A Low-Carbon Generation Expansion Planning
Model Considering Carbon Trading and Green
Certificate Transaction Mechanisms

Huang, Yuansheng; Hu, Jianjun; Yang, Yingqi; Yang, Lei; Liu, Shijian

doi:10.15244/pjoes/106025

Cited by 13 publications

(5 citation statements)

References 29 publications

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“…By the end of 2022, the balance of green credit in China will be RMB 22.03 trillion yuan, and the new issuance scale of green bonds will be about RMB 983.899 billion yuan, with a stock scale of about RMB 3 trillion yuan. As an important market tool for "turning green mountains into golden mountains", green finance allows financial water to continuously nourish green mountains and is a catalyst and gas pedal for China's low-carbon transformation and high-quality development [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Research on the coupling and coordination index of green finance and high-quality economic development based on matrix modeling

Hao

2024

Applied Mathematics and Nonlinear Sciences

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The traditional way to calculate the coupling index of green finance and high-quality economic development has the problems of ignoring spatial spillover effects and regional heterogeneity. Based on the spatial measurement matrix, this paper calculates the coupling index of the two. Firstly, the index system is established according to the characteristics of green finance and high-quality economic development, then the entropy weight method is used to calculate the weight, combined with the Moran index to calculate the regional differences, and finally, the spatial measurement matrix is used to derive the final results. After the model was established, data on China’s green finance and high-quality economic development from 2016 to 2022 were collected as samples, and the coupling analysis was launched and tested using Granger causality. The calculation results show that Shanghai has the highest level of high-quality economic development from 2016 to 2022, steadily increasing from 0.635 to 0.819 in 2022. The global Moran index has been maintaining a level of 5% for all years. The LR index of SDM/SEM is 51.39. The coupling index of the measure of green finance is 0.1395, and the coupling index of the level of high-quality economic development is 0.1873. The Granger causality assumption chi-square for the uncorrelation of the two is 6.382 and 3.085, respectively, with p-values of 0.004 and 0.091. There is a correlation between them that is positive.

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Section: Introductionmentioning

confidence: 99%

Research on the coupling and coordination index of green finance and high-quality economic development based on matrix modeling

Hao

2024

Applied Mathematics and Nonlinear Sciences

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“…The marketization level enhanced the promoting effect of CARBON ETS on energy efficiency. Literature [12] finds that both carbon trading scheme and green certificate trading scheme can increase installed capacity of renewable energy and reduce carbon emissions. When both mechanisms are introduced, the proportion of renewable energy installed will be the highest and carbon emissions will be the lowest.…”

Section: Introductionmentioning

confidence: 99%

The Impact of China’s Carbon Emission Trading Policy on Green Total Factor Productivity – Influence Analysis Based on Super-EBM and Multiple Mediators

Li¹,

Huang²,

Wu³

2022

Pol. J. Environ. Stud.

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Can China's carbon trading policy promote regional green total factor productivity? What are the specific influencing processes and mechanisms between the two? In this paper, we construct an indicator framework for China's green total factor productivity from the perspective of green development, which comprehensively considers various inputs and outputs. This paper uses a more scientific Super-EBM model considering the mixed distance to accurately measure the regional green total factor productivity in China. The static and dynamic effects and multiple mediating effects of carbon trading policy on green total factor productivity were studied by using DID model combined with stepwise regression method. The robustness of the results was tested by parallel trend test and placebo test. The mediating effects of total energy consumption, energy consumption structure, technological innovation and the moderating effects of financial development level and intellectual property protection degree are studied. The results show that carbon trading policy significantly improves China's regional green total factor productivity. The effect of carbon trading policy on green total factor productivity in pilot areas increased to decreased; Total energy consumption and energy consumption structure have a partial intermediary effect on the relationship between carbon emission trading policy and regional green total factor productivity in China, while technological innovation has a masking effect. Regional financial development level and intellectual property protection intensity play a moderating role in the relationship between carbon emission trading policy and regional total factor productivity. Based on the above conclusions, some suggestions are put forward for the improvement of China's carbon trading policy system.

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“…The GEP model considered the capacity margin and LOLE to guarantee the security and reliability of the power system under the presence of RES uncertainties 29‐31 . A peaking reserve is used to tackle the uncertainty of wind power 32 .…”

Section: Introductionmentioning

confidence: 99%

“…References 2,33 proposed a reserve margin as an appropriate solution to cope with the uncertainty problem. The previously mentioned efforts 2,29‐33 proposed only the reserve margin solution to cope with the uncertainty problem.…”

Section: Introductionmentioning

confidence: 99%

“…The GEP model considered the capacity margin and LOLE to guarantee the security and reliability of the power system under the presence of RES uncertainties. [29][30][31] A peaking reserve is used to tackle the uncertainty of wind power. 32 Reference 2 described the RES implementation within the GEP model as thermal power plants with zero fuel cost and a high forced outage rate (FOR).…”

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Robust generation expansion planning considering high penetration renewable energies uncertainty

Abdalla

Adma

Ahmed

2020

Engineering Reports

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The proper optimal generation expansion planning (GEP) should meet the reliability criteria requirements over a planning horizon under the presence of uncertainties. The intermittent nature of renewable energy sources (RES) introduces an enormous uncertainties impact within the planning model. A simulation model for RES uncertainty is developed using the capacity factor (CF) of the RES historical data. The RES simulation model is handled via the probability density function (PDF). The uncertainty parameter of different RES is described as a flexible polyhedral uncertainty set and incorporated within the proposed GEP model. The influence of different uncertainty scenarios for each RES uncertainty on the GEP model can be analyzed separately. The RES uncertainty scenarios are predefined and incorporated within the proposed GEP model through a proposed parameter named as a confidence level. The proposed confidence level parameter is beneficial to the power system planner to control the degree of robustness. Different GEP results are presented for various RES uncertainty scenarios. Three methods are proposed as appropriate solutions to deal with the RES uncertainty impact. The most economical method among the three proposed methods is determined by developing an objective function tailored to achieve the optimality of the economic factor.

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A Low-Carbon Generation Expansion Planning Model Considering Carbon Trading and Green Certificate Transaction Mechanisms

Cited by 13 publications

References 29 publications

Research on the coupling and coordination index of green finance and high-quality economic development based on matrix modeling

Research on the coupling and coordination index of green finance and high-quality economic development based on matrix modeling

The Impact of China’s Carbon Emission Trading Policy on Green Total Factor Productivity – Influence Analysis Based on Super-EBM and Multiple Mediators

Robust generation expansion planning considering high penetration renewable energies uncertainty

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