Carbon Emission Quota Research Articles

Low-carbon economic dispatch and energy sharing method of multiple Integrated Energy Systems from the perspective of System of Systems

This paper mainly focuses on the low-carbon economic dispatch and energy sharing method of multiple Integrated Energy Systems (IES) from the perspective of System of Systems. First, a new model of carbon quota allocation and trading considering carbon balance and carbon sharing among multiple systems is established, and a low-carbon economic dispatch and energy sharing framework based on efficient utilization of regional carbon quota is proposed. Then, a Stackelberg game-based optimization model is proposed for energy service provider (ESP) and IES groups based on the collaborative optimization of IES and carbon transaction cost, where the ESP acts as a leader who chooses proper interactive price to promote energy sharing within the system while IES serves as a follower who minimizes its operation cost in response to the interactive price set by ESP. Moreover, the existence and uniqueness of the Stackelberg equilibrium are analyzed and a decentralized solution algorithm is suggested to reach the goal of optimal energy sharing and optimal operation. Finally, the case study of a joint energy sharing system containing three regional IESs are provided to show the effectiveness of the proposed method. The results demonstrate that the proposed method can not only increase profit of ESP and IES, but helpful to promote the optimal utilization of energy resources and the optimal distribution of carbon emission quota among energy systems.

Allocation of carbon emission quotas among provinces in China: efficiency, fairness and balanced allocation.

This paper constructs the ZSG-SBM model, comprehensive fairness allocation model, and balance allocation model from the perspectives of efficiency, fairness, and balance. Making use of the actual input-output data of China's provincial economic system in 2019, and the above three models to study the reasonable scheme of China's provincial carbon emission quota allocation in 2019. The results show that ZSG efficiency allocation can significantly improve the carbon emission efficiency of inefficient provinces, and the carbon emissions of inefficient provinces after allocation reach the efficiency frontier. The carbon emission quota of 16 provinces which located in the central and western regions of China with underdeveloped economy and relatively low carbon emission efficiency need to be decreased, while the eastern coastal provinces with more developed economy and high carbon emission efficiency in China should increase their carbon emission quota. On the one hand, comprehensive fairness allocation reduces the carbon emission reduction target constraints of economically underdeveloped provinces; on the other hand, it strengthens the carbon emission reduction target constraints of low-carbon technology backward provinces. As a result, the carbon emission quota of economically developed provinces and provinces with high carbon intensity per unit GDP is reduced in this method. The result of balancing efficiency and fairness lies between ZSG efficiency allocation and comprehensive fairness allocation. In order to alleviate the huge pressure on the emission reduction of provinces with low actual carbon emission efficiency under the ZSG efficiency allocation mode, the Chinese government can gradually increase the weight of ZSG efficiency allocation results, and finally adopt a complete ZSG efficiency allocation scheme in the carbon peak year to realize the transformation of low-carbon economy.

Forest Carbon Sequestration Demand Based on Emissions Reduction in China’s Thermal Power and Steel Industries: Implications for Tobacco Industry

Objectives: China is a large country of tobacco production and consumption. In the construction and development of carbon market, the tobacco industry is expected to realizing energy conservation and emission reduction by participating in carbon trading, especially focusing on the forest carbon sequestration demand based on emissions reduction. Compared with the tobacco industry, the heavy pollution industries participate in the carbon market more deeply and widely. Therefore, this paper takes thermal power and steel industries as the research object, in order to provide some implications for the emission reduction path of tobacco industry. It considers the CO2 emissions intensity and marginal abatement costs (MAC) between China’s thermal power and steel industries during 2005–2017, and quantifies the forest carbon sequestration (FCS) demand level of these two industries to account for the role and potential of the forests for China’s green and low-carbon development. Methods: It uses a logistic algorithm to reflect the relationship among FCS demand, MAC and other influencing factors, and the cloud model to simulate FCS demand in different scenarios. Results: It shows an average decline of 54.06% and 56.05% in the carbon intensity of the two industries over the period. The average annualMAC are 11.82–25.55 CNY/ton across pilots, while the annual FCS demand expectation is 35 and 45 million tons for the thermal power and steel industries, respectively. If the MAC increases by 10%, the annual FCS demand will increase to 90 and 50 million tons, respectively. Other factors such as the prices of carbon emissions rights, carbon emission quotas, and industry output show little effect on FCS demand. Conclusion: The economic and technological efficiency of emissions reduction in different industries should be considered comprehensively, and that the consumer to producer subsidy for FCS in the carbon market should be adjusted for resource distribution optimization. This would promote emissions reduction, stimulate FCS demand, and improve the carbon market mechanism.

Stackelberg game based co-firing biomass with coal under carbon cap-and-trade regulation

Coal-fired power industry is under enormous pressure to accomplish carbon emission reduction targets. This paper proposes a bi-level multi-objective model for co-firing biomass with coal under carbon cap-and-trade regulation which considers a leader-follower Stackelberg game between the authority and the coal-fired power plants. The upper level regards social welfare maximization and allocation satisfaction maximization as its multiple objectives, while the lower level attempts to maximize the profits of each coal-fired power plant. The inherent uncertainty prompts the motivation for employing fuzzy set theory to characterize the uncertain parameters and determine their exact values. A case study from Shandong Province, China is provided to demonstrate the practicality and efficiency of the optimization model. [Formula: see text]-constraint method and interactive algorithm are used to solve the model, and furthermore the solutions associated with different free carbon emission quota levels and minimal allocation satisfactions have been generated to examine the influences. Based on the analysis and discussion, the methodology can meet the carbon emission reduction goals and transit to a lower-carbon power generation. It also assists the decision makers to develop desired quota allocation strategy in accordance with their attitudes and actual conditions.

Low‐carbon economic operation for integrated energy system considering carbon trading mechanism

AbstractCarbon trading mechanism is an effective means to control greenhouse gas emissions. This paper focuses on the low‐carbon economic operation of the integrated energy system under carbon trading mechanism in China. The integrated energy system includes the energy storage, ground source heat pump, and other equipment. The objective of this paper was to minimize the annual total cost of the system considering the carbon trading cost and study the operation modes under different carbon trading prices by commercial optimization software. The simulation results show the operation modes in summer are changed obviously with the increase of the carbon trading prices, while the operation modes in winter basically are not changed with the fluctuation of the carbon trading prices; under the carbon trading mechanism, the integrated energy system can not only reduce the carbon emissions, but also reduce the annual total cost through carbon trading, which shows its advantages and good development prospect. In addition, the setting of the carbon emission quota has a direct impact on the economy of the enterprises. Furthermore, the ground source heat pump and the electric refrigeration units can stabilize the fluctuation of the equipment output caused by the change of natural gas prices in this integrated energy system.

A performance analysis framework for carbon emission quota allocation schemes in China: Perspectives from economics and energy conservation

Carbon emission quota allocation plays a critical role in carbon emission reduction in an efficient and economic manner. However, the scientific assessment of carbon quota allocation schemes and thus making a reasonable decision depending on preference still confuses relevant decision makers. This study proposes a performance analysis framework for carbon quota allocation schemes by using a nonparametric frontier analysis approach from the perspectives of economic growth and energy conservation. Then, we apply this approach to evaluate the relative economic and energy conservation performances of 15 allocation schemes by reallocating the 2015 Chinese provincial carbon emission quotas, each of which is constructed via a combination of equity, grandfathering, efficiency and ability to pay principles. The results show that the proposed allocation scheme that integrates efficiency and the ability to pay principles is the best option, realizing approximately 6.78% outputs increase and 3.01% energy conservation relative to the actual 2015 emission scenario. We also show that the best scheme is linked to total quotas; the scheme considering only the equity principle is superior to others, while the total quotas are reduced by 10%. The study provides not only a theoretical tool, but also empirical evidence for the construction of China's carbon quota allocation scheme.

Could carbon emission control firms achieve an effective financing in the carbon market? A case study of China's emission trading scheme

This paper proposes a new prediction method incorporating a set of measuring models applicable to the financing efficiency of China's carbon market to quantify such market's maturity, trading risk coefficient, and financing income. Our theoretical analysis indicates that the price of carbon emission quota essentially affects the financing efficiency of carbon market. While a robust safeguard measure to obtain a respectable income from carbon market financing is the long-term average quota price exceeding the initial quota price. Empirical findings derived from China's emissions trading scheme pilots reveal that these pilots can be divided into the growth-oriented market (i.e. Guangdong whose financing capacity is always significant), the balance-oriented market (i.e. Shanghai and Hubei whose quota pricing mechanisms and the financing level of carbon markets both maturely develop), and the risk-oriented market (i.e. Beijing whose quota price runs at a high-level with an intense financing income volatility). It is therefore achieved that carbon market's maturity level and quota price volatility are both robustly explicable for different financing effects among these pilots. Our key findings show that expanding the coverage of quota trading parties, stabilizing carbon price, and promoting carbon asset management help to improve the financing efficiency of carbon market.

Allocation of carbon emission quotas in Chinese provinces based on Super-SBM model and ZSG-DEA model

Allocation of carbon emission quotas in Chinese provinces based on Super-SBM model and ZSG-DEA model

Research on the optimization of carbon abatement efficiency in China on the basis of task allocation

The fundamental requirement of carbon abatement is to complete the carbon abatement task set, at the lowest cost. In this paper, the non-radial distance function method is used to calculate the marginal carbon abatement costs of each unit, and the statistical method is used to estimate the carbon abatement efficiency of each unit. Based on the sum of dynamic carbon abatement costs in each province, the carbon abatement task allocation is optimized, and the data before and after optimization is compared and analyzed. The main conclusions are as follows: (1) The function of carbon abatement efficiency can be estimated using the marginal cost of carbon abatement, by which, the carbon abatement cost of each province can be calculated. (2) The correlation between carbon emissions and carbon abatement efficiency of each province is weak, so the overall carbon abatement efficiency of China is low. (3) Optimizing the allocation of provincial carbon abatement tasks can significantly reduce the total carbon abatement cost and improve the carbon abatement efficiency. This study has significant theoretical and practical value for improving China’s overall carbon abatement efficiency, and establishing the provincial initial carbon emission quota.

Renewable energy certificates and electricity trading models: Bi-level game approach

To reduce carbon emissions in the power sector, the emissions trading system (ETS) is widely used to mitigate emissions from thermal generators. Also, large-scale and distributed renewable energy is invested to replace conventional thermal generators. Renewable energy certificates (RECs) are designed to support the prior dispatch of renewable energy. However, the purchase motivation for RECs is worth attention. In this paper, a theoretical methodology is proposed to promote transactions of RECs. The cooperation of renewable power plants and the emerging storage technology, e.g., power-to-gas (P2G), is considered to further reduce emissions. In the proposed bi-level model, which is based on the game approach, the thermal generators can purchase RECs and convert them to carbon emission quotas. The oligopoly market is considered to reveal the real payoffs of thermal generators, renewable power plants, and power-to-gas stations (P2GSes). The proposed model is verified on the IEEE 30-bus system. It is found that the RECs can help renewable energy plants increase income by 19.4% without considering cooperation, and more renewable energy is dispatched as priority. It can be concluded that the cooperation of P2GSes and renewable plants considering the RECs can increase the collision payoffs and smooth the output of renewable energy. Sensitive analysis reveals the interaction between the carbon market and the RECs market.

An optimization model for charging and discharging battery-exchange buses: Consider carbon emission quota and peak-shaving auxiliary service market

The mode of battery replacement will become the main means of urban public transport energy supply, which will have a significant impact on the energy cost of public transport companies and the stability of the power system. Therefore, this paper proposes a charging and discharging optimization model for electric buses to participate in the carbon trading market and the peak shaving auxiliary service market. The upper model aims to minimize the total daily energy cost of the bus company, and the lower model is optimized based on the upper optimization results to minimize grid load fluctuations. Then, the scheme proposed in this paper is compared with disordered charging and orderly charging based on time of use price. Finally, a bus company in Beijing is taken as an example of simulation. The results show that compared with the disordered charging and the orderly charging based on time of use price, the charging and discharging schemes proposed in this paper can reduce the daily energy cost of 6052.68 yuan and 617.42 yuan respectively, reduce the fluctuation of power grid load by 92.14 % and 13.85 %, and reduce the carbon emission of the "bus power" combined system by 3930 kg and 2080 kg.

Location optimization of a competitive distribution center for urban cold chain logistics in terms of low-carbon emissions

Owing to the fast economic and social development in Wuhan, the demand for cold chain logistics is increasing rapidly. Currently, the scale of the existing distribution centers cannot fully meet this demand, so building new ones would seem necessary. Research rarely considers consumer choice from the perspective of competition between new and existing cold chain distribution centers, and the low-carbon concept is rarely considered when a competitive site is selected. This paper therefore puts forward a model to assist the decision-making process regarding the choice of location where cold chain logistics facilities might be sited. Based on a bi-level programming method, this model is constructed where the upper level of government aims to determine an optimal location and scale for a cold chain distribution center as well as a rational trading policy regarding carbon emissions to minimize the total social cost of the whole logistics system. The lower level adopts the demand user equilibrium model, which considers the demands of logistics users when choosing between new and existing cold chain distribution centers, so as to minimize the cost incurred by each logistics user. We use the cloud particle swarm optimization algorithm to solve the model and decide a suitable location for a new center in Wuhan, the principal city in the Hubei Province, in China. The study reveals that: (1) The high demand is equivalent to the high number of new distribution centers; (2) The high attractiveness of these centers is equal to their high total scale; (3) Changes in carbon emissions trading prices have an impact on the scale, total carbon emissions, and total social cost of new cold chain distribution centers; (4) The carbon emissions quota policy has an impact on the scale of the location chosen for a new cold chain distribution center, total carbon emissions, and total social costs. This article provides a scientific basis regarding decisions concerning the location of new cold chain distribution centers by the government, and provides some ideas for energy conservation improvement and carbon emissions reduction by the whole society.

The Approach to Carbon Emission Quotas of Road Transportation: A Carbon Emission Intensity Perspective

Carbon trading is an effective measure for the road transportation to reduce energy consumption and carbon emissions. Carbon emission quotas are the primary concern to ensuring the efficiency of carbon trading. However, the existing studies have mostly focused on carbon emission quotas in different regions, i.e., countries and provinces. Few literature studies simulate carbon quota allocation in the road transportation. A novel approach from the perspective of carbon emission intensity of vehicle is proposed, on the basis of data envelopment analysis (DEA) model. Unlike other studies, the idea of allocation of baseline excitation is introduced and the intensity is included in the model as the baseline. Firstly, the Delphi method is employed to select input and output indicators. Secondly, carbon emission intensity is determined by the cumulative distribution function (CDF). Furthermore, the carbon emission quotas in road transportation in 30 provinces of China are used to validate the model. The results show that (1) the carbon emission intensity of commercial trucks and buses in China’s road transport industry is 75.04 g/t·km and 13.12 g/p·km, respectively; (2) the provinces of Shanghai, Guangdong, and Xinjiang have the greatest carbon reduction potential and Henan, Hunan, and Anhui have the largest increase in emission quotas; (3) compared with traditional “history responsibility” and “baseline” methods, the proposed approach increases allocation efficiency by 19% and 14%, respectively; and (4) the approach can make the carbon emission quotas play the role of incentive while taking fairness into account and can more effectively promote the implementation of carbon trading system in road transportation.

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

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.

The Allocation of Carbon Intensity Reduction Target by 2030 among Cities in China

The regional allocation of carbon emission quotas is of great significance to realize the carbon emission target. Basing on the combination of the multi-index method and the improved equal-proportion distribution method, and fully considering the differences in economic factors, population factors, energy factors, technological factors among cities, China’s 2030 carbon intensity reduction target was allocated. The results indicate that: (1) Under the target constraint of 60% reduction in CO2 emissions per unit of Gross Domestic Product (GDP) (carbon intensity) in 2030 compared to 2005, the carbon intensity target reduction rate (CITRR) of 285 Chinese cities is between 17.65% and 141.14%, with an average reduction rate of 51.52%; (2) the CITRR of cities presents significant spatial positive correlation, and the Global Moran I correlation index is 0.38; and (3) the distribution trend of CITRR is the same as the general trend of economic development of China, showing a basic trend of gradual decline from south to north and from coastal to inland. The allocation method takes into account fairness and efficiency, and reflects the differences between cities, so that the allocation results are likely to be accepted by all parties. Meanwhile, this method breaks the limitation of the lack of city’s data and is likely to implement in actual operation. Cities should choose distinguished low-carbon economic development paths, in combination with their characteristics of economic and social development, and carry out inter-city cooperation to promote carbon emission reduction steadily.

A Decision-Making Model of Port Carbon Emission Reduction Investment under Uncertainty

Ports are big emitters of carbon emissions and often spend a lot of money and time on carbon emission reduction. Therefore, this paper constructs a port carbon emission reduction investment decision-making model under the uncertainty of carbon emission amount and carbon trading price, which taking the minimization of carbon emission reduction comprehensive cost as the optimization objective including some key factors such as the budget constraint of port carbon emission investment, carbon emission quota, and so on. At last, the case study of Shanghai port is carried out, and the optimization results show that Shanghai port should invest 3.10 Yi yuan in 2019 for carbon emission reduction. It is useful for the port carbon emission reduction managers and policy makers.

Allocation of carbon emission quotas in China’s provincial power sector based on entropy method and ZSG-DEA

The power sector accounted for almost 40% of China’s carbon emissions in 2017 and is the first industry that is included in the national carbon emission trading system, so the current paper carries out a study on allocating carbon emission allowances for the power sector. Different from previous studies, this article assigns carbon emission allowances to 30 provinces according to the principles of equality, efficiency, and sustainability rather than just using the principles of equality and efficiency. We first apply the entropy method to initially distribute emission allowances to 30 provinces. Then, a zero-sum gains data envelopment analysis (ZSG-DEA) model is used to test the efficiency of quota allocation and redistribute the carbon quotas across 30 provinces continuously until the quotas are optimally distributed. The results show that in 2030, Guangxi, Hainan and Shandong have the most emission quotas, while Heilongjiang, Jilin and Qinghai have the least emission quotas. By comparing the quota share of each province in 2017 with 2030, it is found that Hainan, Guangxi and Qinghai located in western China have small emission reduction challenges, while there are great difficulties for provinces Jiangsu, Shanxi and Shandong situated in the central and eastern China to cut down the emissions.

Provincial Carbon Emission Quota Allocation Study in China from the Perspective of Abatement Cost and Regional Cooperation

To achieve the carbon reduction target, the Chinese government not only requires a quota allocation scheme in line with the current development situation, but also needs to minimize the economic expenditure in the emission reduction work. Therefore, this study integrates the multi-index method and zero-sum gains–data envelopment analysis model to obtain a fair and efficient multi-criteria quota allocation scheme. To ensure the effectiveness of the scheme, the fairness and cost effect of the scheme are quantitatively tested. In addition, regional cooperation factors are introduced into the research framework to providing feasible practical measures. The results show that: (1) After optimization, the eastern region has the largest quota increment, accounting for 45% of the country’s quota. (2) The multi-criteria quota allocation scheme after secondary allocation is a more ideal scheme. The quota scheme not only meets the requirements of fairness and efficiency, but also has lower abatement costs. (3) Regional cooperation should be encouraged by China, especially the eastern region, which can alleviate the reducing emission pressure through cooperation. Although the western region needs to undertake additional emission reduction tasks, it can improve the utilization rate of local renewable resources and be conducive to long-term economic development. These results will provide a reference for China to achieve its carbon reduction targets.

Linking carbon market and electricity market for promoting the grid parity of photovoltaic electricity in China

In order to achieve the power supply change from traditional energy to clean energy in China, improving the grid parity rate of photovoltaic (PV) power is a key problem to be addressed. To establish a harmonious grid price between PV power and coal-fired power, this paper investigates the impact of carbon emission quota (CEQ) price on both PV power revenue and efficiency by constructing the carbon-electricity linkage mode with following innovative works. First, we set a trading mechanism that involves PV power plants and links carbon-electricity markets, and then propose market clearing rules for both CEQ and PV power prices. Second, we integrate market factors into the framework of power cost structure of different power sources based on the Life Cycle Cost (LCC) Theory. Third, we characterize the volatility of CEQ prices by offsetting the reduced fiscal subsidy of PV power and balancing grid price of different power sources. Our key findings show that the plan of improving current trading linkage of carbon-electricity market and grid parity scheme of PV power will be brought forward to 2023 that is 2 years ahead of schedule. What’s more, in the case of completely cancelling subsidy, CEQ price should be tripled by using this linkage to accelerate PV grid parity. By showing the possible trading benefit of carbon markets, this paper will help reduce the generation cost of PV power grid connection.

Bi-level multi-objective programming approach for carbon emission quota allocation towards co-combustion of coal and sewage sludge

As coal-fired power generation is responsible for more than 30% of total global emissions, co-combustion of coal and sewage sludge is widely used to reduce both carbon emissions and coal consumption. This paper proposes a bi-level multi-objective model for carbon emission quota allocation towards co-combustion of coal and sewage sludge under an uncertain environment. It considers the interactions between the authority and the coal-fired power plants in a leader-follower decision process, and seeks the trade-off among economic development, environmental protection and renewable energy utilization. Besides, fuzzy theory has been employed as an uncertainty modeling technique to characterize the vague and inaccurate decision-making environment. To solve the proposed complicated model, weighted sum method and KKT optimality conditions are applied to convert the model into a single-level single-objective model. A real case from Zhejiang Province, China is given to demonstrate the practicality and efficiency of the optimization model. Based on the analyses and discussion, this model provides reasonable and practical carbon emission quota allocation strategies for the authority. It is indicated that allocating greater quotas to lower carbon intensity coal-fired power plants could effectively achieve reduction targets. To verify the reasonableness, the results are compared with those of using single-level model.