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1486. Dynamic Expansion Planning of a Commercial Virtual Power Plant through Coalition with Distributed Energy Resources considering Rival Competitors
Invited abstract in session MA-21: Planning problems in electrical energy systems, stream OR in Energy.
Monday, 8:30-10:00Room: 49 (building: 116)
Authors (first author is the speaker)
| 1. | Santiago Maiz
|
| Electrical Engineering, Universidad de Castilla-La Mancha | |
| 2. | Raquel García-Bertrand
|
| Electrical Engineering, University of Castilla-La Mancha | |
| 3. | Luis Baringo
|
| Electrical Engineering, Universidad de Castilla-La Mancha |
Abstract
We consider a virtual power plant (VPP) that expands its capacity by forming a mid-term coalition with distributed energy resources (DERs) such as conventional and renewable power plants, as well as with energy storage systems and flexible demands. The VPP competes with rival VPPs to aggregate the DERs to its own portfolio. This problem is formulated as a three-stage stochastic bi-level model, where the expected profit of the VPP is maximized in the upper-level problem, while the lower-level problems deal with the decisions of each DER regarding the selection of VPP. In the first stage, the VPP manager places bids to secure each DER auction. The second stage involves decisions to determine the DER auctions, forming the VPP coalition and the procurement of power from the day-ahead market. Uncertainties in this stage include bid prices of rival VPPs and the minimum selling price of DERs. Finally, in the third stage, the expanded VPP determines its optimal operation and manages uncertainties related to renewable energy production levels and market prices. Variability of parameters such as market prices and renewable energy production levels (both solar and wind) is modeled using representative days generated by a clustering K-medoids method. The model incorporates Conditional Value-at-Risk (CVaR) as a risk metric. Through a case study using real data, it is demonstrated that weather conditions and electricity demand significantly influence the coalition formation.
Keywords
- Engineering Optimization
- Electricity Markets
- OR in Energy
Status: accepted
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