scholarly journals Energy Utilization Evaluation of Carbon Performance in Public Projects by FAHP and Cloud Model

2016 ◽  
Vol 8 (7) ◽  
pp. 630 ◽  
Author(s):  
Lin Li ◽  
Fangfang Fan ◽  
Li Ma ◽  
Ziran Tang
Keyword(s):  
Cloud Model ◽  
Energy Utilization ◽  
Public Projects ◽  
Carbon Performance

scholarly journals Dynamic Consolidation of VM Allocation and VM Migration to Optimize Energy Consumption of Cloud Data Centers

2019 ◽  
Vol 8 (6) ◽  
pp. 4932-4937
Keyword(s):  
Energy Consumption ◽  
Data Centers ◽  
Cloud Model ◽  
Energy Utilization ◽  
Cloud Computing Environment ◽  
Cloud Data ◽  
Vm Allocation ◽  
Cloud Application ◽  
Subsequent Effect ◽  
Cloud Data Centers

Including the expanding fame of the cloud model and quick multiplication of cloud frameworks there are expanding concerns about energy utilization and subsequent effect of cloud as a supporter of worldwide CO2 discharges. Until now, little is thought about how to fuse energy utilization and CO2 worries into cloud application. Energy consumption has become an important cost factor for computing resources. In this research article, we proposed an algorithm to VM Allocation and VM migrations in the context of power utilisation in the data centers. This mechanism is to minimize the energy utilization in the cloud computing environment. We validate our results with the help of prediction based faster energy efficient VMs approach and modified Best Fit approach which shows the faster assignments and increase the performance when consumption of the energy is optimised. As well as we also simulate our results in the cloudsim in the multiple numbers of host and virtual machine to reduce the energy consumptions.

Research on the Relation between Corporate Social Responsibility Practice and Financial Performance under the Low Carbon Economy — From the Case Analysis of CNPC

2013 ◽  
Vol 734-737 ◽  
pp. 2041-2046
Author(s):  
Hong Wang ◽  
Deng Hui Xie ◽  
Qi Jie Chen
Keyword(s):  
Social Responsibility ◽  
Financial Performance ◽  
Performance Indicator ◽  
Positive Influence ◽  
Energy Utilization ◽  
Energy Structure ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Carbon Performance ◽  
Carbon Economy

This thesis is focused on the relationship between the low-carbon performance indicator and financial performance indicator of the oil enterprise with social responsibility from the case of the CNPC. In the short run, the role of environment protection assumed by the oil enterprise will cause the extra cost and subsequent lower financial performance. After the correlation analysis of CSR report of CNPC from 2006 to 2011, the result shows that taking social responsibility, developing low-carbon economy, improving the efficiency of energy utilization and cleaning the energy structure will bring positive influence on the enterprise financial performance. Therefore, in the long run, there is a significant correlation between the low-carbon performance indicator and financial performance.

Endogenous Factor Analysis: The Carbon Performance of Public Projects in China

2017 ◽  
Vol 48 (5) ◽  
pp. 25-48
Author(s):  
Ziran Tang ◽  
Lin Li ◽  
Shasha Zhu ◽  
Zhenyu Huang
Keyword(s):  
Project Management ◽  
Human Resources ◽  
Structural Equation ◽  
Equation Model ◽  
Research Model ◽  
Public Project ◽  
Endogenous Factors ◽  
Public Projects ◽  
Framework Approach ◽  
Carbon Performance

This study investigates how the endogenous factors of public projects affect carbon performance. Taking the logical framework approach, a research model and hypotheses are proposed to evaluate the effects of endogenous project factors, including human resources, funding, materials, and project management methodology on project carbon performance. Questionnaires were distributed to project professionals in China and a structural equation model was deployed to analyze these effects. The results show that funding, materials, and project management methodology have a significant influence on public project carbon performance, whereas human resources have no significant effects. Recommendations on how to improve carbon performance are provided.

Distributed Entropy Energy-Efficient Clustering algorithm for cluster head selection (DEEEC)

2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan
Keyword(s):  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Second Stage ◽  
Energy Efficient Clustering ◽  
Two Stages ◽  
Ch Selection

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.

Recovering waste energy of the combined gas turbine system using paraffin melting

2020 ◽  
Vol 14 (4) ◽  
pp. 7481-7497
Author(s):  
Yousef Najjar ◽  
Abdelrahman Irbai
Keyword(s):  
Melting Process ◽  
Payback Period ◽  
Energy Utilization ◽  
Raw Material ◽  
Heat Transfer Fluid ◽  
Layered System ◽  
Exhaust Gas ◽  
Gas Temperature ◽  
Power Cycle ◽  
Waste Energy

This work covers waste energy utilization of the combined power cycle by using it in the candle raw material (paraffin) melting process and an economic study for this process. After a partial utilization of the burned fuel energy in a real bottoming steam power generation, the exhaust gas contains 0.033 of the initially burned energy. This tail energy with about 128 ºC is partly driven in the heat exchanger of the paraffin melting system. Ansys-Fluent Software was used to study the paraffin wax melting process by using a layered system that utilizes an increased interface area between the heat transfer fluid (HTF) and the phase change material (PCM) to improve the paraffin melting process. The results indicate that using 47.35 kg/s, which is 5% of the entire exhaust gas (881.33 kg/s) from the exit of the combined power cycle, would be enough for producing 1100 tons per month, which corresponds to the production quantity by real candle's factories. Also, 63% of the LPG cost will be saved, and the payback period of the melting system is 2.4 years. Moreover, as the exhaust gas temperature increases, the consumed power and the payback period will decrease.

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