Name
Abstract | ||
|---|---|---|
This paper proposes an interactive bidding strategy for smart distribution networks with clustered aggregators to effectively coordinate the energy and profit of each entity. In the proposed bi-level bidding model, there are two levels, where the upper level stands for the distribution operator (DO) to secure the operation quality and bid with energy aggregators (EAs), and the lower level represents each EA to bid for interactive energies with the DO and other EAs. An innovative interactive bidding mechanism is developed to take advantages of renewable generation and energy storage system (ESS). The priority-based decision making is applied to the lower level to elaborately map the bidding mechanism and lead each EA's market interaction. The proposed model is solved by a customized hierarchical genetic algorithm (HGA). Case studies on a practical distribution grid in China and the IEEE 33-bus test feeder demonstrate the effectiveness of the proposed methodology. |
Year | Venue | Keywords |
|---|---|---|
2017 | IEEE Industry Applications Society Annual Meeting | Aggregators,decision making,renewable integration,power market,hierarchical genetic algorithm |
Field | DocType | ISSN |
Energy storage,Mathematical optimization,Distribution networks,Renewable generation,Operator (computer programming),Engineering,Power market,Bidding,Genetic algorithm,Distribution grid | Conference | 0197-2618 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tianguang Lv | 1 | 8 | 3.29 |
| Wei-Jen Lee | 2 | 94 | 31.94 |
| Qian Ai | 3 | 12 | 6.62 |
| Songtao Lu | 4 | 84 | 19.52 |