Online Constructive Method for Computing Renewable Energy Admissible Injections Region Using Adaptive Expansion Schemes: A New EMS Function
This paper proposes a potential new energy management system (EMS) function for managing the uncertainty of renewable energy injecting the power grid. The new function can be viewed as a complement to the existing function of real time contingency analysis (RTCA) that manages the uncertainty from the power grid to meeting the N-1 guideline. The Admissible Region for Renewable Power Injection (ADMIRE) quantifies the amount of renewable energy (RE) for each site that the power grid can accommodate without causing operational and engineering violations. With this capability, ADMIRE holds the potential to emerge as a new EMS function for RE integration. In this paper, a Constructive region expansion (CoreX) method for on-line computation of ADMIRE is proposed along with an analytical basis. This method iteratively constructs a convex set for approximating feasible RE injection points where the new feasible points are obtained in a targeted space in each iteration. The innovative CoreX method can compute the ADMIRE using the exact AC power flow nonlinear model and has flexibility to adaptively expand the computed feasible points of ADMIRE in any targeted space for RE uncertainty security evaluation. The existing functions, static security assessment, and dynamic security assessment, available in modern control centers were designed to manage network uncertainty, not renewable uncertainty. In this paper, a renewable uncertainty security assessment is proposed based on the proposed on-line CoreX method. Numerical studies conducted on the 9-bus, 1354-bus, and real 3104-bus systems validate the computational effectiveness of the proposed method and underscore its efficiency in online assessing the operational impacts due to renewable energy uncertainty.
Authors
- Hsiao‐Dong Chiang (ORCID: https://orcid.org/0000-0003-0769-5071)
- Lin Zeng (ORCID: https://orcid.org/0000-0002-1134-594X)
Institutions
- Cornell University (US)
Publication Details
- Journal
- IEEE Transactions on Power Systems
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1109/tpwrs.2025.3605067
- Primary Topic
- Advanced Control Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00