scholarly journals Research on carbon emission quota allocation in power industry

2019 ◽  
Vol 300 ◽  
pp. 042069
Author(s):  
Meng Li ◽  
Peng Wang
Keyword(s):  
Carbon Emission ◽  
Power Industry ◽  
Emission Quota ◽  
Quota Allocation

scholarly journals Research on China’s Regional Carbon Emission Quota Allocation in 2030 under the Constraint of Carbon Intensity

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yuan Zhang
Keyword(s):  
Carbon Dioxide ◽  
Information Entropy ◽  
Carbon Emission ◽  
Entropy Method ◽  
Carbon Intensity ◽  
Maximum Deviation ◽  
Carbon Trading ◽  
Emission Quota ◽  
Quota Allocation ◽  
Deviation Method

To achieve the goal of carbon dioxide emission reduction in 2030 promised to the United Nations, China unified the Carbon Trading System (CTS) in 2017 since carbon dioxide quota allocation is one of the core issues of carbon trading. It is imperative to establish a flexible carbon quota allocation system based on the unbalanced characteristics of resource endowment and economic development in different regions. Unlike previous distribution research, this paper considers five principles, which are fairness principle, efficiency principle, feasibility principle, development principle, and innovation principle. The maximum deviation method is used to research the carbon emission quota allocation in 30 provinces of China, and the results are compared with those under the single principle and the information entropy method. The results reveal that the distribution under the single principle is severely unbalanced, making the region have a strong sense of relative deprivation. The maximum deviation method is better than the information entropy method to achieve carbon intensity by 2030. It is also conducive to promote the coordinated development of the regional economy, narrow the poverty gap, and achieve sustainable development.

scholarly journals Use of BP Neural Networks to Determine China’s Regional CO2 Emission Quota

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yawei Qi ◽  
Wenxiang Peng ◽  
Ran Yan ◽  
Guangping Rao
Keyword(s):  
Co2 Emissions ◽  
Co2 Emission ◽  
Carbon Emission ◽  
Emission Trading ◽  
Benchmark Model ◽  
Emission Quota ◽  
Quota Allocation ◽  
Carbon Emission Trading ◽  
Feature System ◽  
Trading Policy

China declared a long-term commitment at the United Nations General Assembly (UNGA) in 2020 to reduce CO2 emissions. This announcement has been described by Reuters as “the most important climate change commitment in years.” The allocation of China’s provincial CO2 emission quotas (hereafter referred to as quotas) is crucial for building a unified national carbon market, which is an important policy tool necessary to achieve carbon emissions reduction. In the present research, we used historical quota data of China’s carbon emission trading policy pilot areas from 2014 to 2017 to identify alternative features of corporate CO2 emissions and build a backpropagation neural network model (BP) to train the benchmark model. Later, we used the model to calculate the quotas for other regions, provided they implement the carbon emission trading policy. Finally, we added up the quotas to obtain the total national quota. Additionally, considering the perspective of carbon emission terminal, a new characteristic system of quota allocation was proposed in order to retrain BP including the following three aspects: enterprise production, household consumption, and regional environment. The results of the benchmark model and the new models were compared. This feature system not only builds a reasonable quota-related indicator framework but also perfectly matches China’s existing “bottom-up” total control quota approach. Compared with the previous literature, the present report proposes a quota allocation feature system closer to China’s policy and trains BP to obtain reasonable feature weights. The model is very important for the establishment of a unified national carbon emission trading market and the determination of regional quotas in China.

scholarly journals A Two-Stage Algorithm of Locational Marginal Price Calculation Subject to Carbon Emission Allowance

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2510 ◽  
Author(s):  
Mingxing Wu ◽  
Zhilin Lu ◽  
Qing Chen ◽  
Tao Zhu ◽  
En Lu ◽  
...  
Keyword(s):  
Power Systems ◽  
Electricity Markets ◽  
Carbon Emission ◽  
Optimal Solution ◽  
Pareto Optimal Solution ◽  
Pareto Optimal ◽  
Emission Quota ◽  
Quota Allocation ◽  
Locational Marginal Price ◽  
Marginal Price

To analyze the effect of carbon emission quota allocation on the locational marginal price (LMP) of day-ahead electricity markets, this paper proposes a two-stage algorithm. For the first stage of the algorithm, a multi-objective optimization model is established to simultaneously minimize the total costs and carbon emission costs of power systems. Hence, an evenly distributed Pareto optimal solution can be solved effectively by means of the normalized normal constraint method. For the second stage, a tracing model is built with the goal of minimizing the total costs of power systems and satisfying the constraints generated based on the Pareto optimal solution obtained from the first stage. Furthermore, the influence of carbon emission quota allocation on the LMP of electricity markets is analyzed, and different schemes to allocate carbon emission quotas are evaluated on a real 1560-bus and 52-unit system.

scholarly journals Quota Allocation for Carbon Emissions in China′s Electric Power Industry Based Upon the Fairness Principle

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2256 ◽  
Author(s):  
Ming Meng ◽  
Lixue Wang ◽  
Qu Chen
Keyword(s):  
Electric Power ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Electric Power Industry ◽  
Power Industry ◽  
Total Carbon ◽  
Carbon Mitigation ◽  
Power Sector ◽  
Quota Allocation ◽  
Electric Power Sector

As an essential measure to mitigate the CO2 emissions, China is constructing a nationwide carbon emission trading (CET) market. The electric power industry is the first sector that will be introduced into this market, but the quota allocation scheme, as the key foundation of market transactions, is still undetermined. This research employed the gross domestic product (GDP), energy consumption, and electric generation data of 30 provinces from 2001 to 2015, a hybrid trend forecasting model, and a three-indicator allocation model to measure the provincial quota allocation for carbon emissions in China′s electric power sector. The conclusions drawn from the empirical analysis can be summarized as follows: (1) The carbon emission peak in China′s electric power sector will appear in 2027, and peak emissions will be 3.63 billion tons, which will surpass the total carbon emissions of the European Union (EU) and approximately equal to 2/3 of the United States of America (USA). (2) The developed provinces that are supported by traditional industries should take more responsibility for carbon mitigation. (3) Nine provinces are expected to be the buyers in the CET market. These provinces are mostly located in eastern China, and account for approximately 63.65% of China′s carbon emissions generated by the electric power sector. (4) The long-distance electric power transmission shifts the carbon emissions and then has an impact on the quotas allocation for carbon emissions. (5) The development and effective utilization of clean power generation will play a positive role for carbon mitigation in China′s electric sector.

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