Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) - Volume 16, Issue 1, 2023

The Permanent magnet synchronous motor (PMSM) drive has emerged as one of the most preferred motor drives for industrial applications. Its distinguished advantages include high torque density, high efficiency, and vast speed range operation. This paper presents, first, details of PMSM drives and their components. Second, explains the modelling of PMSM. Third, discusses the needs of position sensors, their applications, and their performance with the required accuracy. They are finally concerned about extensive industrial applications and future sensorless and sensorbased PMSM drives research trends. Conclusion: This paper reviews permanent magnet synchronous motor types and permanent magnet materials used due to their advantage and disadvantage and the classification of PM rotor type. This paper briefly discusses the position sensor, its types, and application based on requirements. Based on comparative analysis of permanent magnet materials, briefly discussed sensors and classification of permanent magnet motor, recommendations are given on their practical application.

Introduction: Rural electrification in India is planned with high-capacity distribution transformers which supply the isolated location loads of various categories like agricultural, household, small business, etc. This distribution system planning with non-optimal distribution transformers leads to poor voltage profiles and high power losses in the distribution network. This paper presents that a High-Voltage Distribution System (HVDS) is more suitable than a Low- Voltage Distribution System (LVDS). Methods: A model is developed to evaluate the technical losses, voltage profiles, and optimal payback period of the investments for the planned HVDS network. The replacement of LVDS with HVDS is achieved by replacing high-capacity distribution transformers with small-capacity at optimal locations. Results: The results of this study are validated on the real 11kV agricultural feeder of the Narshinghpur District of Madhya Pradesh, India. Conclusion: The results demonstrate improvement in voltage profiles, low power losses, and optimal payback period for the proposed problem. The obtained results proved that the replacement of LVDS with HVDS would be more beneficial for rural electric power distribution system planning.

Background: With the access to large-scale distributed energy, the voltage off-limit problem of the distribution network has become more and more serious, and the traditional centralized voltage control method has been difficult to meet the demand of distribution network control and market development. Methods: In this paper, a voltage regulation strategy based on decentralized wind power clustering is proposed. Considering the active and reactive power regulation ability of decentralized wind power, based on the cluster division of distributed energy, the goal is to minimize power regulation and voltage fluctuation within the cluster. Combining the K-means clustering algorithm and optimized PSO algorithm for voltage regulation within the cluster ensures that the voltagecrossing problem is solved. After the voltage regulation of all clusters, the auxiliary service transaction of voltage regulation is implemented to complete the voltage regulation of the whole network. Results: Taking ieee33 bus system as an example, the MATLAB simulation shows that the decentralized wind power access triggered voltage overrun. Using the proposed cluster division method to cluster the model, the clustered voltage regulation of the nodes with voltage overrun or reaching the limit resulted in greater voltage down-regulation than the overall voltage regulation. Conclusion: The proposed voltage regulation strategy has better advantages. It is verified that the proposed voltage regulation strategy not only solves the voltage overrun problem, but also reduces voltage fluctuations and the amount of power regulation used for voltage regulation, increasing the utilization of distributed energy with better superiority.

Background: Image denoising methods based on partial differential equations have attracted much attention due to their "infinite" local adaptation capabilities, high flexibility, and strong mathematical theoretical support. Methods: This paper proposes a mixed higher order partial differential equation denoising model for the step effect caused by the second-order denoising model and the edge blur caused by the fourth-order denoising model. The model combines the second-order and fourth-order terms based on the relationship between the variational energy minimization and the partial differential equations. The fourth-order term is used to remove noise in the uniform area of the image to avoid the step effect, and the second-order term is used at the edge to avoid boundary blur. Results: Theoretical analysis and numerical experiment results show that the proposed model has weak solutions and can effectively avoid the step effect and maintain the edge. Conclusion: The image denoising results of the model are better than those of other improved denoising models in subjective effect, and objective evaluation indicators, such as SNR, PSNR, and MSSIM.

Background: With the continuous penetration of renewable energy in modern power systems, the problem of excessive frequency deviation of power systems, which is caused by the integration of wind power into electricity grids, needs to be solved urgently. Objective: Make up for frequency fluctuations when AC systems fail, improve the frequency characteristics of main system networks, and reasonably distribute unbalanced power. Methods: According to the principle of active power distribution, a frequency division coordinated control strategy that uses low-pass filter control to divide power fluctuations into high-frequency fluctuations and low-frequency fluctuations is proposed. High-frequency fluctuations are attached to the wind farm side, and low-frequency fluctuations are attached to the DC system to realize frequency division control. Results: The simulation results showed that the coordination of the frequency division control of the wind farm and flexible DC system could effectively reduce the main grid’s frequency fluctuations, which are caused by the AC system failure, and improve the stable operation ability of the AC and DC systems. Conclusion: The frequency division control can overcome the unbalanced power distribution caused by traditional droop control, reduce the frequency deviation of the AC system, realize frequency autonomy, and enhance system robustness.

Background: Reliability analysis of logic circuits has been widely investigated due to increasing fault occurrence in modern integrated circuits. Simulation-based and analytical methods are developed to estimate the reliability of logic circuits. Methods: In this paper, a signal probability-based method is presented to estimate the reliability of logic circuits. In the proposed approach, four signal probabilities (correct 0, correct 1, incorrect 0, and incorrect 1) are derived (for every node of the circuit) using a probabilistic transfer matrix (PTM), and the correlation coefficients (CCs) are deployed to resolve the reconvergent fanouts issues. The CCs are defined in a fanout cone and are propagated through the logic gates to the related reconvergent nodes. The Bayesian network concept is applied to achieve more accuracy in the propagation of CCs through the logic gates. Results: The accuracy and scalability of the proposed method are proved by various simulations on benchmark circuits (ISCAS 85, LGSynth91, and ITC99). The proposed method efficiently solves the reconvergent fanout problem. Moreover, the proposed method outperforms the previous methods regarding accuracy and scalability. Conclusion: Simulation results on ISCAS 85, LGSynth91, and ITC99 benchmark circuits show less than 3% average error compared with the accurate simulation-based fault injection method.

Background: Accurate identification and positioning of sugarcane buds is not only the prerequisite for the automatic cutting of sugarcane buds, but also the premise of intelligent directional planting of sugarcane. Objective: In this study, a feature extraction and recognition method for sugarcane buds was proposed based on the S component in HSV model to identify the position of sugarcane bud center in the sugarcane seed image. Methods: According to the observation and analysis of 3D image of the S component in a single sugarcane bud segment after median filtering, the S component value of the stem node area containing the sugarcane bud was concentrated, and there were continuous depressions on the edge of the sugarcane bud. A rectangular template with a width of 350 pixels and step length of 35 pixels was created to search for the position with the maximum average component value, so as to indirectly determine the position of the stem node. The 3D geometric space of the S-component was analyzed, and the characteristics of the edge of sugarcane bud in the longitudinal section curve were extracted as the troughs. Finally, the characteristic parameters of the sugarcane bud were used to determine the size and position of the ellipse that approximated the shape of the sugarcane bud, indirectly locate the sugarcane bud, and effectively retain the characteristic information of the sugarcane bud. Results: The test results showed that the success rate of sugarcane bud identification was 90%, and it took 1.58 s to identify an image on average. Conclusion: The method can effectively reduce the deviation of the location of sugarcane bud center, prevent the sugarcane bud damage due to the wrong location of the sugarcane bud and the low germination rate caused by the sugarcane bud facing downward during the planting process, and provide a research foundation for the intelligent and precise planting of sugarcane.