Some 175 years ago Michael Faraday discovered magnetic circular birefringence, now commonly known as the Faraday effect. Sensing the magnetic field through the influence that the field has on light within the fiber optic sensor offers several advantages, one of them fundamental. These advantages find application in the measurement of electric current at high voltages by measuring the induced magnetic field, thus warranting application for this kind of fiber optic sensor (FOS) in future smart grids. Difficulties in designing and manufacturing high-performance FOSs were greatly alleviated by developments in optical telecommunication technology, thus giving new impetus to magnetometry based on the Faraday effect. Some of the major problems in the processing of optical signals and temperature dependence have been resolved, yet much effort is still needed to implement all solutions into a single commercial device. Artificial structures with giant Faraday rotation, reported in the literature in the 21st century, will further improve the performance of FOSs based on the Faraday effect. This paper will consider obstacles and limits imposed by the available technology and review solutions proposed so far for fiber optic sensors based on the Faraday effect.

Fiber Optic Sensors Based on the Faraday Effect.

Fractional calculus is a 300 years topic, which has been introduced to real physics systems modeling and engineering applications. In the last few decades, fractional-order nonlinear chaotic systems have been widely investigated. Firstly, the most used methods to solve fractional-order chaotic systems are reviewed. Characteristics and memory effect in those method are summarized. Then we discuss the memory effect in the fractional-order chaotic systems through the fractional-order calculus and numerical solution algorithms. It shows that the integer-order derivative has full memory effect, while the fractional-order derivative has nonideal memory effect due to the kernel function. Memory loss and short memory are discussed. Finally, applications of the fractional-order chaotic systems regarding the memory effects are investigated. The work summarized in this manuscript provides reference value for the applied scientists and engineering community of fractional-order nonlinear chaotic systems.

Solutions and memory effect of fractional-order chaotic system: A review

High reliability and measurement accuracy are the premises and foundations of the practical use of optical transformer in power systems. Based on the theory of power optic sensor and model structure, the implementation plans for magneto-optical glass type as well as all-fiber type current transformer and electro-optic crystal type as well as all-fiber type voltage transformer are classified and compared, the advantages and disadvantages in the aspects of detection algorithms and manufacturing processes are also pointed out. Finally, the problems associated with the practical use of optical sensing technology and research directions are discussed.

Study and comment of the optical transformers in power system

The paper introduces fundamental principles and main characteristics of the fiber optical current transformer(FOCT),compares in detail with the Rogowski coil type CT and magneto-optical CT,analyzes the advantages preferable to relay protection by using FOCTFacing the main problems in the engineering application of FOCT,the paper suggests solving measures

The Fiber Optical Current Transformer(FOCT) Technology and It's Engineering Application

The beat length of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> /4 wave plate of fiber optic current transformer (FOCT) will change with the temperature fluctuation of environment, which will result in additional phase error, reducing the accuracy of current measurement. In this article, we presented an FOCT based on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> /4 wave plate fabricated with polarization-maintaining photonic crystal fiber (PCF). Combined with the error model caused by the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> /4 wave plate in FOCT, we analyzed the specific mechanism of temperature influence on the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> /4 wave plate. Aiming at the problem of fusing PCF to panda polarization-maintaining fiber, we optimized the related parameters of fiber fusion splicer to reduce the fusion loss of the fiber. It was experimentally verified that the beat length of PCF is less sensitive to temperature than that to elliptical-core polarization-maintaining fiber. Finally, we measured the current of FOCT utilizing two kinds of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> /4 wave plates in a full temperature range from −40 °C to 70 °C. It was verified that it is insensitive to temperature for FOCT when utilizing PCF <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> /4 wave plate, with the corresponding system current measurement accuracy at 0.5S level. 

A Method for Suppressing Error of Fiber Optic Current Transformer Caused by Temperature Based on λ/4 Wave Plate Fabricated With Polarization-Maintaining Photonic Crystal Fiber

The fiber optic current sensor (FOCS) is susceptible to external temperature in actual operation, which will lead to its accuracy deviation, even malfunction. In order to improve the temperature stability of FOCS’s ratio error, a temperature compensation method based on RBF neural network is established by taking the temperature as input and the ratio error as output to the network. Compared with BP neural network, the simulation results show that the temperature compensation model based on RBF neural network has better accuracy whose prediction error is less than 3%. At the same time, the experimental results show that the drift deviation of ratio error can remain as low as ±0.1% in the range of -40 °C to 70°C, and the 0.2S-level accuracy of GBT20840.8 standard can be achieved.

Fiber optic current sensor temperature compensation through RBF neural network

The engineering application number of fiber optic current sensor (FOCS) is decreasing year by year since 2012 in China due to its reliability problems. However, the researchers and related enterprises have also made some constructive attempts on the study of fault diagnosis of FOCS. In this paper, the application status and the common fault modes of FOCS are analyzed. Three ways to diagnosing the soft and hard fault of FOCS are reviewed, including based on analytical model, on signal processing and on knowledge. Finally, the research direction of FOCS fault diagnosing is prospected. It is concluded that the diversified and intelligent fault diagnosis method based on knowledge has more advantages compared with the other two methods. In addition, the development of FOCS for integrated optical path is of great help in improving its reliability and will be a research hotspot in the future.

Fault diagnosing methods of fiber optic current sensor: a review

The invention relates to a fault diagnosis method and device of an optical fiber current transformer. An original optical path and a circuit structure of the optical fiber current transformer are keptunchanged, and the output data amount of 'protection channel 1 data', 'protection channel 2 data' and 'metering channel data', and state quantity of 'optical power meter value', 'voltage value' and 'temperature value' of the transformer are separately subjected to the relevant data treatment; and compared with a set threshold value, if a threshold range is exceeded, a relevant diagnostic programis started, and an early warning and an alarm hint are carried out. According to the fault diagnosis method and device of the optical fiber current transformer, the fault diagnosis method is integrated and totalized, the working state of the transformer can be accurately detected in real time, and warning and alarming are carried out on a fault situation in time.

Fault diagnosis method and device of optical fiber current transformer

This paper is concerned with development and optimization of strategies for direct wind power supply to industrial consumers based on big data analysis, for the purpose of achieving economic benefit for both wind power generation companies and industrial enterprises. A basic database was established, which contains historical data of wind power output and industrial electric load, as well as meteorological parameters that have significant influence on wind velocity and social parameters that are strongly related to production of industrial companies. A combined model based on cluster analysis and Back Propagation Neural Network algorithm was built for characterization and prediction of wind power output and industrial load, and MapReduce algorithm was utilized to achieve big data analysis process. The effectiveness of recommended strategies is validated through case study which considered five typical industrial companies and fifteen wind farms in northeast of China. The result shows that the recommended strategies can achieve extra economic benefit of roughly Ұ 200,000 per year in theory.

Research on Strategy for Direct Wind Power Supply to Industrial Consumers based on Big Data Analysis

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Papers

Fiber optic current sensor temperature compensation through RBF neural network

Fault diagnosing methods of fiber optic current sensor: a review

Fault diagnosis method and device of optical fiber current transformer

Research on Strategy for Direct Wind Power Supply to Industrial Consumers based on Big Data Analysis