Recent Advances in Electrical & Electronic Engineering - Volume 15, Issue 6, 2022

Background: Conventionally, a two-stage conversion is required for providing isolated DC output. Objectives: This paper aimed at proposing a converter comprising three ports with isolated output and higher output power and voltage levels, and to study its switching operations. Methods: The converter has two input ports that connect an AC source and the solar PV source. The third port acts as an output port to supply the desired load. The proposed topology can supply the high dc output voltage with isolation while maintaining a high input power factor. A singlestage conversion is used in the converter, which helps in reducing the switching devices and the bulky electrolytic capacitor while integrating a solar PV. As there is no intermediate stage of conversion in the proposed converter, it is well suited for the standalone PV-based applications, such as remote light electric vehicle chargers. Results: The simulation verification of the proposed converter has been obtained in the MATLAB/SIMULINK, and the experimental results have been obtained via a control algorithm implemented using FPGA-based Typhoon HIL 402, which demonstrated the control method and working of topology to be effective. Conclusion: The desirable operation of the converter has been achieved.

Background: Previous works on total harmonic distortion (THD) minimization for multilevel inverters (MLI’s) have made a symmetrical approach that imposes Quarter Wave Symmetry (QWS) and Half Wave Symmetry (HWS) with the aim to restrict the computational difficulties to solve the finalized non-linear expressions. Objective: However, the QWS constraint can be abolished, which leads to more generalized formulations and multiple solutions corresponding to minimum THD for the complete modulation index range. Methods: A systematic search approach using MATLAB in-build function is adopted to investigate ideal angles of switching related to a three-level, three-phase inverter restricted to only HWS as a constraint for two and three (i.e., N = 2 and 3) switching transitions per quarter cycle. Results: On account of the effective minimization of the dominant low-order odd line voltage harmonics, the proposed pulse-width-modulation (PWM) scheme proved its superiority based on minimum THD% performance compared to the previously reported PWM techniques with both HWS and QWS being retained. Conclusion: The simulation and experimental findings show that the proposed non-symmetrical PWM scheme outperforms the classic PWM method limited to QWS and HWS symmetries across the whole modulation-index range, with the added benefit of a general formulation and many solutions.

Background: Most of the proposed interface circuits use bulky inductors to enhance the key performance parameter, i.e., power transfer efficiency. This sets constraints on designing power conditioning circuitry for constrained IoT applications. Objective: To replace the bulky physical inductor with area-optimized components suitable for integrated circuit realization with reduced silicon footprint for constrained applications like Internet-of- Things (IoT). Methods: This paper presents the implementation of Circuit Resonance with Active Inductor (CRAI) technique based interface circuit design to deliver the maximum power generated from the Piezoelectric Energy Harvesting (PEH) source to the load. Results: Compared to the conventional FWBR technique, the proposed CRAI technique improves ≈2X power delivered to the load. Conclusion: The proposed work presents an inductor-less interface circuit for PEH. An active inductor (gyrator) is used to induce ‘IP’ rejection at the PEH circuit resonant frequency to enhance the performance parameters. Since the proposed technique is based on active inductor, it can be easily fabricated in small Integrated Circuit (IC) packages, allowing integration with state-of-the-art constrained IoT applications. CRAI technique based on the rejection of ‘IP’ at the resonance using active inductor as first reported here. The proposed concept is non-adiabatic, but it could be used for constrained self-powered autonomous IoT applications and could be important in guiding the design of new interface circuits for PEH.

Background: At present, small current grounding systems are widely used in distribution network of China. Affected by the complex topology of the distribution network and other factors, single-phase grounding fault has become the most prone type of electrical short-circuit fault in China. Objective: Considering that the traditional fault selection and location methods are difficult to mine the effective information of fault quantity, a new method is proposed in this paper to achieve accurate fault location on the basis of ensuring timeliness. Methods: In this paper, the physical topology of the distribution network is regarded as a graph, the overhead lines and cables of the main equipment are regarded as the nodes in the graph, and the problem of fault node location is corresponding to the task of graph attention classification. Considering the average degree and homogeneity of the given network topology, an improved graph attention network is built to realize fault node location. Results: This paper verifies the effectiveness of the proposed model for fault location through simulation in PSCADA. In addition, the applicability of the proposed model in the case of changes in the distribution network structure is verified. It verifies that the proposed method achieves high positioning accuracy. Conclusion: The proposed model can locate the fault line quickly and accurately when a singlephase grounding fault occurs, which is of great significance to improve the stability of the power system and give full play to the advantages of a small current grounding system.

Background: The digital transformation strategy puts forward higher requirements for the information support system of the power system. Also, it points out the direction for the operation and maintenance of essential equipment such as large power transformers. However, the complex operating environment of power transformers poses a challenge to the digital operation and maintenance of equipment. Objectives: Complex power transformer monitoring data is characterized by a wide range of sources, complex structures, incomplete information and unfocused distribution. This paper discussed and studied the Extraction and Integration Method of Core Feature of Power Transformer under Incomplete Information to fully exploit the potential value of power data and realize data collection and condition assessment of the equipment. Methods: First, the power transformer holographic data perception technology and its analysis methods were explained from the perspective of multiple parameters; Then, based on actual cases, an information decision table based on incomplete information of power transformers based on equipment components and fault types was established to obtain the core feature of the power transformer itself; Secondly, by analyzing the distribution of the core feature index, a model for multitask data integration and fusion in a cloud-edge-end architecture was proposed, and the integration method for multi-source data transfer was elaborated. Results: Finally, the feasibility of the proposed method was verified through simulation analysis of a calculation example. Conclusion: The method described in this article has a certain reference value for evaluating complex equipment that is mainly data-driven but lacks more serious information in the power grid digital transformation process.

Background: Focusing on the stability problems brought by integrated wind power and fuel cell, the objective of this paper is to analyze small-signal stability and improvement of a hybrid renewable energy system connected with Doubly-Fed Induction Generators (DFIGs) and Solid Oxide Fuel Cells (SOFCs) energy with the Static Series Synchronous Compensator (SSSC) and power-Oscillation Damper (POD). Methods: For this purpose, a SSSC-POD controller is designed and the state-space representation of such a hybrid power system for modal analysis is developed. Then an approach of coordination and optimization of SSSC-POD parameters based on Genetic Algorithm (GA) and modal analysis is proposed to further improve the power system small-signal stability. Results: Several designed scenarios, including changing the tie-line power, POD input signal, and SOFC power output, are considered in IEEE's two-area system to test the proposed method through small-disturbance eigenvalue analysis and time-domain simulations. Conclusion: Simulation results demonstrate that the proposed approach can effectively suppress the local and inter-area oscillations and improve power system stability.

Background: The operation state evaluation and fault location of the transformer is one of the technical bottlenecks restricting the safe power grid operation. Methods: A hybrid intelligent method based on the Improved Sine Cosine Algorithm and BP neural network (ISCA-BP) is developed to improve the accuracy of transformer fault diagnosis. First, the cloud model is introduced into the Sine Cosine Algorithm (SCA) to determine the conversion parameter of each individual to balance the global search and local exploitation capabilities. After that, six popular benchmark functions are used to evaluate the effectiveness of the proposed algorithm. Finally, based on the dissolved gas analysis technology, the improved SCA algorithm is employed to find the optimal weight and threshold parameters of the BP neural network, and the transformer fault classification model is established. Results: Simulation results indicate that the improved SCA algorithm exhibits strong competitiveness. Furthermore, compared with the BP neural network optimized by the Sine Cosine Algorithm (SCA-BP) and BP neural network, the ISCA-BP method can significantly improve the diagnostic accuracy of transformer faults. Conclusion: The proposed intelligent method can provide a valuable reference idea for transformer fault classification.