Name
Abstract | ||
|---|---|---|
In this paper, both bottom-up and top-down models for demand response with agent-base approach and neural networks have been investigated. Simulations have been carried out with practical load data from the UK and Canada. Results show that each approach has its advantages and disadvantages depending on difference application scenarios. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SMC.2013.227 | SMC |
Keywords | Field | DocType |
agent-base approach,neural network,difference application scenarios,residential customer demand response,decision making,agent-based modeling,agent,canada,demand response,united kingdom,marketing data processing,multi-agent systems,difference application scenario,bottom-up demand response model,top-down demand response model,uk,customer satisfaction,practical load data,residential customer,top-down model,neural nets,residential customer demand,multi agent systems | Customer satisfaction,Industrial engineering,Computer science,Demand response,Multi-agent system,Artificial intelligence,Artificial neural network,Machine learning | Conference |
ISSN | Citations | PageRank |
1062-922X | 0 | 0.34 |
References | Authors | |
1 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fang-Yuan Xu | 1 | 9 | 4.57 |
| Xue Wang | 2 | 0 | 0.34 |
| Loi Lei Lai | 3 | 135 | 38.72 |
| Chun Sing Lai | 4 | 41 | 15.62 |