- Title
- Real-time prediction of event-driven load shedding for frequency stability enhancement of power systems
- Creator
- Dai, Y.; Xu, Y.; Dong, Z. Y.; Wong, K. P.; Zhuang, L.
- Relation
- IET Generation, Transmission and Distribution Vol. 6, Issue 9, p. 914-921
- Publisher Link
- http://dx.doi.org/10.1049/iet-gtd.2011.0810
- Publisher
- The Institution of Engineering and Technology
- Resource Type
- journal article
- Date
- 2012
- Description
- Maintaining frequency stability is one of the three dynamic security requirements in power system operations. As an emergency control, event-driven load shedding (ELS), which is determined preventively and triggered immediately after fault occurrence, can effectively prevent frequency instability. This study proposes a methodology for real-time predicting required ELS against severe contingency events. The general idea is to train an extreme learning machine-based prediction model with a strategically prepared ELS database, and apply it on-line for real-time ELS prediction. The methodology can overcome the shortcomings of conventional deterministic approaches by its high generalisation capacity and accuracy. It can either be an individual tool or a complement to deterministic approaches for enhancing the overall reliability of the ELS strategy. Its feasibility and accuracy are verified on the New England 10-machine 39-bus system, and the simulation results show that the prediction is acceptably accurate and very fast, which is promising for practical use.
- Subject
- ELS; ELM; power systems; frequency stability
- Identifier
- http://hdl.handle.net/1959.13/1319097
- Identifier
- uon:23781
- Identifier
- ISSN:1751-8687
- Language
- eng
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