Carbon Abatement Cost-Sharing Strategy for Electric Power Sector Based on Incentive and Subsidy Mechanisms

The green and low carbon transition and development of the electricity industry is the most crucial task in realizing the“dual-carbon target”,and it is urgent to explore the incentive and subsidy mechanism to promote green electricity consumption and the cost-sharing strategy of carbon reduction,to alleviate the pressure of carbon abatement cost of each subject of the electricity supply chain.Against this background,this paper takes into account the low-carbon subsidies provided by the government and the incentive subsidies for users,and studies the optimal decision-making of each subject in the electricity supply chain,so that each of them can obtain the optimal profit and achieve carbon emission reduction at the same time.Firstly,taking into account the direct power purchase mode of large users and the electricity-selling companies emerging after the reform of the power sales side,we have established a cooperative mechanism for sharing the cost of carbon emission reduction in the electricity supply chain and clarified the relationship between the supply and demand of electricity among the main parties.Subsequently,considering government low-carbon subsidies and user incentive subsidies,the optimal decisionmaking model is established under two scenarios of decentralized and centralized cooperative games in the supply chain,respectively,with the objective of maximizing profits and carbon reduction rates.Solving for the optimal proportion of carbon abatement costs shared by each participant in the electricity supply chain in achieving game equilibrium.Finally,we analyze the role of the government’s low-carbon subsidies,users’incentive subsidies,and other factors on the profit and carbon reduction effect of the electricity industry through the example analysis and further analyze the impact of carbon abatement cost-sharing measures to provide recommendations for the electricity industry to realize low-carbon abatement and make decisions.

Quantitative evaluation of the green production and consumption policies in China

Dual control of energy consumption is an effective method proposed in China to launch and deepen the transition in energy use.It has obtained favorable results;however,the resource consumption and pollution emissions per unit of Gross Domestic Product(GDP)remain high.This article quantitatively studies the current policies’effects to promote the advancement of dual control of energy consumption and develop future policies.Green production and consumption policies promote the development of dual control of energy consumption;therefore,this paper examines these policies through text mining and a quantitative evaluation system.The results suggest strong state demand for developing green production and consumption and the necessity for scientific evaluation;however,the state’s focus on the relevant policy tools is imbalanced.Constraint policy tools have the highest proportion of restricting pollutant emissions but lack comprehensiveness.Incentive and guidance policy tools have the problems of poor targets and low volume.Additionally,by constructing policy modeling consistency(PMC)index models for evaluating green production and consumption policies,six selected policies indicate solid performance,but some still have problems regarding policy timeframe,policy function,and green process.Based on the conclusions,this paper provides some targeted recommendations.

Investigating spatio-temporal characteristics and influencing factors for green energy consumption in China

The green transformation of energy consumption is beneficial for promoting green development in China.This study constructed a green energy consumption evaluation index system and measured the green energy consumption levels in 30 provinces of China from 2000 to 2019 using the fuzzy comprehensive evaluation method.This study further employed the spatial Durbin model to examine influencing factors and spillover effects of green energy consumption.The results showed that,temporally,China’s green energy consumption levels had a fluctuating upward trend.While,spatially,the overall levels of green energy consumption in China showed apparent characteristics of“high in the west and low in the east”.In terms of influencing factors,environmental regulations played an important role in promoting green energy consumption in the region,while economic development,opening up,and industrial structure had considerably inhibiting effects.Additionally,economic development,opening up,and industrial structure of neighboring regions showed marked positive spillover effects,while urbanization level and technological innovation showed substantial negative spillover effects.The regional heterogeneity test results showed that environmental regulation and industrial structure rationalization were the important factors for promoting green energy consumption in the eastern region,environmental regulation played an important driving role in the central region,and opening to the outside world and technological innovation helped improve the level of green energy consumption in the western region.

Resource pre-allocation algorithms for low-energy task scheduling of cloud computing

In order to lower the power consumption and improve the coefficient of resource utilization of current cloud computing systems, this paper proposes two resource pre-allocation algorithms based on the ＂shut down the redundant, turn on the demanded＂ strategy here. Firstly, a green cloud computing model is presented, abstracting the task scheduling problem to the virtual machine deployment issue with the virtualization technology. Secondly, the future workloads of system need to be predicted： a cubic exponential smoothing algorithm based on the conservative control（CESCC） strategy is proposed, combining with the current state and resource distribution of system, in order to calculate the demand of resources for the next period of task requests. Then, a multi-objective constrained optimization model of power consumption and a low-energy resource allocation algorithm based on probabilistic matching（RA-PM） are proposed. In order to reduce the power consumption further, the resource allocation algorithm based on the improved simulated annealing（RA-ISA） is designed with the improved simulated annealing algorithm. Experimental results show that the prediction and conservative control strategy make resource pre-allocation catch up with demands, and improve the efficiency of real-time response and the stability of the system. Both RA-PM and RA-ISA can activate fewer hosts, achieve better load balance among the set of high applicable hosts, maximize the utilization of resources, and greatly reduce the power consumption of cloud computing systems.

Green finance,fintech and environmental protection:Evidence from China

This paper is one of the first to offer a comprehensive analysis of the impact of green finance related policies in China,utilizing text analysis and panel data from 290 cities between 2011 and 2018.Employing the Semi-parametric Difference-in-Differences(SDID)we show that overall China's green finance related policies have led to a significant reduction in industrial gas emissions in the review period.Additionally,we found that Fintech development contributes to the depletion of sulphur dioxide emissions and has a positive impact on environmental protection investment initiatives.China is poised to be a global leader in green finance policy implementation and regulators need to accelerate the formulation of green finance products and enhance the capacity of financial institutions to offer green credit.While minimizing the systemic risk fintech poses,policy makers should encourage fintechs to actively participate in environmental protection initiatives that promote green consumption.