Name
Abstract | ||
|---|---|---|
Highway Rest areas have the opportunity to intelligently handle workload induced by customer arrivals so as to minimize energy consumption. Patterns of vehicle arrivals during the day can be automatically identified and proper action can be taken. Using some aspects of the Smart Meters, Smart Appliances and the Internet of Things, significant energy savings might be accumulated by temporarily switching off, or operating in economy mode if possible, certain appliances. In this case study a rest area featuring a number of electrical appliances is modeled and examined through a simulation. Useful findings are drawn about modes of operation that hit a balance between energy savings and customer service quality. In order to identify these modes of operation a multi-objective optimization problem is formulated and then solved using the genetic algorithm NSGA-II that returns the desired Pareto front. A human operator can then, by critically examining the different modes in the Pareto front, decide which operation mode is best suited for the problem at hand. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/3003733.3003793 | PCI |
Keywords | Field | DocType |
Multi-objective Optimization, Genetic Algorithms, Energy Management, Scheduling, Timetabling | Energy management,Scheduling (computing),Computer science,Workload,Multi-objective optimization,Real-time computing,Energy consumption,Optimization problem,Genetic algorithm,Energy minimization | Conference |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iordanis Xanthopoulos | 1 | 0 | 0.34 |
| George Goulas | 2 | 57 | 5.93 |
| Christos Gogos | 3 | 80 | 6.25 |
| Panayiotis Alefragis | 4 | 120 | 14.33 |
| Efthymios Housos | 5 | 219 | 14.71 |