1. Development of Power Harmonic Detection
In power systems, the ideal current and voltage waveforms are sinusoidal waves at the power frequency. However, in reality, various distortions often exist. Especially in recent years, the continuous application of variable frequency drives, converters, and electronic equipment in distribution networks has led to an increase in nonlinear loads, causing severe distortion of the current and voltage waveforms in the power system. This results in a large number of harmonics in the power grid, causing numerous power accidents. Therefore, harmonic pollution is currently recognized as a major public hazard affecting power grid safety. In the process of harmonic mitigation, harmonic monitoring is the main method, which is the foundation for solving harmonic hazards and provides guidance for identifying specific harmonics. According to the development history of harmonic detection, it can be mainly divided into three stages: First, from the early 19th century to the 1940s, harmonic detection was mainly based on Fourier transform; second, from the 1950s to the 1980s, frequency-selective measurement technology was mainly used; third, from the 1980s to the present, with the development of computer technology, microprocessor technology, and integrated circuits, spectrum analyzers and harmonic analyzers based on fast Fourier transform have emerged. The use of these detection instruments has greatly improved the accuracy of calculation results. In my country, the use of this algorithm and phase-locked loop technology to measure harmonics began in the 1980s, and it has now developed into a digital, electronic, and intelligent harmonic testing method.
2. Principle and Method of Harmonic Detector
2.1 Measurements were performed using analog bandstop or bandpass filters.
This is the earliest method for harmonic measurement. Its advantages lie in its low circuit cost, simple structure, ease of control, and low output impedance. Its disadvantages include high susceptibility to environmental influences, low detection accuracy, the presence of a significant amount of fundamental frequency components in the test results, and relatively high operating losses.
2.2 Harmonic Detection Based on Neural Networks
This research outcome, namely neural networks, is based on the improvement of computational power and the approximation of arbitrary continuous functions, obtained through theoretical learning and analysis of dynamic networks. Currently, the application of this network in power system harmonic detection is still in its early stages, primarily focusing on harmonic prediction, harmonic source identification, and harmonic measurement. When using neural networks in harmonic measurement, the main considerations are network composition, algorithm selection, and sample determination.
2.3 Wavelet Analysis Method for Harmonic Measurement
Significant progress has been made in this area of research, primarily in addressing the shortcomings of Fourier transform in terms of complete locality absence in the time domain and complete localization in the frequency domain, meaning it exhibits locality in both the time and frequency domains. This method allows the projection of higher harmonic variations in power systems onto different scales, thereby reflecting the characteristics of singular, high-frequency, higher harmonic signals and providing a basis for harmonic analysis.
2.4 FFT Transformation Method
This method for detecting harmonics in power systems is a measurement approach based on digital signal processing. The main steps involve first sampling the voltage or current of the signal to be measured, then converting the sample, and finally performing a Fourier transform using a computer to obtain the phase coefficient and amplitude of each harmonic. This method is currently the most widely used harmonic detection method in power systems, characterized by high accuracy, multiple functions, and ease of operation, thus ensuring accurate harmonic detection.
3. Research on power communication technology
In today's society, the demand for electricity is increasing, and the requirements for the reliability of power supply are also constantly rising. Harmonics in the power grid bring many negative impacts to the power system. These mainly manifest as follows: increased losses in power generation, transmission, supply, and consumption equipment to varying degrees, reducing equipment utilization and efficiency; decreased reliability of automatic devices and relay protection; inaccurate readings of measuring instruments, as harmonics affect the operation of instruments and meters; interference with communication systems, affecting the safety of communication equipment and personnel; and negatively impacting consumption equipment, causing malfunctions and reducing equipment lifespan. Therefore, the power system should strictly monitor harmonics and improve the power environment.
With the development of the power industry, the power communication industry has also experienced rapid growth, greatly enhancing communication capabilities. The emphasis on and research into power quality has made ensuring power quality a consensus among power companies. Establishing a systematic and efficient online power monitoring network for monitoring and managing the power grid has become essential. This allows for real-time monitoring of power quality levels, identifying the causes affecting the safe operation of the power grid, and taking timely and effective measures to improve the power supply quality, ensure the safe operation of the power grid, and achieve economic benefits. The impact of power harmonics has been ongoing. While power harmonic detection instruments are complex and diverse, compatibility between different instruments remains a challenge. To address this issue, the PQDIF data format has become a unified standard, enabling effective data management, resource sharing, and establishing a practical and universal platform, thus introducing power quality detection into a standardized development stage. From both an economic and efficiency perspective, this avoids the unsatisfactory data processing results caused by different data formats. The application of PQDIF format storage and transmission based on the internet in power harmonic detection systems has also contributed to the development of power communication technology.
4. Conclusion
With the development of information and communication technologies, power quality detection technology is moving towards informatization, networking, and standardization, becoming more adaptable to the operation of power systems. In power system harmonic detection, better integration of computer, communication, and electronic technologies is the development trend of harmonic detection.
