Robust data-driven and fully distributed volt/var control for active distribution networks with multiple virtual power plants
Abstract
This paper proposes a data-driven and fully distributed volt/var control (VVC) method for active distribution networks (ADNs) with multiple virtual power plants (VPPs), which is model-free and robust against bad data in measurements. The proposed scheme combines the advantages of a robust regression based feedback optimization algorithm and a revised alternating direction multiplier method (ADMM). Each VPP continuously obtains local system feedback to correct control strategies, and exchanges only limited information with its neighbors. Furthermore, faster convergence is achieved by applying Nesterov’s accelerated gradient method to the dual update in ADMM. The effectiveness of the method is demonstrated via numerical simulations using several distribution systems.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Distributed VVC approaches aim to reduce the communication and computational burden of fully centralized OPF while still exploiting network information and coordination among devices.
“These methods aim to reduce the communication and computational burden of fully centralized OPF while still exploiting network information and coordination among devices.”
From Physics-Informed AI-Based EV smart inverter control for two-stage Volt/Var coordination in renewable-rich active distribution networks (2026) · cites this paper as [15]
Cited by
Sorted by citations
Zhong, Y., Qiu, J., Yang, Y., Zhang, C., Tao, Y., Sun, X., & Lai, S. (2026) · Energy and AI · doi:10.1016/j.egyai.2026.100869
- Authors
- Li, S., Wu, W., & Lin, Y.
- Affiliations
- Tsinghua University (CN)
- State Grid Fujian Electric Power Company (China) (CN)
- Venue
- IEEE Transactions on Smart Grid
- Published
- 2022-07
- Volume
- 13
- Issue
- 4
- Pages
- 2627-2638
- ISSN
- 1949-3053 (ISSN-L)
- 1949-3061
- OpenAlex
- W4226293814
- Cited by
- 54
- References
- 0
- Citations by year
- 2026: 14 · 2025: 11 · 2024: 14 · 2023: 12 · 2022: 3
- FWCI
- 2.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Smart Grid (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Optimal Power Flow Distribution
- Physical Sciences › Engineering › Control and Systems Engineering › Microgrid Control and Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
- Keywords
- volt/var control, active distribution networks, virtual power plants, distributed control, data-driven control, robust regression, bad data, alternating direction method of multipliers, Nesterov acceleration, model-free control
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
