Abstract:

To enhance the economic efficiency and coordination capability of virtual power plant (VPP) in electricity markets, this paper proposes a multi-timescale bidding strategy based on hierarchical and zonal regulation. Firstly, virtual power units are defined as unified modeling units for dispatch and trading. A zonal aggregation strategy is developed based on grid topology and overload risk, and external characteristic models of virtual power units are constructed to represent the regulation capability of VPP. Secondly, a multi-timescale bidding model covering both day-ahead and real-time markets is established, and the bi-level optimization problem is transformed into a single-level model via Karush-Kuhn-Tucker (KKT) conditions to reduce computational complexity. Finally, case studies are conducted to validate the effectiveness of the proposed model. Results demonstrate that the proposed strategy can effectively reduce modeling complexity while ensuring network security and privacy protection. It enables VPP to coordinate bidding in multi-time scale markets, with VPP revenue increasing by 15.8% and 17.2% compared to fixed bidding and the day-ahead market, respectively, thus enhancing its market adaptability and profitability.

Key words: virtual power plant, hierarchical and zonal regulation, multi-timescale