Background
I. Background
What is Power Quality?
Any voltage or current deviation from a perfect sinusoidal waveform that can results in failure or misoperation of customer equipment.
Quality of the current and voltage provided to the customers means,
Providing customers with a clean sinusoidal waveforms at 60 Hz without sags or spikes.
Providing power to allow sensitive electronic equipment operate reliably.
Why Power Quality Become More and More Important?
Proliferation of highly sensitive computerized equipment places more stringent demands on PQ,
such as Semiconductor industry, Computers and computer-related businesses, Variable-speed drives or robots,
Programmable logic controllers
Electronic equipment results in more PQ problems
Deregulation of power industry creates more competitive market.
Some facts: (Impact to Silicon Valley)
- One cycle interruption makes a silicon device worthless
- Five minutes shut down of a chip fabrication plant causes delay from a day to a week
- One second of power outage makes e-commerce sites lose millions of dollars worth of business.
Some figures: US PQ losses: $20 billion/year (Frost & Sullivan)
State of the Art
PQ monitoring software and hardware are needed in both utilities and customers
- Detect, identify, and localize different PQ disturbances
- Real time decision making
The topic of a general event classification (opposed to individual fault detection) has rarely been addressed
Existing automatic recognition methods need much improvement in terms of their versatility, reliability, and accuracy.
The accumulation of a comprehensive PQ database will significantly expedite the birth of the solutions
Scope of this Project and Current Status
The figure below shows the scope of this research project, with a red circle indicating the
current status of the project, which is also the scope of Min Wang's Master thesis.
Goals of this research project
-Enhancement of real-time power system protection
-Statistical accumulations of power quality problems
-Incipient fault detections
Current work -- Applying advanced signal processing techniques to identification of power quality events
