TITLE:
Distributed Adaptive Learning Framework for Wide Area Monitoring of Power Systems Integrated with Distributed Generations
AUTHORS:
Kang Li, Yuanjun Guo, David Laverty, Haibo He, Minrui Fei
KEYWORDS:
Smart Grid; Anti-islanding Protection; Distributed Agents; Incremental Learning; Monitoring and Control
JOURNAL NAME:
Energy and Power Engineering,
Vol.5 No.4B,
November
12,
2013
ABSTRACT: This paper presents a preliminary study of developing a
novel distributed adaptive real-time learning framework for wide area
monitoring of power systems integrated with distributed generations using
synchrophasor technology. The framework comprises distributed agents
(synchrophasors) for autonomous local condition monitoring and fault detection,
and a central unit for generating global view for situation awareness and
decision making. Key technologies that can be integrated into this hierarchical
distributed learning scheme are discussed to enable real-time information extraction
and knowledge discovery for decision making, without explicitly accumulating
and storing all raw data by the central unit. Based on this, the configuration
of a wide area monitoring system of power systems using synchrophasor technology,
and the functionalities for locally installed open-phasor-measurement-units
(OpenPMUs) and a central unit are presented. Initial results on anti-islanding
protection using the proposed approach are given to illustrate the effectiveness.