A Hybrid Optimisation Decision Model for a Smart Green Energy Industry Park: Exploring the Impact of the Carbon Tax Policy in Taiwan

2021 ◽  
pp. 107567
Author(s):  
Chih-Hao Yang
Keyword(s):  
Tax Policy ◽  
Decision Model ◽  
Carbon Tax ◽  
Green Energy ◽  
Energy Industry ◽  
The Impact

scholarly journals Did the Introduction of Carbon Tax in Australia Affect Housing Affordability?

2013 ◽  
Vol 869-870 ◽  
pp. 840-843
Author(s):  
Xin Janet Ge
Keyword(s):  
Risk Factors ◽  
Supply Chain ◽  
Energy Consumption ◽  
Tax Policy ◽  
Carbon Tax ◽  
Housing Affordability ◽  
Greenhouse Emissions ◽  
Pricing Scheme ◽  
The Cost ◽  
The Impact

The Australian carbon pricing scheme (carbon tax) was introduced and became effective on 01 July 2012. The introduction of the carbon tax immediately increases the cost of electricity to a number of industries such as manufacturing and construction. Households were also affected as a result of these costs been passed through the supply chain of the affected industries. The carbon tax policy was introduced to addresses greenhouse emissions and energy consumption in Australia. However, the carbon tax policy may have introduced a number of economic risk factors to the Australian housing market, in particular the impact of housing affordability.

scholarly journals Emission-Intensity-Based Carbon Tax and Its Impact on Generation Self-Scheduling

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 777 ◽  
Author(s):  
Ping Che ◽  
Yanyan Zhang ◽  
Jin Lang
Keyword(s):  
Electricity Market ◽  
Emission Intensity ◽  
Tax Policy ◽  
Programming Model ◽  
Carbon Tax ◽  
Electric Power Industry ◽  
Decomposition Algorithm ◽  
Mixed Integer ◽  
Tax Rate ◽  
The Impact

We propose an emission-intensity-based carbon-tax policy for the electric-power industry and investigate the impact of the policy on thermal generation self-scheduling in a deregulated electricity market. The carbon-tax policy is designed to take a variable tax rate that increases stepwise with the increase of generation emission intensity. By introducing a step function to express the variable tax rate, we formulate the generation self-scheduling problem under the proposed carbon-tax policy as a mixed integer nonlinear programming model. The objective function is to maximize total generation profits, which are determined by generation revenue and the levied carbon tax over the scheduling horizon. To solve the problem, a decomposition algorithm is developed where the variable tax rate is transformed into a pure integer linear formulation and the resulting problem is decomposed into multiple generation self-scheduling problems with a constant tax rate and emission-intensity constraints. Numerical results demonstrate that the proposed decomposition algorithm can solve the considered problem in a reasonable time and indicate that the proposed carbon-tax policy can enhance the incentive for generation companies to invest in low-carbon generation capacity.

scholarly journals The Impact of Corporate Governance on the Capital Structure of Companies from the Energy Industry. The Case of Poland

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7412
Author(s):  
Barbara Grabinska ◽  
Marcin Kedzior ◽  
Dorota Kedzior ◽  
Konrad Grabinski
Keyword(s):  
Corporate Governance ◽  
Capital Structure ◽  
Climate Policy ◽  
Personal Characteristics ◽  
Energy Sector ◽  
State Ownership ◽  
Green Energy ◽  
Energy Industry ◽  
The Impact ◽  
The Capital Structure

The energy sector is expected to face fundamental challenges in the near future. On the one hand, it is experiencing a rapidly increasing demand for energy. At the same time, it is subject to the pressure of the climate policy due to environmental issues. For the same reason, the energy sector is forced to undertake costly investments to transform production from black to green energy. The issue of financing has become one of the key problems of the energy sector, especially in those countries in which energy production traditionally is based on fossil fuels, i.e., coal. The paper aims to investigate the impact of corporate governance on the capital structure of companies from the energy industry. We use three proxies of corporate governance quality: institutional investors, the board size, and state ownership and investigate their impact on capital structure. Our findings suggest that the latter two negatively impact debt levels. In our model, we control for financial factors and CEO personal characteristics. We use a Polish setting since transformational problems of the energy sector in Poland are especially visible. At the same time, energy companies in Poland are subject to the strict EU climate policy.

scholarly journals Study on Green Supply Chain Cooperation and Carbon Tax Policy considering Consumer’s Behavior

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Jian Liu ◽  
Chao Hu
Keyword(s):  
Supply Chain ◽  
Tax Policy ◽  
Carbon Tax ◽  
Supply Chain Coordination ◽  
Environmental Awareness ◽  
Green Supply Chain ◽  
Tax Revenue ◽  
Theoretic Model ◽  
Tax Rate ◽  
The Impact

Carbon tax policy has been shown to be an effective incentive for the reduction of carbon emissions, and it also profoundly influences supply chain cooperation. This paper explores the interaction between carbon taxes and green supply chain cooperation. Specifically, we analyze the impact of a carbon tax on green supply chain coordination and further optimize the carbon tax to achieve a win-win situation for both the supply chain and the environment. Because consumer’s behavior has a significant impact on green product demand, we consider the problems above under two types of consumer’s behavior characteristics: consumer’s environmental awareness and consumer’s reference behavior. A game-theoretic model is employed to describe a green supply chain consisting of a manufacturer and a retailer, combining important factors such as the carbon tax rate, green investment coefficient, and degree of reference effect. Then, we obtain the optimal carbon tax rate by balancing the total tax revenue and product greenness. A revenue-sharing contract is introduced to achieve green supply chain coordination, and the impact of the carbon tax on coordination is analyzed. The results show the following. (1) The carbon tax rate and the difference between the power of the manufacturer and retailer are the main factors determining green supply chain coordination. (2) Maximum greenness can be achieved when development costs are higher, while the maximum tax revenue is obtained when the development cost is lower, but with the loss of greenness. (3) If the power of the manufacturer is low, coordination can be achieved under the optimal carbon tax. If the power of the manufacturer is at a medium level, coordination can be achieved by increasing the carbon tax; as a result, increased greenness will be realized, but with the loss of tax revenue. However, when the power of the manufacturer is strong, coordination cannot be achieved. (4) Price reference behavior can promote supply chain coordination, but consumer’s environmental awareness cannot.

The impact of the carbon tax policy on green building strategy

2016 ◽  
Vol 60 (8) ◽  
pp. 1412-1438 ◽  
Author(s):  
Wen-Hsien Tsai ◽  
Chih-Hao Yang ◽  
Cheng-Tsu Huang ◽  
Yen-Ying Wu
Keyword(s):  
Tax Policy ◽  
Carbon Tax ◽  
Green Building ◽  
The Impact

scholarly journals Optimized Energy Cost and Carbon Emission-Aware Virtual Machine Allocation in Sustainable Data Centers

2020 ◽  
Vol 12 (16) ◽  
pp. 6383
Author(s):  
T. Renugadevi ◽  
K. Geetha ◽  
K. Muthukumar ◽  
Zong Woo Geem
Keyword(s):  
Virtual Machine ◽  
Carbon Emission ◽  
Data Centers ◽  
Carbon Tax ◽  
Operating Cost ◽  
Green Energy ◽  
Energy Usage ◽  
Electricity Cost ◽  
Machine Allocation ◽  
The Impact

Cloud data center’s total operating cost is conquered by electricity cost and carbon tax incurred due to energy consumption from the grid and its associated carbon emission. In this work, we consider geo-distributed sustainable datacenter’s with varying on-site green energy generation, electricity prices, carbon intensity and carbon tax. The objective function is devised to reduce the operating cost including electricity cost and carbon cost incurred on the power consumption of servers and cooling devices. We propose renewable-aware algorithms to schedule the workload to the data centers with an aim to maximize the green energy usage. Due to the uncertainty and time variant nature of renewable energy availability, an investigation is performed to identify the impact of carbon footprint, carbon tax and electricity cost in data center selection on total operating cost reduction. In addition, on-demand dynamic optimal frequency-based load distribution within the cluster nodes is performed to eliminate hot spots due to high processor utilization. The work suggests optimal virtual machine placement decision to maximize green energy usage with reduced operating cost and carbon emission.

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