Name
Abstract | ||
|---|---|---|
We consider a utility who seeks to coordinate the energy consumption of multiple demand-side flexible resource aggregators. For the purpose of privacy protection, the utility has no access to the detailed information of loads of resource aggregators. Instead, we assume that the utility can directly observe each aggregator’s aggregate energy consumption outcomes. Furthermore, the utility can leverage resource aggregator energy consumption via time-varying electricity price profiles. Based on inverse optimization technique, we propose an estimation method for the utility to infer the energy requirement information of aggregators. Subsequently, we design a data-driven pricing scheme to help the utility achieve system-level control objectives (e.g., minimizing peak demand) by combining hybrid particle swarm optimizer with mutation (HPSOM) algorithm and an iterative algorithm. Case studies have demonstrated the effectiveness of the proposed approach against two benchmark pricing strategies – a flat-rate scheme and a time-of-use (TOU) scheme. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TSG.2016.2544939 | IEEE Trans. Smart Grid |
Keywords | Field | DocType |
Pricing,Energy consumption,Optimization,Aggregates,Indexes,Power demand,Load modeling | Mathematical optimization,Economics,Data-driven,Inverse optimization,Leverage (finance),News aggregator,Iterative method,Multi-swarm optimization,Peak demand,Energy consumption | Journal |
Volume | Issue | ISSN |
PP | 99 | 1949-3053 |
Citations | PageRank | References |
4 | 0.45 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiwei Xu | 1 | 10 | 1.69 |
| Tianhu Deng | 2 | 27 | 5.69 |
| Zechun Hu | 3 | 80 | 14.70 |
| Yong-Hua Song | 4 | 291 | 29.51 |
| Jun Wang | 5 | 626 | 84.82 |