Vulnerability of modern power systems to locally initiated voltage collapse gives rise to a need for methods to measure local voltage security and to predict voltage instability. The paper presents a novel architecture based on a suite of AI technologies and three-dimensional PQV surfaces which provides prediction of local voltage collapse and indices of system voltage security. Robustness and adaptation are demonstrated on difficult and realistic power system simulation models.
- Artificial intelligence
- Fuzzy kaiman filters
- Neuro-fuzzy systems
- Voltage stability
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering