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International audience ; Though the electricity market in China has gone through several reforms in the last few decades, the market is still not completely liberalized. The wholesale prices are regulated and for renewable it is based on feed-in tariff; there is not yet a competitive spot or derivative market concerning the generation side. Furthermore, with great potential, renewable energy is being gradually promoted by the government to compete freely with conventional energies. However, it is hard for a renewable generator to survive without subsidy. So, in this paper we propose a new round of revolution in power sector to introduce electricity futures into China with the expectation of perfecting the market and providing a proper hedging tool for renewable plants. We make an estimation of the risk premium and then simulate the futures prices in China's market. To support the establishment of the futures contracts, we also propose two pricing mechanisms: Demand-side price & Opportunity cost price and study their effects on the futures. Finally, some suggestions with regard to the construction of futures market in China and the operational strategy for renewable plants are given.

Though the electricity market in China has gone through several reforms in the last few decades, the market is still not completely liberalized. The wholesale prices are regulated and for renewable it is based on feed-in tariff; there is not yet a competitivespot or derivative market concerning the generation side. Furthermore, with great potential, renewable energy is being gradually promoted by the government to compete freely with conventional energies. However, it is hard for a renewablegenerator to survive without subsidy. So, in this paper we propose a new round of revolution in power sector to introduce electricity futures into China with the expectation of perfecting the market and providing a proper hedging tool for renewable plants. We make an estimation of the risk premium and then simulate the futures prices in China's market. To support the establishment of the futures contracts, we also propose two pricing mechanisms: Demand-side price & Opportunity cost price and study their effects on the futures. Finally, some suggestions with regard to the construction of futures market in China and the operational strategy for renewableplants are given.

Though the electricity market in China has gone through several reforms in the last few decades, the market is still not completely liberalized. The wholesale prices are regulated and for renewable it is based on feed-in tariff; there is not yet a competitivespot or derivative market concerning the generation side. Furthermore, with great potential, renewable energy is being gradually promoted by the government to compete freely with conventional energies. However, it is hard for a renewablegenerator to survive without subsidy. So, in this paper we propose a new round of revolution in power sector to introduce electricity futures into China with the expectation of perfecting the market and providing a proper hedging tool for renewable plants. We make an estimation of the risk premium and then simulate the futures prices in China's market. To support the establishment of the futures contracts, we also propose two pricing mechanisms: Demand-side price & Opportunity cost price and study their effects on the futures. Finally, some suggestions with regard to the construction of futures market in China and the operational strategy for renewableplants are given.

Though the electricity market in China has gone through several reforms in the last few decades, the market is still not completely liberalized. The wholesale prices are regulated and for renewable it is based on feed-in tariff; there is not yet a competitivespot or derivative market concerning the generation side. Furthermore, with great potential, renewable energy is being gradually promoted by the government to compete freely with conventional energies. However, it is hard for a renewablegenerator to survive without subsidy. So, in this paper we propose a new round of revolution in power sector to introduce electricity futures into China with the expectation of perfecting the market and providing a proper hedging tool for renewable plants. We make an estimation of the risk premium and then simulate the futures prices in China's market. To support the establishment of the futures contracts, we also propose two pricing mechanisms: Demand-side price & Opportunity cost price and study their effects on the futures. Finally, some suggestions with regard to the construction of futures market in China and the operational strategy for renewableplants are given.

Fossil fuel are used in power generation in oil and gas producing countries due to the resourceavailability. However, the growing electricity demand, the potential exports revenues associated to hydrocarbons as well as the environmental policies have to be taken into account for the definition of the electricity generation mix. Thus, the development of the power generation capacities according to the resource availability and the economic factors (demand and costs) is investigated through a modeling approach. Over the past ten years, Egypt has become an important gas producer and a strategic gas supplier for Europe. Moreover, natural gas represents around eighty percent of the Egyptian power sector mix. However, this extensive share of natural gas in power generation mix could not be sustainable in long-term due to the limited hydrocarbons' resources of Egypt. In this study, the current and future power generation situation of the country is analyzed through a dynamic linear programming model. Finally, a power generation strategy based on a gradual integration of nuclear and renewable is suggested.

AbstractIn order to implement or maintain a green supply chain (GSC) that produces goods and services responsibly and sustainably, supply chain managers should use tools that allow for the efficient identification, quantification, and mitigation of the ever‐present risks. The objective of the present research is to identify the risk factors associated with the processes involved in GSC management. Based on an analysis of the characteristics of GSC risk, the authors put forward a list of risk design principles and a risk criteria evaluation system for a GSC. Gray relation analysis method was then used to clarify the degree of connection between certain supply chain risk factors and select key risk factors. Finally, Back Propagation Artificial Neural Network (BP‐ANN) method was used to determine the risk level associated with a GSC. The determination of risk level will help companies to develop effective strategic management initiatives in a GSC environment.

To reduce traffic congestion and protect the environment, license plate control (LPC) policy has beenimplemented in Beijing since 2011. In 2019, 100,000 vehicle license plates were distributed, including60,000 for electric vehicle (EV) and 40,000 for gasoline vehicle (GV). However, whether the currentlicense plate allocation is optimal from a social welfare maximization perspective remains unclear. This paper proposes a two-level Stackelberg game which portrays the interaction between vehicle applicants and the government to quantify the optimal EV license plates under the LPC policy in Beijing. The equilibrium number of EV license plates derived from the Stackelberg model is 58,800, which could increase the social welfare by 0.38%. Sensitivity analysis is conducted to illustrate the impact of important influential factors — total license plate quota, vehicle rental fee, and energy price — on EV adoption. The LPC policy under COVID-19 is also studied through a scenario analysis. If thegovernment additionally increases the total quota by 20,000, 24% could be allocated to GV and 76% to EV. One third reduction of the current vehicle rental fee could increase EV license plates by 10.5%. Interms of energy prices, when gasoline price is low, reducing electricity price could contribute to EVadoption significantly, while that effect tapers off as the gasoline price rises.

To reduce traffic congestion and protect the environment, license plate control (LPC) policy has beenimplemented in Beijing since 2011. In 2019, 100,000 vehicle license plates were distributed, including60,000 for electric vehicle (EV) and 40,000 for gasoline vehicle (GV). However, whether the currentlicense plate allocation is optimal from a social welfare maximization perspective remains unclear. This paper proposes a two-level Stackelberg game which portrays the interaction between vehicle applicants and the government to quantify the optimal EV license plates under the LPC policy in Beijing. The equilibrium number of EV license plates derived from the Stackelberg model is 58,800, which could increase the social welfare by 0.38%. Sensitivity analysis is conducted to illustrate the impact of important influential factors — total license plate quota, vehicle rental fee, and energy price — on EV adoption. The LPC policy under COVID-19 is also studied through a scenario analysis. If thegovernment additionally increases the total quota by 20,000, 24% could be allocated to GV and 76% to EV. One third reduction of the current vehicle rental fee could increase EV license plates by 10.5%. Interms of energy prices, when gasoline price is low, reducing electricity price could contribute to EVadoption significantly, while that effect tapers off as the gasoline price rises.

To reduce traffic congestion and protect the environment, license plate control (LPC) policy has beenimplemented in Beijing since 2011. In 2019, 100,000 vehicle license plates were distributed, including60,000 for electric vehicle (EV) and 40,000 for gasoline vehicle (GV). However, whether the currentlicense plate allocation is optimal from a social welfare maximization perspective remains unclear. This paper proposes a two-level Stackelberg game which portrays the interaction between vehicle applicants and the government to quantify the optimal EV license plates under the LPC policy in Beijing. The equilibrium number of EV license plates derived from the Stackelberg model is 58,800, which could increase the social welfare by 0.38%. Sensitivity analysis is conducted to illustrate the impact of important influential factors — total license plate quota, vehicle rental fee, and energy price — on EV adoption. The LPC policy under COVID-19 is also studied through a scenario analysis. If thegovernment additionally increases the total quota by 20,000, 24% could be allocated to GV and 76% to EV. One third reduction of the current vehicle rental fee could increase EV license plates by 10.5%. Interms of energy prices, when gasoline price is low, reducing electricity price could contribute to EVadoption significantly, while that effect tapers off as the gasoline price rises.

International audience The topic of climate change has aroused increasingly widespread concern around the world. Under the agreement at the 21st Conference of the Parties of the United Nations Framework Convention on Climate Change (UNFCCC), covened in Paris, France (Paris Agreement), which requires all Parties to undertake emission reductions, the developing countries who were once exempted from emission reduction obligations are now becoming more and more important. This study focuses on mitigation actions in China, the largest carbon emitter, as well as the largest developing country in the world. Specifically, we examine Chinese Certified Emission Reduction (CCER) projects. The objective is to compare the reduction efficiency of three types of projects: simple abatement and completely renewable energy alternative projects at the supply side and demand side projects. From market-induced carbon leakage point of view, a dual market equilibrium model was built, with results showing that the key factors affecting the leakage rates are price elasticities of both demand and supply sides and market share parameters. In most cases, renewable energy alternative projects show the least leakage rate while demand side projects show the highest. Sensitivity analysis finds that leakage rates for the three types of projects are more sensitive to price elasticity parameters than market share parameters. Moreover, factors Edec (electricity price elasticity of coal demand from coal-fired generation) and Ede (electricity price elasticity of electricity demand) affect not only the leakage rate of each project but also the comparative results between them. Although our study is based on China, the theoretical analysis is applicable in other regional voluntary emission reduction markets around the world. So, a systematic approach to comprehensively analyze the issue is summarized, based on which, we recommend two mitigation strategies to cope with the issue in offset projects in order to give managerial insights for the ...

International audience ; The topic of climate change has aroused increasingly widespread concern around the world. Under the agreement at the 21st Conference of the Parties of the United Nations Framework Convention on Climate Change (UNFCCC), covened in Paris, France (Paris Agreement), which requires all Parties to undertake emission reductions, the developing countries who were once exempted from emission reduction obligations are now becoming more and more important. This study focuses on mitigation actions in China, the largest carbon emitter, as well as the largest developing country in the world. Specifically, we examine Chinese Certified Emission Reduction (CCER) projects. The objective is to compare the reduction efficiency of three types of projects: simple abatement and completely renewable energy alternative projects at the supply side and demand side projects. From market-induced carbon leakage point of view, a dual market equilibrium model was built, with results showing that the key factors affecting the leakage rates are price elasticities of both demand and supply sides and market share parameters. In most cases, renewable energy alternative projects show the least leakage rate while demand side projects show the highest. Sensitivity analysis finds that leakage rates for the three types of projects are more sensitive to price elasticity parameters than market share parameters. Moreover, factors Edec (electricity price elasticity of coal demand from coal-fired generation) and Ede (electricity price elasticity of electricity demand) affect not only the leakage rate of each project but also the comparative results between them. Although our study is based on China, the theoretical analysis is applicable in other regional voluntary emission reduction markets around the world. So, a systematic approach to comprehensively analyze the issue is summarized, based on which, we recommend two mitigation strategies to cope with the issue in offset projects in order to give managerial insights for the government. Firstly, the calculated leakage rates for different types of projects provide a new perspective to evaluate various offset projects, thus helping consider project types for priority validation. Secondly, we suggest to establish an accurate and classified discount coefficient system according to the project types to deal with the issue; the sensitivity analysis is helpful to find the most influential factors. A top-down approach to implement the strategy is proposed.

International audience ; The rapid development of electric vehicles can greatly alleviate the environmental problems and energy tension. However, the lack of public supporting facilities has become the biggest problem hinders its development. How to reasonably plan the placement of charging stations to meet the needs of electric vehicles has become an urgent situation in China. Different from private charging piles, charging station could help to break the limitation of short range. It also has a special dual attribute of public service and high investment. Therefore, a mathematically optimal model with two objective functions is developed to analyze the relationship between upfront investments and operating costs and service coverage of charging station system and it was solved by Particle Swarm Optimization. Besides, we take into account the conveniences of stations for charging vehicles and their influences on the loads of the power grid. Geographic Information System is used to overlay the traffic system diagram on power system diagram to find the alternative construction sites. In this study, a district in Beijing is analyzed using the proposed method and model. And the following suggestions are given: government should lead the construction of charging station; service ability needs to be enhanced; it is better to make more investment at earlier stage; constructions of charging stations can facilitate EV's development.

International audience ; The rapid development of electric vehicles can greatly alleviate the environmental problems and energy tension. However, the lack of public supporting facilities has become the biggest problem hinders its development. How to reasonably plan the placement of charging stations to meet the needs of electric vehicles has become an urgent situation in China. Different from private charging piles, charging station could help to break the limitation of short range. It also has a special dual attribute of public service and high investment. Therefore, a mathematically optimal model with two objective functions is developed to analyze the relationship between upfront investments and operating costs and service coverage of charging station system and it was solved by Particle Swarm Optimization. Besides, we take into account the conveniences of stations for charging vehicles and their influences on the loads of the power grid. Geographic Information System is used to overlay the traffic system diagram on power system diagram to find the alternative construction sites. In this study, a district in Beijing is analyzed using the proposed method and model. And the following suggestions are given: government should lead the construction of charging station; service ability needs to be enhanced; it is better to make more investment at earlier stage; constructions of charging stations can facilitate EV's development.