Minimising the Energy Consumption of Real-Time Tasks with Precedence Constraints on a Single Processor

2006 ◽  
pp. 45-56
Author(s):  
Hui Wu ◽  
Sridevan Parameswaran
Keyword(s):  
Energy Consumption ◽  
Real Time ◽  
Precedence Constraints ◽  
Single Processor

scholarly journals A Novel Method for Detecting Abnormal Energy Data in Building Energy Monitoring System

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Liang Zhao
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Real Time ◽  
Difference Method ◽  
Building Energy ◽  
Energy Monitoring ◽  
Order Difference ◽  
Energy Data ◽  
First Order ◽  
Novel Method

This paper presents a novel abnormal data detecting algorithm based on the first order difference method, which could be used to find out outlier in building energy consumption platform real time. The principle and criterion of methodology are discussed in detail. The results show that outlier in cumulative power consumption could be detected by our method.

scholarly journals A New Approach for Real Time Train Energy Efficiency Optimization

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2660 ◽  
Author(s):  
Agostinho Rocha ◽  
Armando Araújo ◽  
Adriano Carvalho ◽  
João Sepulveda
Keyword(s):  
Energy Efficiency ◽  
Simulated Annealing ◽  
Energy Consumption ◽  
Real Time ◽  
Optimization Algorithm ◽  
Normal Operation ◽  
Speed Profile ◽  
Railway Systems ◽  
Optimal Speed ◽  
Advisory System

Efficient use of energy is currently a very important issue. As conventional energy resources are limited, improving energy efficiency is, nowadays, present in any government policy. Railway systems consume a huge amount of energy, during normal operation, some routes working near maximum energy capacity. Therefore, maximizing energy efficiency in railway systems has, recently, received attention from railway operators, leading to research for new solutions that are able to reduce energy consumption without timetable constraints. In line with these goals, this paper proposes a Simulated Annealing optimization algorithm that minimizes train traction energy, constrained to existing timetable. For computational effort minimization, re-annealing is not used, the maximum number of iterations is one hundred, and generation of cruising and braking velocities is carefully made. A Matlab implementation of the Simulated Annealing optimization algorithm determines the best solution for the optimal speed profile between stations. It uses a dynamic model of the train for energy consumption calculations. Searching for optimal speed profile, as well as scheduling constraints, also uses line shape and velocity limits. As results are obtained in seconds, this new algorithm can be used as a real-time driver advisory system for energy saving and railway capacity increase. For now, a standalone version, with line data previously loaded, was developed. Comparison between algorithm results and real data, acquired in a railway line, proves its success. An implementation of the developed work as a connected driver advisory system, enabling scheduling and speed constraint updates in real time, is currently under development.

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