Energy consumption of Data Driven traffic simulations

2016 ◽  
Author(s):  
SaBra Neal ◽  
Richard Fujimoto ◽  
Michael Hunter
Keyword(s):  
Energy Consumption ◽  
Data Driven ◽  
Traffic Simulations

Operation Optimization Approaches of Thermal Power Units with Big Data-Driven Hybrid Modeling

2014 ◽  
Vol 631-632 ◽  
pp. 362-366
Author(s):  
Ning Ling Wang ◽  
Yong Zhang ◽  
Long Fei Zhu ◽  
Zhi Ping Yang
Keyword(s):  
Energy Consumption ◽  
Thermal Power ◽  
Hybrid Modeling ◽  
Data Driven ◽  
Fuzzy Rough Set ◽  
Operation Optimization ◽  
Operation Conditions ◽  
Energy Consumption Model ◽  
Practical Guidelines ◽  
Data Driven Modeling

An accurate and reliable energy-consumption model is the key to operation optimization and energy-saving diagnosis of thermal power units especially under different operation conditions and boundaries. Conventional mathematical and data-driven modeling methods were overviewed and compared in this paper. A hybrid modeling based on thermodynamic theory and fuzzy rough set (FRS) method was proposed to process the great volume of operation data and describe the energy-consumption behavior of thermal power units. On this basis, the operation optimization was performed with intelligent computation methods to derive the realizable benchmark state with the whole set of operation parameters. The resultant optimum operation state reflects the exterior factors and system behavior, taking practical guidelines for the modeling and optimization of large thermal power units.

scholarly journals Predicting Building Energy Consumption using Engineering and Data Driven Approaches: A Review

2017 ◽  
Vol 2 (5) ◽  
pp. 44 ◽  
Author(s):  
Aulon Shabani ◽  
Orion Zavalani
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Building Energy ◽  
Data Driven ◽  
World Population ◽  
Design Phase ◽  
Energy Prediction ◽  
Important Concern ◽  
Paper Review ◽  
Second Category

Rapid growth of world population has higher impact on increasing buildings energy consumption. Therefore, improving energy consumption is an important concern for building engineers and operators. Energy management through forecasting approaches as one of most effective methods is in focus of this paper. Review of most elaborated methods is in our focus, where we investigate two main directions of energy prediction approaches. First category of approaches focuses on engineering methods mainly very reliable on building early operation stages and design phase, meanwhile second category go through data driven methods. Existing research works focused on these two models are introduced emphasizing advantages and relevant applications of methods.

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