A slab-coupled optical fiber sensor (SCOS) falls into a narrow class of all-dielectric optical fiber electric field sensors, which makes it a perfect candidate for measurements of high electric fields in environments where presence of conductors is highly perturbing to the system under test. Its nonlinear response to high fields requires a new nonlinear calibration technique. A nonlinear calibration method is explained and demonstrated to successfully measure high electric fields, as well as high voltages with dynamic range up to 50 dB. Furthermore, a SCOS can be fitted into narrow spaces and make highly localized measurements due to its small size. This allows a SCOS to be integrated inside a standard high voltage coaxial cable, such as RG-218. Effects of partial discharge and arcing is minimized by development of a fabrication method to avoid introduction of impurities, especially air-bubbles, into the cable during SCOS insertion. Low perturbation of the measured voltage is shown by simulating the introduced voltage reflections to be on the order of –50 dB. It is also shown that a SCOS can be inserted into other cables without significant perturbation to the voltage. A complete high voltage and high electric field measurement system is built based on the high-voltage modifications of the SCOS technology. The coaxial SCOS is enhanced for robustness. Enhancements include packaging a SCOS into stronger ceramic trough, strengthening the fiber with kevlar reinforced furcation tubing and protecting the sensor with metal braces and protective shells. The interrogator is protected from electromagnetic interference with an RF-shielded box. Reduction in power losses introduced by the new PANDA-SCOS technology allows interrogator bandwidths to be increased up to 1.2 GHz. The whole measurement process is streamlined with dedicated software, developed specifically for high voltage and electric field measurements with support for the nonlinear calibration.

A slab-coupled optical fiber sensor (SCOS) falls into a narrow class of all-dielectric optical fiber electric field sensors, which makes it a perfect candidate for measurements of high electric fields in environments where presence of conductors is highly perturbing to the system under test. Its nonlinear response to high fields requires a new nonlinear calibration technique. A nonlinear calibration method is explained and demonstrated to successfully measure high electric fields, as well as high voltages with dynamic range up to 50 dB. Furthermore, a SCOS can be fitted into narrow spaces and make highly localized measurements due to its small size. This allows a SCOS to be integrated inside a standard high voltage coaxial cable, such as RG-218. Effects of partial discharge and arcing is minimized by development of a fabrication method to avoid introduction of impurities, especially air-bubbles, into the cable during SCOS insertion. Low perturbation of the measured voltage is shown by simulating the introduced voltage reflections to be on the order of −50 dB. It is also shown that a SCOS can be inserted into other cables without significant perturbation to the voltage.A complete high voltage and high electric field measurement system is built based on the high-voltage modifications of the SCOS technology. The coaxial SCOS is enhanced for robustness. Enhancements include packaging a SCOS into stronger ceramic trough, strengthening the fiber with kevlar reinforced furcation tubing and protecting the sensor with metal braces and protective shells. The interrogator is protected from electromagnetic interference with an RF-shielded box. Reduction in power losses introduced by the new PANDA-SCOS technology allows interrogator bandwidths to be increased up to 1.2 GHz. The whole measurement process is streamlined with dedicated software, developed specifically for high voltage and electric field measurements with support for the nonlinear calibration.

Over the last several decades, electricity consumption and generation have continually grown. Investment in the Transmission and Distribution (T&D) infrastructure has been minimal and it has become increasingly difficult and expensive to permit and build new power lines. At the same time, a growing increase in the penetration of renewable energy resources is causing an unprecedented level of dynamics on the grid. Consequently, the power grid is congested and under stress. To compound the situation, the utilities do not possess detailed information on the status and operating margins on their assets in order to use them optimally. The task of monitoring asset status and optimizing asset utilization for the electric power industry seems particularly challenging, given millions of assets and hundreds of thousands of miles of power lines distributed geographically over millions of square miles. The lack of situational awareness compromises system reliability, and raises the possibility of power outages and even cascading blackouts. To address this problem, a conceptual Power Line Sensor Network (PLSN) is proposed in this research. The main objective of this research is to develop a distributed PLSN to provide continuous on-line monitoring of the geographically dispersed power grid by using hundreds of thousands of low-cost, autonomous, smart, and communication-enabled Power Line Sensor (PLS) modules thus to improve the utilization and reliability of the existing power system. The proposed PLSN specifically targets the use of passive sensing techniques, focusing on monitoring the real-time dynamic capacity of a specific span of a power line under present weather conditions by using computational intelligence technologies. An ancillary function is to detect the presence of incipient failures along overhead power lines via monitoring and characterizing the electromagnetic fields around overhead conductors. This research integrates detailed modeling of the power lines and the physical manifestations of the parameters being sensed, with pattern recognition technologies. Key issues of this research also include design of a prototype PLS module with integrated sensing, power and communication functions, and validation of the Wireless Sensor Network (WSN) technology integrated to this proposed PLSN.