FAULT DETECTION AND DIAGNOSTIC SYSTEM FOR SMART METER
In the 21 st century due to the growing population and industries energy demand is on the rise. Moreover, fulfilling the increasing demand environmental problem is also a big challenge
due to the burning of fossil fuels. So, all the existing infrastructure needs to be improved to an efficient system. Smart Grid is the step towards optimal power utilization. A smart meter
is one of the crucial parts of a smart grid which deals directly at the consumer end along with the option of net metering that gives power back to the grid when load consumption is low
and production is high at consumer e.g. Solar panels. This also saves power and reduces the energy cost for the consumer. For this purpose, the design and development of a reliable
smart meter is a very important task. So, the research focus will be the development of a system that detects faults and diagnose the problem in smart meters. In this research, a system
will be designed based on mathematical modeling and control system techniques along with existing solutions from the current literature and experiences. It is capable to identify and
analyze some commonly occurring software and hardware problems in smart meters.
Additionally, it will also minimize power theft. There is a lack of research on the consumer end for a smart meter. There is a need for an integrated standalone system that can deal with
hardware and software problems simultaneously in real-time. The proposed methodology will be an integrating system that will acquire the data, analyze it, identify the fault based on
mathematical models and fault identification logic and take remedial action using modern control techniques e.g. State Estimators. Safety and reliability are absolutely important for
modern sophisticated systems and technologies. Therefore, malfunction monitoring capabilities are instilled in the system for detection of incipient faults and anticipation of their
impact on the future behavior of the system using fault diagnosis techniques. In particular, state-of-the-art applications rely on the quick and efficient treatment of malfunctions within
the equipment/system, resulting in increased production and reduced downtimes.