| Robotic
Monitoring of Power Systems |
INTROUCTION
Economically effective maintenance
and monitoring of power systems to ensure high quality and reliability of electric
power supplied to customers is becoming one of the most significant tasks of today's
power industry. This is highly important because in case of unexpected failures,
both the utilities as well as the consumers will have to face several losses.
The ideal power network can be approached through minimizing maintenance cost
and maximizing the service life and reliability of existing power networks. But
both goals cannot be achieved simultaneously. Timely preventive maintenance can
dramatically reduce system failures. Currently, there are three maintenance methods
employed by utilities: corrective maintenance, scheduled maintenance and condition-based
maintenance. The following block diagram shows the important features of the various
maintenance methods. Corrective
maintenance dominates in today's power industry. This method is passive, i.e.
no action is taken until a failure occurs. Scheduled maintenance on the other
hand refers to periodic maintenance carried out at pre-determined time intervals.
Condition-based maintenance is defined as planned maintenance based on continuous
monitoring of equipment status. Condition-based maintenance is very attractive
since the maintenance action is only taken when required by the power system components.
The only drawback of condition-based maintenance is monitoring cost. Expensive
monitoring devices and extra technicians are needed to implement condition-based
maintenance. Mobile monitoring solves this problem. Mobile
monitoring involves the development of a robotic platform carrying a sensor array.
This continuously patrols the power cable network, locates incipient failures
and estimates the aging status of electrical insulation. Monitoring of electric
power systems in real time for reliability, aging status and presence of incipient
faults requires distributed and centralized processing of large amounts of data
from distributed sensor networks. To solve this task, cohesive multidisciplinary
efforts are needed from such fields as sensing, signal processing, control, communications
and robotics. As
with any preventive maintenance technology, the efforts spent on the status monitoring
are justified by the reduction in the fault occurrence and elimination of consequent
losses due to disruption of electric power and damage to equipment. Moreover,
it is a well recognized fact in surveillance and monitoring fields that measurement
of parameters of a distributed system has higher accuracy when it is when it is
accomplished using sensing techniques. In addition to sensitivity improvement
and
subsequent
reliability enhancement, the use of robotic platforms for power system maintenance
has many other advantages like replacing man workers for dangerous and highly
specialized operations such as live line maintenance.
MOBILE
ROBOT PLATFORM Generally
speaking, the mobile monitoring of power systems involves the following issues:
SENSOR FUSION: The aging of power cables begins long before the cable actually
fails. There are several external phenomena indicating ongoing aging problems
including partial discharges, hot spots, mechanical cracks and changes of insulation
dielectric properties. These phenomena can be used to locate the position of the
deteriorating cables and estimate the remaining lifetime of these cables. If incipient
failures can be detected, or the aging process can be predicted accurately, possible
outages and following economical losses can be avoided.
In the robotic platform, non-destructive miniature sensors capable of determining
the status of power cable systems are developed and integrated into a monitoring
system including a video sensor for visual inspection, an infrared thermal sensor
for detection of hot spots, an acoustic sensor for identifying partial discharge
activities and a fringing electric field sensor for determining aging status of
electrical insulation. Among failure phenomena, the most important one is the
partial discharge activity
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