With the deregulation of power industry, many tie lines between control areas are driven to operate near their maximum capacity, especially those serving heavy load centers. Wide area controllers (WACs) using wide-area or global signals can provide remote auxiliary control signals to local controllers such as automatic voltage regulators, power system stabilizers, etc to damp out inter-area oscillations. The power system is highly nonlinear system with fast changing dynamics. In order to have an efficient WAC, an online system monitor/predictor is required to provide inter-area information to the WAC from time to time. This paper presents the design of an online wide area monitor (WAM) using a neural network called the wide area neuroidentifier (WANI). The WANI is used to predict ahead the speed deviations of generators in the different areas using phasor measurement unit (PMU). Results are presented to show the effectiveness of the wide area monitor for different disturbances.
X. Li and G. K. Venayagamoorthy, "A Neural Network Based Wide Area Monitor for a Power System," Proceedings of the IEEE Power Engineering Society General Meeting, 2005, Institute of Electrical and Electronics Engineers (IEEE), Jan 2005.
The definitive version is available at https://doi.org/10.1109/PES.2005.1489743
IEEE Power Engineering Society General Meeting, 2005
Electrical and Computer Engineering
Keywords and Phrases
Automatic Voltage Regulators; Computerised Monitoring; Control Engineering Computing; Interarea Oscillations; Neural Network; Neurocontrollers; Nonlinear Control Systems; Nonlinear System; Online System Monitor; Phase Measurement; Phasor Measurement Unit; Power Engineering Computing; Power Industry Deregulation; Power System Based Wide Area Monitor; Power System Measurement; Power System Stabilizers; Remote Auxiliary Control Signals; Wide Area Controllers; Wide Area Neuroidentifier
Article - Conference proceedings
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