Abstract
In order to achieve more efficient voltage regulation in a power system, coordinated secondary voltage control has been proposed, bringing in the extra benefit of enhancement of power system voltage stability margin. This paper investigates a new potential application of coordinated secondary voltage control by multiple FACTS voltage controllers in eliminating voltage violations in power system contingencies. The study is presented by the example New England ten-machine power system with two SVCs and two STATCOMs installed. The coordinated secondary voltage control is assigned to the SVCs and STATCOMs in order to eliminate voltage violations in system contingencies. In the paper, it is proposed that the secondary voltage control is implemented by a learning fuzzy logic controller. A key parameter of the controller is trained by P-type learning algorithm via offline simulation with the assistance of injection of artificial loads in controller's adjacent locations. A multiagent collaboration protocol, which is graphically represented as a finite-state machine, is proposed in the paper for the coordination among multiple SVCs and STATCOMs. As an agent, each SVC or STATCOM can provide multilocation coverage to eliminate voltage violations at its adjacent nodes in the power system. Agents can provide collaborative support to each other which is coordinated according to the proposed collaboration protocol.
Original language | English |
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Pages (from-to) | 588-595 |
Number of pages | 8 |
Journal | Power Systems, IEEE Transactions on |
Volume | 18 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2003 |
Keywords
- power system control
- multi-agent theory
- coordinated secondary voltage control
- power system voltage stability margin
- artificial loads injection
- multi-agent systems
- New England ten-machine power system
- voltage control
- fuzzy logic controller
- STATCOM
- multilocation coverage
- learning algorithm
- multiagent collaboration protocol
- flexible AC transmission systems
- static VAr compensators
- power system dynamic stability
- SVC
- finite-state machine
- P-type learning algorithm
- voltage violations elimination
- offline simulation
- FACTS voltage controllers
- fuzzy control