Author
Listed:
- Tan, Hong
- Yang, Ao
- Lin, Zhenjia
- Ge, Leijiao
- Wang, Qiujie
- Gao, Yuan
Abstract
The Electric-Hydrogen Virtual Power Plant aggregates internal distributed energy resources to achieve joint electricity and hydrogen output, providing a new pathway for accommodating surplus renewable energy generation. However, precise modeling methods for the uncertain operating region of EH-VPP remain challenging. In this regard, this paper first defines the uncertain operating region of EH-VPP and constructs its internal optimization model. Then, based on multi-parameter programming theory and the cutting-plane method, the mapping relationship of the EH-VPP electricity‑hydrogen joint output curve is analytically derived. Based on this, the probability density function of the projection points of the electricity‑hydrogen joint curve onto the hydrogen production rate axis is derived, incorporating the known probability distributions of input random variables, thereby enabling probabilistic modeling of the uncertain operating region boundary. Finally, the opportunity constraint method is applied to construct the uncertain operating region of EH-VPP, which is then used in the coordinated scheduling optimization of the electric‑hydrogen integrated energy system. Simulation results show that the proposed method efficiently characterizes the uncertain operating region with an error of less than 0.05 %, supports flexible modeling based on confidence levels, and ensures both scheduling security and computational efficiency in large-scale collaborative scheduling scenarios.
Suggested Citation
Tan, Hong & Yang, Ao & Lin, Zhenjia & Ge, Leijiao & Wang, Qiujie & Gao, Yuan, 2025.
"Uncertain operation region of electricity-hydrogen virtual power plant: Concept and description method,"
Applied Energy, Elsevier, vol. 396(C).
Handle:
RePEc:eee:appene:v:396:y:2025:i:c:s0306261925009407
DOI: 10.1016/j.apenergy.2025.126210
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:396:y:2025:i:c:s0306261925009407. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.