Name
Abstract | ||
|---|---|---|
Demand response (DR) is used in smart grids to shape customer load during peak hours. Automated DR offers utilities a fine grained control and a high degree of confidence in the outcome. However the impact on the customer's comfort means this technique is more suited for industrial and commercial settings than for residential homes. In this paper we present a real-life system for achieving automated controlled DR in a heterogeneous environment. The system is integrated with the USC microgrid. Results show that while on a per building per event basis the accuracy of our prediction and customer selection techniques varies, it performs well on average when considering several events and buildings. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2768510.2775333 | International Conference on Future Energy Systems |
Field | DocType | Citations |
Traffic analysis,Smart grid,Demand response,Real-time computing,Dynamic demand,Engineering,Reliability engineering,Microgrid | Conference | 1 |
PageRank | References | Authors |
0.37 | 17 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marc Frîncu | 1 | 10 | 2.67 |
| Charalampos Chelmis | 2 | 156 | 27.09 |
| Muhammad Rizwan Saeed | 3 | 4 | 3.14 |
| Viktor K. Prasanna | 4 | 7211 | 762.74 |
| Saima Aman | 5 | 227 | 18.13 |
| Vasileios Zois | 6 | 1 | 0.71 |
| Carol Fern | 7 | 1 | 0.37 |
| Aras Akbari | 8 | 1 | 0.37 |