Name
Abstract | ||
|---|---|---|
This paper considers the problem of optimal battery usage under real-time pricing scenarios. The problem is formulated as a finite-horizon optimization problem, and solved via an incremental algorithm that is provably optimal in the long run. The proposed approach gives rise to a class of algorithms that utilize the battery state-of-charge to make usage decisions in real-time. The proposed algorithm is simple to implement, easy to modify for a variety use cases, and outperform the state-of-the-art technique such as Markov Decision Process (MDP) based. The robustness and flexibility of the proposed algorithm is tested extensively via numerical studies. |
Year | Venue | Keywords |
|---|---|---|
2017 | 2017 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS) | Incremental gradient descent, storage optimization, real-time pricing |
Field | DocType | ISSN |
Mathematical optimization,Markov process,Use case,Smart grid,Computer science,Markov decision process,Real time pricing,Robustness (computer science),Battery (electricity),Optimization problem | Conference | 2164-7038 |
Citations | PageRank | References |
0 | 0.34 | 19 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amrit S. Bedi | 1 | 7 | 2.14 |
| Md. Waseem Ahmad | 2 | 2 | 0.77 |
| Ketan Rajawat | 3 | 124 | 25.44 |
| Sandeep Anand | 4 | 22 | 5.55 |