Distributed optimal energy consumption control of HEVs under MFG-based speed consensus

2020 ◽  
Vol 18 (2) ◽  
pp. 193-203
Author(s):  
Qiaobin Fu ◽  
Fuguo Xu ◽  
Tielong Shen ◽  
Kenichi Takai
Keyword(s):  
Energy Consumption ◽  
Optimal Energy ◽  
Consumption Control

scholarly journals How to Effectively Control Energy Consumption Growth in China’s 29 Provinces: A Paradigm of Multi-Regional Analysis Based on EAALMDI Method

2021 ◽  
Vol 13 (3) ◽  
pp. 1093
Author(s):  
Yunlong Zhao ◽  
Geng Kong ◽  
Chin Hao Chong ◽  
Linwei Ma ◽  
Zheng Li ◽  
...  
Keyword(s):  
Energy Consumption ◽  
High Resolution ◽  
Energy Policy ◽  
Policy Making ◽  
Regional Analysis ◽  
Policy Implications ◽  
Consumption Growth ◽  
High Resolution Analysis ◽  
Resolution Analysis ◽  
Consumption Control

Controlling energy consumption to reduce greenhouse gas emissions has become a global consensus in response to the challenge of climate change. Most studies have focused on energy consumption control in a single region; however, high-resolution analysis of energy consumption and personalized energy policy-making, for multiple regions with differentiated development, have become a complicated challenge. Using the logarithmic mean Divisia index I (LMDI) decomposition method based on energy allocation analysis (EAA), this paper aims to establish a standard paradigm for a high-resolution analysis of multi-regional energy consumption and provide suggestions for energy policy-making, taking 29 provinces of China as the sample. The process involved three steps: (1) determination of regional priorities of energy consumption control by EAA, (2) revealing regional disparity among the driving forces of energy consumption growth by LMDI, and (3) deriving policy implications by comparing the obtained results with existing policies. The results indicated that 29 provinces can be divided into four groups, with different priorities of energy consumption control according to the patterns of coal flows. Most provinces have increasing levels of energy consumption, driven by increasing per capita GDP and improving living standards, while its growth is restrained by decreasing end-use energy intensity, improving energy supply efficiency, and optimization of industrial structures. However, some provinces are not following these trends to the same degree. This indicates that policy-makers must pay more attention to the different driving mechanisms of energy consumption growth among provinces.

scholarly journals Optimal energy consumption and throughput for workflow applications on distributed architectures

2014 ◽  
Vol 4 (1) ◽  
pp. 44-51
Author(s):  
Abdallah Ben Othman ◽  
Jean-Marc Nicod ◽  
Laurent Philippe ◽  
Veronika Rehn-Sonigo
Keyword(s):  
Energy Consumption ◽  
Distributed Architectures ◽  
Optimal Energy

Energy Aware Grid Scheduling for Dependent Task Using Genetic Algorithm

2016 ◽  
Vol 7 (2) ◽  
pp. 18-36
Author(s):  
Shiv Prakash ◽  
Deo Prakash Vidyarthi
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Job Scheduling ◽  
Computing System ◽  
Computational Grid ◽  
Task Execution ◽  
Energy Aware ◽  
Optimal Energy ◽  
Proposed Model ◽  
Dynamic Voltage

Consumption of energy in the large computing system is an important issue not only because energy sources are depleting fast but also due to the deteriorating environmental conditions. A computational grid is a large heterogeneous distributed computing platform which consumes enormous energy in the task execution. Energy-aware job scheduling, in the computational grid, is an important issue that has been addressed in this work. If the tasks are properly scheduled, keeping the optimal energy concern, it is possible to save the energy consumed by the system in the task execution. The prime objective, in this work, is to schedule the dependent tasks of a job, on the grid nodes with optimal energy consumption. Energy consumption is estimated with the help of Dynamic Voltage Frequency Scaling (DVFS). Makespan, while optimizing the energy consumption, is also taken care of in the proposed model. GA is applied for the purpose and therefore the model is named as Energy Aware Genetic Algorithm (EAGA). Performance evaluation of the proposed model is done using GridSim simulator. A comparative study with other existing models viz. min-min and max-min proves the efficacy of the proposed model.

scholarly journals Regional Disparities and Transformation of Energy Consumption in China Based on a Hybrid Input-Output Analysis

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5287
Author(s):  
Yuehui Xia ◽  
Ting Zhang ◽  
Miaomiao Yu ◽  
Lingying Pan
Keyword(s):  
Economic Development ◽  
Energy Consumption ◽  
Rapid Development ◽  
Input Output ◽  
Output Analysis ◽  
Four Dimensions ◽  
Low Energy Consumption ◽  
Level Of Economic Development ◽  
Radar Map ◽  
Consumption Control

Different regions in China have different energy consumption characteristics and changing trends. This paper focuses on analyzing trends in energy consumption changes along the timeline for 30 regions in China. Using the Hybrid Input-Output Model, this paper decomposes energy consumption in 30 regions in 2007, 2012 and 2016 into energy embedded of final consumption expenditure, gross capital formation, inflow and outflow. We use these four dimensions as coordinates to draw a regional radar map. According to the changing characteristics of the radar map, 30 regions are divided into three groups. By analyzing the reasons for the changes in three regions, we draw the following conclusions. For regions where energy consumption is mainly inflow, the economically developed regions have to form a low energy consumption environment while achieving economic growth. The economically underdeveloped regions need to carry out energy conservation and emission reduction as well as ensuring the level of economic development. For some outflow regions with moderately economic development, it is necessary to balance the economic development and energy consumption control according to regional characteristics. For resource-rich regions which are in the process of transformation from agriculture to industrialization, they have to maintain the rapid development speed and strengthen their infrastructure with less energy consumption of buildings.

scholarly journals Research on Standard System for “Double Control” of Total Energy Consumption and Energy Intensity

2019 ◽  
Vol 118 ◽  
pp. 01020
Author(s):  
Qing Ding ◽  
Haihong Chen ◽  
Pengcheng Li ◽  
Meng Liu ◽  
Ling Lin
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Continuous Improvement ◽  
Energy Intensity ◽  
Standard System ◽  
Total Energy Consumption ◽  
Intensity Control ◽  
The Future ◽  
Consumption Control

The significance of the principles and methods for building the standard system for “double control” was analyzed. A framework of standard system for “double control” was preliminarily built, comprising three subsystems of fundamental common, total energy consumption control and energy intensity control. The features and shortcomings of standards for “double control” was analyzed, as a reference for the continuous improvement of the standard system for “double control”, as well as the research and preparation of key standards in the future.

scholarly journals Powertrain Optimization for Electric Buses under Optimal Energy-Efficient Driving

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6451
Author(s):  
Alexander Koch ◽  
Olaf Teichert ◽  
Svenja Kalt ◽  
Aybike Ongel ◽  
Markus Lienkamp
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Energy Savings ◽  
Ride Comfort ◽  
Programming Approach ◽  
Automated Driving ◽  
Dynamic Programming Approach ◽  
Optimal Energy ◽  
Driving Cycles ◽  
Powertrain Configuration

State of the art powertrain optimization compares the energy consumption of different powertrain configurations based on simulations with fixed driving cycles. However, this approach might not be applicable to future vehicles, since speed advisory systems and automated driving functions offer the potential to adapt the speed profile to minimize energy consumption. This study aims to investigate the potential of powertrain optimization with respect to energy consumption under optimal energy-efficient driving for electric buses. The optimal powertrain configurations of the buses under energy-efficient driving and their respective energy consumptions are obtained using powertrain-specific optimized driving cycles and compared with those of human-driven unconnected buses and buses with non-powertrain-specific optimal speed profiles. Based on the results, new trends in the powertrain design of vehicles under energy-efficient driving are derived. The optimized driving cycles are calculated using a dynamic programming approach. The evaluations were based on the fact that the buses under energy-efficient driving operate in dedicated lanes with vehicle-to-infrastructure (V2I) communication while the unconnected buses operate in mixed traffic. The results indicate that deviating from the optimal powertrain configuration does not have a significant effect on energy consumption for optimized speed profiles; however, the energy savings from an optimized powertrain configuration can be significant when ride comfort is considered. The connected buses under energy-efficient driving operating in dedicated lanes may reduce energy consumption by up to 27% compared to human-driven unconnected buses.

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