing, carbon trading development trends and uncertainty risks in the current IES planning scheme, problems such as mismatch between supply and demand, excess carbon emissions and weak renewable energy carrying capacity have emerged. To address these problems, this study proposes a multi-stage time sequence robust planning model for IES that considers carbon trading and extreme scenarios. First, the synergistic and complementary energy framework of IES is introduced, and the operation principle of each unit in the system is briefly shown by matrix. Then, considering the construction sequence of multiple stages and the load difference in different seasons, a life cycle planning model is established, which includes carbon trading cost, renewable energy curtailment penalty cost, integrated demand response cost. In order to improve the system’s ability to withstand the uncertainty of power and load, the extreme scenario is obtained according to the confidence level, and the improved robust optimization model is used to enhance the robustness of the system, which plays a dual role of risk prevention and control. Finally, a green ecological park is used as the object to implement simulation, and a safer planning scheme is obtained under extreme scenarios. The case study shows that: (1) Compared with the single-stage planning method, the method proposed in this study can reduce the depreciation cost in the whole life cycle by 5.44%, and improve the phenomenon that the curtailment rate of wind power exceeds 20%. (2) After participating in the carbon market, the cumulative income generated in the three stages is 17.92 million ¥. (3) After implementing demand response, the cumulative configuration capacity of wind turbine, ground source heat pump and energy storage decreased by 1.02%, 7.85% and 57.6%, respectively. (4) The improved robust optimization model improves the risk resistance of the system.

In the construction of the energy Internet and the environment of national environmental protection, China has proposed the establishment of carbon trading markets, such as policy mechanisms, and energy conservation and emission reduction have also become the most popular topic. To this end, the article proposes a low-carbon operation mode of an integrated energy system. First, build a combined electricity-gas-heat-storage structure based on energy conversion and storage devices; then, introduce a stepped carbon trading mechanism and establish a hierarchical calculation model, that is, calculate carbon trading costs based on the carbon emission range; then, Establish a low-carbon scheduling model, in which the goal is to minimize the sum of power generation costs and CO2 emissions transaction costs, and take into account safety constraints. Finally, a case study will be conducted to test the effectiveness of the proposed model.

Climate warming and the energy crisis have been high-profile issues today, and carbon trading is considered one of the essential means to solve the problem. Carbon trading cannot ignore the impact on energy consumption and carbon emissions. Therefore, it is beneficial to develop a low-carbon economy to scientifically predict the trend of energy consumption and make timely investment decisions and policies in carbon trading. Based on the modelling mechanism of energy economy and the grey forecasting model, this paper studies the dynamic relationship among energy consumption, carbon emissions, economic growth, and carbon trading price and then constructs a grey prediction model of energy consumption driven by carbon trading. The least-square method and recursive mathematical method were used to obtain the model’s parameter estimation and corresponding time formula, respectively. In the end, we apply the model to the energy consumption in China, and three experimental results reveal that the prediction performance of the novel model is significantly better than the existing four grey models. And it is predicted that the energy consumption of coal in China will increase by 15.3118% in 2025, which can provide an essential reference for the energy structure adjustment and environmental policymaking in China.

The traditional robust optimization algorithm can only provide the scheduling plan in the worst case, but due to the time coupling constraints such as climbing and energy storage SOC(State of Charge) constraints, it is difficult to provide an adjustment scheme for intra-day scheduling plan. In the first stage, the upper and lower bounds of equipment output are taken as decision variables, and the cumulative change of load is introduced to deal with the constraint of demand response, so as to form the economic operation domain of the park. The Column-and-Constraint generation method (CCG) is used to solve the three-layer optimization problem, and the scheduling plan and optimal operating domain in the worst case are obtained. The intra-day scheduling can be adjusted arbitrarily according to the new energy output within the interval. Carbon transaction cost is included in the goal function to account for reduced carbon emissions. Simultaneously, to take use of the benefits of flexible adjustment, FM income is incorporated into the goal function, and the charging and discharging behavior of energy storage is defined by optimizing calculations based on real-time capacity prices during daily scheduling. The calculation results show that the proposed robust optimization algorithm based on economic operation domain can be regarded as an extension of the traditional robust algorithm. Besides, the total cost can be reduced and the economy can be improved by adjusting the scheduling scheme according to the new energy output in real time under the premise of ensuring the time coupling constraint.

The application of the farm biogas project is a perfect measure to deal with the increasingly nervous global climate problem and energy crisis and can support the accomplishment of urgently needed carbon peaking and carbon neutrality effectively. But the poor economic benefits hinder its better development. Thus, this paper aims to enhance the economics of farm biogas projects and explore a win–win model for economic and environmental benefits by studying the economic impact of participation in carbon trading on three types of farm biogas projects. First, economic analysis of farm biogas projects based on life cycle cost is carried out using case analysis. Second, the greenhouse gas emission reductions are calculated and benefits from carbon trading are considered. Then, the economic robustness was tested. Specifically, the economics of all three types of farm biogas projects is improved after carbon trading. The ecological farm biogas project has the best economic performance, with a net present value of $551,689.11, internal rate of return of 49%, and payback period of 2.39 years. In addition, the emission reductions of 5045.79 t CO2e, 7420.28 t CO2e, and 148.41 t CO2e are very significant. Based on these, suggestions for developing farm biogas projects and introducing biogas projects to carbon trading are put forward for the reference of governments and investors when making investments and reforms. According to the result, participation of farm biogas projects in carbon trading can effectively enhance economic benefits and accelerate the achievement of the greenhouse gas emission reduction target which is of great significance to the urgent goal of global green and low-carbon transformation. [ABSTRACT FROM AUTHOR]

The issue of climate change is highly related to carbon emissions. One of the practical efforts to reduce carbon emissions is through carbon trading and offset mechanisms. Implementing carbon trading demands massive funding allocation, which requires sustainable financial policy arrangements from the government and the private sector as an instrument to support nationally determined contributions under the Paris Agreement. However, only a few review articles look into the specific combination of green finance (also known as sustainable financing) and the carbon trading mechanism. In this study, we aim to review research on green finance and its association to the emission reduction and carbon trading. We utilized the VOSviewer framework to perform a bibliometric analysis on the Scopus database, and performed search, identification, and screening processes using selected relevant keywords. We obtained 506 articles from 2014 to 2022 related to sustainable finance and carbon trading aspects. Using rigorous bibliometric approaches, we identified both established and recent research clusters for topological analysis, identification of major research subjects, interdependencies, and trends in collaborative effort. The results indicate that there is ample room for additional research to link carbon trading with green finance initiatives or financing, which can improve the success of carbon trading activities. [ABSTRACT FROM AUTHOR]

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Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Southern Energy Construction is the property of Southern Energy Construction Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper explores the effect of carbon trading on low-carbon transformation of high energy consumption enterprises in China. Based on the mechanism of interaction and restriction among high energy consumption enterprises, carbon verification agencies and the government, a tripartite evolutionary game model is constructed. The three-dimensional dynamic system is built to analyze the behavior patterns of the three parties. The evolution path of the tripartite game is visualized, and the low-carbon transformation states of high energy consumption enterprises in different situations are described. The results show that the high energy consumption enterprises, verification organization and the government cannot reach the optimal game equilibrium (low-carbon transformation, verification and supervision) temporarily when seeking their own interests. The corresponding measures should be taken with different situations of the tripartite game. No matter what strategy the government chooses, the low-carbon transformation could be promoted by carbon trading through carbon verification mechanism. [ABSTRACT FROM AUTHOR]

The "double carbon" goal promotes the development of China's energy sector in the direction of green, low-carbon, safe and efficient. In order to improve the penetration of renewable energy such as scenery stabilize the diversified load fluctuation on the user side, improve energy utilization efficiency and develop safe lowcarbon and clean energy based on the carbon trading mechanism, the optimal operation model of micro energy grid MEG considering comprehensive demand response was constructed, and the CPLEX solution toolbox was used to solve the model for different scenarios. The results display that the operation cost of MEG system without considering carbon trading and comprehensive demand response is ¥18 853.30 while the operation cost of MEG system after considering carbon trading and comprehensive demand response is ¥15 540.57, which decreases by ¥3 312.73. At the same time, the peak-valley difference of electric, heating, cool and air conditioning load on the user side decreases by 5.9%, 3.4%, 10% and 9.13%. The results show that the established MEG optimal operation model can further improve the operation economy of the system and effectively reduce the carbon emission of the system. [ABSTRACT FROM AUTHOR]

In the context of the marketization of carbon trading in the power system, it is of great theoretical and practical significance to study a scientific and effective carbon emission quota allocation strategy. To solve this problem, under the current situation of large-scale access to new energy, considering the limitations of the carbon emissions from different emission subjects plus the construction of a carbon trading model among the emission subjects, a day-ahead optimal scheduling method that takes carbon emission quotas and carbon trading into account is proposed. Firstly, carbon transaction cost models of thermal power and wind power are constructed, respectively, and a carbon emission quota allocation strategy based on the entropy method is proposed to redistribute the weights of baseline emission factors for the regional power grid. Then, considering the additional carbon emissions of conventional thermal power units caused by wind power access, the carbon trading costs of different types of generation units are calculated on the basis of carbon trading price prediction. Thereafter, a day-ahead optimal scheduling model considering carbon emissions trading is constructed with the objective of minimizing the total cost of the system in the scheduling period. The model is solved as an MINLP problem based on MATLAB 2016a software utilizing CPLEX 12.4. Simulation results verify the correctness and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The concept of "oil to electricity" is crucial for expanding the share of electricity in final energy consumption as well as for encouraging energy efficiency and emission reduction. Initially, a multidimensional strategy analysis is conducted for the government, ports, and ships concerned. From an economics perspective, a mathematical model of electricity substitution benefit analysis based on multiagent cooperative game theory under cap and trade and carbon tax policies is constructed, and the effect of carbon emissions caused by ships on the environment and society is converted into economic value. How several variables, such as transformation costs, ship electricity consumption, subsidy rates, carbon tax prices, and the ratio of shore power usage time to berthing time, affect the functioning of shore power is analyzed. The best electricity price under various circumstances is determined while considering the benefits of the three parties to maximize social welfare. The reduction in carbon dioxide and pollutant emissions is calculated. Meanwhile, the environmental advantages of the "replacement of oil with electricity" procedure are estimated. An example supports the claim that the suggested modeling approach can successfully resolve the economic benefits of each participant for the period that fosters the growth of electricity replacement projects and offers a sound scientific foundation for the formation of pertinent legislation. [ABSTRACT FROM AUTHOR]

With the realization of the "dual carbon" goal, urban public transport with an increasing proportion of new energy vehicles will become the key subject to achieve the carbon emission reduction goal. Under the new background of deep coupling between transport networks and power grids, it is of great significance to study the carbon-trading mode of urban public transport participation in promoting the development of new energy vehicles and improving the operating efficiency and low-carbon level of the "energy-transport" system. In this paper, based on blockchain technology, a framework for urban public transportation networks to participate in carbon trading is established to solve the current problems of urban public transportation's insufficient motivation to reduce emissions, lax operation strategy and lack of carbon-trading matching mechanisms. Finally, Hyperledger Fabric was selected as the simulation platform, and we simulated the model through the calculation example. The results show that the proposed scheme can effectively improve the operating efficiency of urban public transport and reduce its operating costs and carbon emissions. In addition, policy recommendations on carbon price, carbon quota and penalties are proposed to improve the institutional system of the carbon-trading market. [ABSTRACT FROM AUTHOR]

For achieving carbon neutralization and promoting the coordinated development of solar and coal-fired power generations in the context of energy transition, this paper develops a public–private partnership project including the government, carbon exchange enterprise, solar thermal power plant and a coal-fired thermal power plant. Using the four-party evolutionary game theory method, the evolutionary stable strategies are evaluated. The influence estimate results of key factors show that a higher carbon emission penalty and a green electricity subsidy as well as a lower carbon trading tax rate will be beneficial to the carbon trading market, as well as facilitate carbon neutralization. In most instances, the government and carbon exchange enterprise can hold acceptable participating intention. For relatively suitable reference value ranges, the carbon emission quota sale price range of the solar thermal power plant sold to the carbon exchange enterprise is 5.5~6.0 USD/t, that of the carbon exchange enterprise sold to the coal-fired thermal power plant is 5.0~6.5 USD/t, that of the solar thermal power plant sold to the coal-fired thermal power plant is 5.0~5.5 USD/t, that sold to the coal-fired thermal power plant by outside organizations is 9.0~10.5 USD/t, and the carbon trading tax rate range is 6.0~6.2%. [ABSTRACT FROM AUTHOR]

Introducing carbon trading into electricity market can convert carbon dioxide into schedulable resources with economic value. However, the randomness of wind power generation puts forward higher requirements for electricity market transactions. Therefore, the carbon trading market is introduced into the wind power market, and a new form of low‐carbon economic dispatch model is developed. First, the economic dispatch goal of wind power is be considered. It is projected to save money and reduce the cost of power generation for the system. The model includes risk operating costs to account for the impact of wind power output variability on the system, as well as wind farm negative efficiency operating costs to account for the loss caused by wind abandonment. The model also employs carbon trading market metrics to achieve the goal of lowering system carbon emissions, and analyze the impact of different carbon trading prices on the system. A low‐carbon economic dispatch model for the wind power market is implemented based on the following two goals. Finally, the solution is optimised using the Ant‐lion optimisation method, which combines Levi's flight mechanism and golden sine. The proposed model and algorithm's rationality is proven through the use of cases. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The potential to sequester carbon by tree species in tropical regions such as Bangladesh is promising in regard to carbon sequestration (CS) potentiality and reducing CO2 emissions. This study focuses on perennial tree species within 488 hectares of Bangladesh Agricultural University (BAU) to assess the CS and to produce a C stock map for BAU. To compute the green and dry weight, weight of C and CO2 sequestration in the tree, a simplified methodology from the National Computational Science Institute of the Shodor Education Foundation was applied. A total of 27,543 trees comprising 424 species were taken into consideration, dividing the whole study area into four segments. B. ceiba and L. acidissima received the maximum and minimum green, dry, and C weight values. The topmost five carbon stock accumulating trees are M. longifolium (264,768 kg yr−1), S. mahagoni (257,290), A. lebbeck (118,310), M. indica (78,906), and T. grandis (51,744) whilst A. lebbeck is the major C stock accumulating tree within BAU. The top five CS potential are found for B. ceiba (181 kg), A. columnaris (139 kg), S. siamea (116 kg), F. elastica (113 kg), and F. religiosa (83 kg). To reveal the prospects of tree species in Bangladesh for emission reduction, the CS potential could be incorporated with the C trading scheme of the CDM (clean development mechanism) of the Kyoto Protocol. [ABSTRACT FROM AUTHOR]

Balancing sustainable economic growth and environmental protection in developing countries is an important way to mitigate climate change. Based on panel data from nine provinces along the Silk Road Economic Belt between 2004 and 2021, this paper takes Chongqing, a pilot city for carbon trading rights, as the experimental group and the remaining eight provinces as the control group; we mainly analyze the impact of the carbon emissions trading policy on Chongqing's carbon emissions and economic development after its implementation in 2013 using the difference-in-differences method (DID) and propensity score matching difference-in-differences method (PSM-DID). Then we use the synthetic control method (SCM) to test its robustness. The results showed that while maintaining the economic development speed, carbon trading helps to reduce carbon emissions. In addition, we also found that the economic activity effect and the energy intensity effect are the mediating effects of the carbon emissions reduction. Finally, taking the policy effect of the carbon emissions trading in Chongqing as a reference, this article confirmed the importance of aligning the carbon trading pathway with targeted green policies from the government. The government should drive the establishment of a regional carbon market in the nine provinces along the Silk Road Economic Belt, which could help to achieve sustainable development. [ABSTRACT FROM AUTHOR]

A virtual power plant (VPP) is an effective way to manage distributed energy resources. Virtual power plant cluster (VPPC) is constructed due to the increasing number of VPPs. It has great potential in carbon emission reduction through coordination between VPPs. Therefore, a dynamic dispatch priority model is proposed. The model adjusts the dispatch sequence of VPPs based on carbon emissions. The higher the carbon emissions, the lower the dispatch priority. The VPPC participates in carbon trading and the carbon trading cost is included in the optimization objective. There are still many uncontrolled distributed energy resources, e.g., wind power, out of the VPPC. The distributionally robust optimal method is used to deal with the uncertainty of wind power. Finally, this paper proposes a two-stage distributionally robust optimal model of VPPC considering carbon emission-based dynamic dispatch priority. This model can be solved by the column-and-constraint generation (C&CG) algorithm. A VPPC with four VPPs is used in case studies, which verify the economic benefit and low carbon of the proposed model.

Under the background of carbon emission abatement worldwide, carbon trading is becoming an important carbon financing policy to promote emission mitigation. Aiming at the emerging coupling among various energy sectors, this paper proposes a bi-level scheduling model to investigate the low-carbon operation of the electricity and natural gas integrated energy systems (IES). Firstly, an optimal energy flow model considering carbon trading is formulated at the upper level, in which carbon emission flow model is employed to track the carbon flows accompanying energy flows and identify the emission responsibility from the consumption-based perspective, and the locational marginal price is determined at the same time. Then at the lower level, a developed demand-side management strategy is introduced, which can manage demands in response to both the dynamic energy prices and the nodal carbon intensities, enabling the user side to participate in the joint energy and carbon trading. The bi-level model is solved iteratively and reaches an equilibrium. Finally, case studies based on the IEEE 39-bus system and the Belgium 20-node system illustrate the effectiveness of the proposed method in reducing carbon emissions and improving consumer surplus.

A low-carbon economic optimization dispatch model of integrated energy system is proposed to improve the low-carbon and economic efficiency of the integrated energy systems. Firstly, the waste heat generator with the organic Rankine cycle is introduced into the combined heat and power to decouple the combined heat and power operation, and a coupled model with an organic Rankine cycle, power to gas, combined heat and power and carbon capture system is established. Then, the ladder-type carbon trading mechanism is introduced to improve the low-carbon model. Finally, the function is established to minimize the sum of energy purchase costs, operation and maintenance costs, and environmental costs. The proposed integrated energy systems’ low-carbon economic dispatch model reduces the total operating cost by 18.9% and the carbon emissions by 83.7% by setting up different models for comparative analysis.

In order to enhance the carbon emission reduction capability and economy of the microgrid, a capacity optimization configuration method considering laddered carbon trading and demand response is proposed for a grid-connected microgrid consisting of photovoltaic, battery and hydrogen storage devices. Combined with the mathematical model and system structure of each unit in the microgrid, the integrated operation control strategy is determined in this paper. A demand response model containing three load types is developed to reduce the stress on the storage and generation side. A carbon-trading mechanism is introduced into the operating costs to establish a configuration model with annual overall profit and power supply reliability as the optimization objectives. The non-dominated sorting genetic algorithm II is used to optimize the capacity of each unit, and the effectiveness of this model is verified by taking a microgrid in a region in Northwest China as an example to analyze the impacts of ladder carbon trading and demand response on the configuration results and system operation.

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the context of carbon trading, energy conservation and emissions reduction are the development directions of integrated energy systems. In order to meet the development requirements of energy conservation and emissions reduction in the power grid, considering the different responses of the system in different time periods, a wind-hydrogen integrated multi-time scale energy scheduling model was established to optimize the energy-consumption scheduling problem of the system. As the scheduling model is a multiobjective nonlinear problem, the artificial fish swarm algorithm–shuffled frog leaping algorithm (AFS-SFLA) was used to solve the scheduling model to achieve system optimization. In the experimental test process, the Griewank benchmark function and the Rosenbrock function were selected to test the performance of the proposed AFS-SFL algorithm. In the Griewank environment, compared to the SFLA algorithm, the AFS-SFL algorithm was able to find a feasible solution at an early stage, and tended to converge after 110 iterations. The optimal solution was −4.83. In the test of total electric power deviation results at different time scales, the maximum deviation of early dispatching was 14.58 MW, and the minimum deviation was 0.56 MW. The overall deviation of real-time scheduling was the minimum, and the minimum deviation was 0 and the maximum deviation was 1.89 WM. The integrated energy system adopted real-time scale dispatching, with good system stability and low-energy consumption. Power system dispatching optimization belongs to the objective optimization problem. The artificial fish swarm algorithm and frog algorithm were innovatively combined to solve the dispatching model, which improved the accuracy of power grid dispatching. The research content provides an effective reference for the efficient use of clean and renewable energy. [ABSTRACT FROM AUTHOR]

Global climate change caused by excessive greenhouse gas（GHG） emissions has been widely concerned. Agricultural activities are the second largest source of GHGs emissions, so it is urgent to reduce agricultural GHGs emissions. Biochar, which has stable properties, abundant aromatic carbon and pores, is produced by pyrolysis of biomass under high temperature and limited oxygen conditions. The effect of biochar amendment on GHGs mitigation and soil carbon sequestration is excellent, and biochar application has the potential to participate in China’s ongoing carbon trading of voluntary emission reduction（VER）. However, the factors affecting the carbon sequestration and GHGs emission reduction effect of biochar are complicated, so it is necessary to systematically summarize the mitigation effect, influencing factors and research progress of biochar. This paper reviewed researches on the GHGs emission reduction and carbon sequestration effect of biochar through pot and field experiment as well as meta-analysis research. At the same time, CiteSpace software was used for visual analysis to explore the research hotspots and development trends in this field. The opportunities and challenges faced by biochar application projects participating in carbon trading were summarized based on the characteristics of domestic and foreign carbon trading market development and corresponding supporting policies. Corresponding solutions were also provided in this study, which offered scientific guidance and useful reference for the development of carbon sequestration and GHGs emission reduction research of biochar and the successful participation of biochar application projects in carbon trading. [ABSTRACT FROM AUTHOR]

Following China and the United States, India is the third highest CO2 emitter in the world. With its fast rising population and an industry primarily reliant on coal and oil, the country's emissions will continue to rise unless appropriate measures are taken. In India generally the carbon sequestration is done by storing CO2 in sedimentary basins where it gets capped by the impermeable cap rocks. The study aims to unfold the other techniques of carbon sequestration in subsurface formations, except for narrating the different types of carbon capture and sequestration techniques along with its storage in different types of environments. For instance, abiotic and biotic environments for CO2 sequestration. It further talks about carbon injections of oceanic, geological, and terrestrial types, to name just a few. Types of carbon emission sources are discussed too. In this paper three different approaches are described for carbon mitigation, namely CarbFix, CO2 Plume technology and Carbon Trading. A prefeasibility study was done in order to implement the three techniques in Dholera geothermal region in Gujarat, India. In literature review, it can be seen how the three techniques can help in permanent mitigation of captured carbon through carbonate mineralization, power generation and industrial applications. For any project government and public participation is important. In this regard the study gives a brief understanding about the steps to be taken by government and the public to promote such projects for carbon mitigation. Besides, the steps to be taken in such projects for health and risk assessment were talked about in literature review too. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Forest ecosystem, as a predominant component of terrestrial ecosystems in view of carbon sinks, has a high potential for carbon sequestration. Accurately estimating the carbon sequestration rate in forest ecosystems at provincial level, is a prerequisite and basis for scientifically formulating the technical approaches of carbon neutrality and the associated regulatory policies in China. However, few researches on future carbon sequestration rates (CSRs) for Chinese forest ecosystems for provincial-level regions (hereafter province) have been reported, especially for forest soils. In this study, we quantitatively assessed the carbon sequestration rates of existing forest ecosystems of all the provinces from 2010 to 2060 using the Forest Carbon Sequestration model (FCS), in combination with large quantities of field-measured data in China under three future climate scenarios (RCP2.6, RCP4.5, and RCP8.5). Results showed that CSRs across provinces varied from 0.01 TgC a−1 to 36.74 TgC a−1, with a mean of 10.09 ± 0.43 TgC a−1. Inter-provincial differences have been observed in forest CSRs. Regarding the spatial variations in CSRs on a unit area basis within provinces, the eastern region provinces have a larger capacity for sequestration than the western region, while the western region has greater CSR per unit GDP and per capita. Moreover, there are significant negative correlations between the CSRs per capita in each province and the corresponding GDP per capita, under the assumption that GDP per capita is constant in the future across provinces. In summary, there is a significant regional imbalance in CSR among provinces. Special technological and policy interventions are required to realize carbon sink potential sustainably. An overlap in China's poorer areas and areas with stronger carbon sinks has indicated that existing policies to support traditional carbon trading are insufficient. Regulatory measures such as "regional carbon compensation" must be adopted urgently in line with the Chinese characteristics, so that people in western or underdeveloped regions can consciously strengthen forest protection and enhance forest carbon sinks through coordinated regional development while ensuring that China's forests play a greater role in carbon neutrality strategies. [ABSTRACT FROM AUTHOR]

People are increasingly paying much attention to battery technology, especially the zinc-nickel battery and the lithium battery, for solving energy shortages and environmental contamination. Meanwhile, the drastic change in the external outside environment has brought a huge challenge to manage the battery industry chain. Therefore, in the uncertain external environment, the study of supply chain competition between lithium battery and new nickel battery manufacturers is the focus of this paper. We build a cooperative game model under the demand disturbance and a non-cooperative game under the background of product promotion. The results show that (i) the price set by the manufacturer increases with technical improvement when consumers are more sensitive to the technical level. (ii) The optimal price of all manufacturers will drop as the CETRC (carbon emission technology renewal coefficient) increases. (iii) The price of zinc-nickel batteries will be higher than that of lithium battery as the market promotion rate is in the middle range. In the model, the supply chain determines different optimal prices according to the different ranges of the demand disturbance. [ABSTRACT FROM AUTHOR]

In order to promote the synergistic green and low-carbon development of energy supply-demand sides, this paper uses the complex network evolutionary game to explore the impact of supply side decision-making on the diffusion of low-carbon transformation on demand-side under low-carbon policies. The result shows that: (1) It is feasible for the government to use carbon trading as a policy tool to promote synergistic low-carbon transformation on supply-demand sides, but it is constrained by the carbon price trend. (2) Relying only on the direct supply of clean energy from the energy supply to demand side is not enough to promote synergistic development, and the government needs to guide the both sides to cooperate in the construction of renewable energy power plants. (3) When carbon price is on an upward trend, the government needs to push forward the low-carbon transformation process on supply side, and form the low-carbon transformation of demand side driven by supply side. (4) When carbon price is on a downward trend, the government needs to guide the supply side to bear part of the transformation cost pressure on the demand side, and at the same time give more transformation subsidies. • Dynamic carbon prices are introduced to complex network evolutionary games. • Energy supply side decisions will determine low-carbon transformation of demand side. • Synergistic development on energy supply-demand sides requires carbon trading mechanism. • Cooperative transformation of supply-demand sides needs to consider carbon price trends. [ABSTRACT FROM AUTHOR]

With the development of the energy and carbon markets, it has become a trend for multiple virtual power plants (MVPP) that aggregate distributed resources from different regions to participate in market trading through cooperative operation. In order to study the energy-carbon interactions between VPPs and the supply-demand interactions for MVPP and users, this paper introduces a load aggregator (LA) and establishes a cooperative alliance consisting of MVPP and LA. Firstly, a carbon emission allowance allocation and transaction mechanism for MVPP is proposed based on the modified Shapley value method, which considers the impact of energy interactions within the alliance on the carbon emissions. Then, a cooperation model for the MVPP-LA alliance is established based on Nash bargaining theory, and it is decomposed into two subproblems of the maximal alliance benefits and the optimal benefit distribution. In terms of benefit distribution, this paper modifies the bargaining mechanism based on the contribution of each VPP to the alliance benefit. A dynamic penalty factor-based alternating direction method of multipliers (DP-ADMM) is used to solve the two subproblems in a distributed manner. Finally, the validity of the proposed trading mechanism, allocation method and solution algorithm are verified through several cases. • A contribution-based bargaining model is proposed for a fair benefit distribution. • A modified CEA allocation mechanism for MVPP cooperation is proposed. • A combined carbon trading mechanism is developed. • A DP-ADMM is adopted to solve the cooperation problem. [ABSTRACT FROM AUTHOR]

The integrated energy system (IES) can promote the accommodation of renewable energy, achieve efficient energy utilization, and reduce carbon emissions, which is a crucial direction of energy system transformation development. This study proposes an optimal design and scheduling operation framework of photovoltaic-wind-hydrogen-based IES coupled with multiple heterogeneous energy flows and energy storages for urban communities. The carbon trading mechanism and uncertainty of renewable energy output are taken into account, where the uncertainty can be tackled by fuzzy chance constrained programming (FCCP) method through a clear equivalent transformation to the fuzziness of forecast error. Then, a case study with the minimum sum of multiple costs over a day-ahead planning horizon is employed to validate the applicability of the proposed IES, in which various operation scenarios regarding system configuration and confidence levels with comprehensive performance evaluation are investigated and analyzed. The simulation results indicate that compared with the reference system, primary energy saving rate, total cost saving rate, and CO 2 emission reduction rate of the proposed IES are 45.18%, 11.39% and 52.17%, respectively. Besides, as the confidence level increases, the overall performance corresponding to evaluation indicators shows a downward tendency. Moreover, a reasonable carbon price and lower natural gas price will improve the overall benefits. The proposed model can be helpful for decision-makers to trade off the pros and cons between system performance and risk and provide a reference for similar studies and applications. [Display omitted] • A photovoltaic-wind-hydrogen-based integrated energy system is proposed. • Carbon trading and uncertainty with fuzzy chance constrained programming are considered. • Impacts of system configuration, confidence levels and market factors are analyzed. • Managers should weigh the pros and cons between system performance and risk. • Carbon trading can reduce carbon emission and accelerate renewable energy absorption. [ABSTRACT FROM AUTHOR]

China has implemented a variety of energy efficiency policies to achieve energy saving and carbon abatement targets. While the national carbon market has been launched and China has opted to give market-oriented policies a greater role in achieving net zero, energy efficiency policies still constitute a significant portion of the policy mix. However, the substantial drawback of energy efficiency policies compared to carbon trading, the rebound effect, has made energy efficiency policies debatable. It is crucial to precisely understand the magnitude of the rebound effect to design and implement effective energy policies. Our study estimates and compares the direct energy rebound and output expansion effects in China's manufacturing and service sectors using firm-level data from 2013 to 2016 and employing panel regression analysis. We also analyze the impact of firm characteristics such as ownership status, geographical location, and industry type on enterprises' rebound effects. We found a 33.5% direct rebound effect and a 19.3% output expansion effect in the manufacturing sector. In the service sector, the direct energy rebound effect was 57.9%, a larger one than the manufacturing sector. We also estimate direct energy rebound effects for key manufacturing and service enterprises. Our findings reveal that key manufacturing enterprises exhibit a larger rebound effect compared to the overall manufacturing sector, while key service enterprises show a smaller rebound effect than the overall service sector. Public, foreign, and heavy service enterprises show a smaller energy rebound effect, while northeastern manufacturing and service enterprises exhibit a larger rebound effect. We suggest that China's carbon market should also cover key service enterprises. For those below the threshold, enhancing energy management is essential to mitigate the rebound effect. Aligning with carbon emission cap targets, rather than relying solely on energy efficiency policies, could more effectively achieve energy savings and carbon abatement. • Direct energy rebound effects are identified in manufacturing (33.5%) and service (57.9%) sectors. • Output expansion drives rebound energy use in high-consumption firms. • Rebound effect weakens the effectiveness of China's energy efficiency policies. • Explore the impacts of firm-level characteristics on energy rebound effects in China. • We suggest that China's carbon emission trading scheme cover key service enterprises. [ABSTRACT FROM AUTHOR]

• The load response transfer rate and dynamic incentive electricity price are considered in the model of the virtual power plant. • The consumption surplus value function is added to the carbon cost model with carbon intensity as the index. • The incentive electricity price is linked with the changing carbon price by taking the response transfer quantity as a bridge. • An intra-day rolling optimal regulating model is established on the basis of the equipment output deviation penalty. Adapting virtual power plants (VPPs) to the development of new power systems has gradually become a trend. Meanwhile, the economical and effective use of demand-side resources in VPPs has become a research hotspot in the field of new energy. This paper proposes a low-carbon operation strategy with progressive demand response (DR). A DR model id established by evaluating the scheduling potential of low-carbon and flexible loads and the DR transfer of different users motivated by incentive mechanisms. Because the changing carbon price in carbon trading also affects the response transfer amount, it is beneficial to reduce the operating cost of the energy system by using consumers' surplus value according to consumer psychology to guide energy users to participate in DR. Finally, wind, light, user load data and VPP internal unit output are optimized in rolling mode over multiple time scales, and the optimal adjustment results of the previous day are taken as the basis. At the same time, the output deviation penalty function is added to further reduce the system cost. The nonlinear model of DR cost is transformed into a mixed integer linear model, which is modeled on MATLAB software and solved by a CPLEX optimization solver. The case analysis shows that the progressive DR strategy may increase the total operating cost of the system, but reduce the cost of the carbon emission. The proposed model and method can not only improve the feasibility and effectiveness of market supervision strategy, but also provides a useful reference for operators and demand-side users in energy systems to choose strategies. [ABSTRACT FROM AUTHOR]

• A operational optimisation strategy for S-CCHP systems is proposed. • Multiple objectives: energy, economic and environmental impacts. • A dynamic, annual, all-season model has been developed. • PV/T panels provide 87.11 % of the electricity demand in the summer. • Cutting costs by 16.15% and CO 2 by 57.79%. The Solar Combined Cooling, Heat, and Power (S-CCHP) system offers a promising solution to the energy crisis and environmental concerns. Its operation optimisation is essential due to intermittent solar irradiation. However, previous studies have concentrated on the "electricity-heating" subsystem and economic costs, with less emphasis on the integrated system's broader benefits and environmental impact. This study introduces an operational optimisation approach across "electricity-heating-cooling-gas" subsystems based on the design extension of the Residential Building Heating and Electricity Production (RESHeat) system. Specifically, the approach optimises operation from both the demand and supply sides, incorporating the demand response (DR) and Ladder Carbon Trading (LCT) on the demonstration in Limanowa, Poland, to balance economic and environmental impacts. The results show that the optimised electricity is reduced by 0.71 % per day while heating and cooling demands rise by 0.57% and 0.91%. PV/T panels provide 87.11% of electricity, with excess sold back to the grid in summer. DR combined with LCT in the extension design contributed to cutting costs by 16.15 % and CO 2 by 57.79% compared with the initial design, underscoring the efficacy of collaborative operational in enhancing both economic and environmental performance. [ABSTRACT FROM AUTHOR]

• A Certified Emission Reduction calculation method for hydropower plants. • A Certified Emission Reduction embedded operational optimization model for terraced hydropower plants. • An NSGA-Ⅱ based multi-objective optimal scheduling model solution method specialized for hydropower Certified Emission Reduction projects. • An analysis of five typical optimized operational scenarios for terraced hydropower plants. Given the escalating issue of greenhouse gas emissions, the Certified Emission Reduction (CER) mechanism has been further developed, which provides additional revenues and improves the efficiency of renewable energy projects including terraced hydropower plants. However, limited literature integrates the role of the CER scheme into the optimal scheduling of the terraced hydropower plants. To establish a low-carbon economical operation strategy for terraced hydropower plants considering CER, we first specify the CER calculation method for hydropower plants using emissions baseline analysis. Then, a CER-embedded optimal scheduling model for terraced hydropower plants is established. Therefore, the benefits of CER are combined to the consideration of the overall benefits of hydropower plants, which guides the hydropower plant generation operation strategy. Ultimately, we focus on five typical operating scenarios for terraced hydropower where generation benefits, different CER prices, power subsidies for the summer peak load period, and extreme weather factors with dry water are respectively considered. Further, a comparative analysis of individual factor impacts is conducted in a pairwise manner. Results demonstrate that the proposed model can improve the comprehensive efficiency of the terraced hydropower plants by 18.45 % while the water discarded can be reduced by about 0.413 million m³. [ABSTRACT FROM AUTHOR]

• Introducing the DNO as the coordinator and operator of the IEM cluster. The Stackelberg game theory is used to describe the unequal market positions and the vertical trading system between the two parties. • The model optimizes the electricity interaction prices between each IEM and establishes a cooperative game model based on Nash bargaining theory to simulate the electricity cooperation and interaction relationships among them, facilitating a fair distribution of benefits between individual entities and the cluster. • Building upon the established optimization model, carbon trading mechanisms and demand response models are introduced to limit the carbon emissions of the IEMs. This approach aims to minimize carbon emissions while maximizing the economic objectives of the multiple IEMs, thereby enhancing the motivation of each IEM and achieving perfect coordination between environmental and economic aspects. The integrated energy microgrid (IEM) plays a crucial role in supporting energy structural transformation and achieving carbon peaking and carbon neutrality goals. However, IEM clusters, which comprise various forms of IEMs, often share connections with the same distribution network operator (DNO), leading to competitive tensions both within the cluster and between the cluster and the DNO. To mitigate these conflicts and promote low-carbon, cost-effective operations, this study introduces a double-layer game model. This model aims to minimize operational costs and maximize carbon emission reductions. The external layer applies the Stackelberg game with the DNO as the leader and the IEM cluster as the follower. The internal layer employs cooperative game theory to model interactions among multiple IEMs. Optimal electricity trading and pricing for each entity are determined using a combination of the bisection method and the alternating direction method of multipliers (ADMM). Additionally, a carbon trading mechanism is integrated into the model to balance economic and environmental objectives. The results indicate that the proposed double-layer game model facilitates a mutually beneficial scenario for both the DNO and the IEMs in terms of low carbon emissions and economic efficiency. This model provides a practical framework for effectively managing and coordinating interactions among multiple IEMs, thereby ensuring simultaneous economic and environmental advantages. [ABSTRACT FROM AUTHOR]

Currently, the ecological problems caused by the greenhouse effect are growing more serious, and implementing carbon sequestration methods is an effective way to address them. Arid and semi-arid desert areas have tremendous potential as carbon sinks, and artificial forests in these areas play an important role in absorbing and sequestering carbon dioxide. This study selected three main species of artificial protective trees along the Tarim Desert Highway—Haloxylon ammodendron (C.A.Mey.) Bunge, Calligonum mongolicum Turcz. and Tamarix chinensis Lour.—and evaluated them for their carbon sequestration, oxygen release capacity, and economic benefits using Pn (net photosynthetic rate) and biomass methods. The results showed that the average daily Pn value and carbon sequestration and oxygen release per unit leaf area of T. chinensis were significantly higher than those of H. ammodendron and C. mongolicum (p < 0.05). The total carbon storage of the three shelterbelts was 15.41 × 104 t, and the carbon storage of H. ammodendron was significantly higher than that of C. mongolicum and T. chinensis (p < 0.05). According to the net photosynthetic rate method, the annual carbon sequestration and oxygen release of the shelter forest is 6.13 × 104 t a−1, and the transaction price is CNY 13.73 million a−1. The total amount of carbon sequestration and oxygen release of the shelter forest obtained via the biomass method is 97.61 × 104 t, and the transaction price is CNY 218.77 million. This study conducted research on the carbon sequestration capacity of protective forests along the Tarim Desert Highway located in an extremely arid region. It highlights the significant contribution of these protective forests in terms of carbon storage, playing a crucial role in promoting ecological restoration and sustainable development in arid areas. Additionally, this study provides a scientific basis for estimating carbon storage and promoting the sustainable management of artificial forests in arid desert regions.