Power, Control, and Data Processing Systems

Abstract In recent years, the technology of plasma processing and thin film deposition using electron cyclotron resonance plasma (ECR) sources has been developed and widely utilized in plasma processing at low pressures due to its higher ionization rate compared to DC and RF plasma sources, as well as its lower sheath potential. One of the challenges of ECR plasma processing systems is the requirement for expensive magnetic field generation systems. This issue can be addressed by using permanent magnets instead of magnetic coils for generating magnetic fields. In this article, magnetic field profile of four NdFeB grade 42 permanent block magnets have been computed using Magnetic Field No Current (MFNC) module of COMSOL software and the optimal arrangement of magnets, for which resonant surfaces are placed inside the discharge chamber, has been determined. Then, microwave generated discharge in the presence of permanent magnets have been computed using Plasma and Electromagnetic Wave (EMW) modules. Additionally, we calculated characteristics of the discharge such as plasma density and microwave power absorption.

Abstract Home energy management systems (HEMS) play an important role in optimizing energy consumption. These systems manage the electricity consumption of household appliances using demand response programs based on real-time prices. The main goal of these systems is to reduce electricity costs and increase energy efficiency. In this paper, a price-base demand response approach is proposed for a smart home with different types of home appliances, including electric storage and thermal storage systems. In the proposed method, various appliances are considered in the smart home modeled by the energy hub system. An objective function is developed for daily management simultaneously addressing electricity costs to provide comprehensive management for smart homes. The proposed model examines how the smart home energy system responds under various conditions. Additionally, stochastic optimization accounts for the probabilistic nature of demands, photovoltaic (PV), and wind energy. The simulation results indicate that the consumer's payment cost is 79 cents and the emissions cost is 7 cents. The numerical results demonstrate the effectiveness of this approach.

Abstract The electric spring is used as a demand side management device in the smart grid. Electric springs can be effective in applications such as voltage and power regulation, three-phase load balancing, harmonics compensation, and improve voltage stability by utilizing inverters and mounting on the consumer side. On the other hand, the increasing expansion of renewable energies, the emergence of micro-grids, and electric vehicles are exacerbating power quality issues such as undervoltage, overvoltage, unbalanced loads, and harmonics in the power distribution grid. Therefore, electric springs can provide appropriate voltage quality for critical loads (E.g., building security systems, computers, and digital systems) by connecting series to non-critical loads (E.g., electric water heater, washing machine, and air conditioner) and using different control methods. In this paper, the effect of changes in the magnitude and angle of each line impedance, noncritical load, and critical load on the ability of voltage compensating of electric spring is investigated. For this purpose, two operating modes of overvoltage and undervoltage have been considered to obtain the compensation limits of electric spring. Finally, in this paper, an allowable range for the magnitude and angle of each impedance is proposed, in which the electric spring can compensate for voltage fluctuations without instability.

Abstract In recent years, information security has become a significant issue in the energy sector. And the inability to control information can cause irreparable damage to the network. Therefore, we need measuring devices for better monitoring and control of the network, but due to financial limitations, it is not possible to install these devices in all nodes. In the state estimation process, the placement of measurement devices at optimal locations is of great importance. Therefore, by determining the best possible combination of measurement devices, including their type, location, and quantity, desirable results can be achieved. Therefore, this research presents the optimal placement of measuring devices with the aim of reducing the state estimation error. Also, the reliability of the measuring equipment and related costs are computed and optimized during the optimization procedure. The results of this research have been analyzed in two systems of 33 and 69 bus. The simulation results are compared with the conventional methods of the past and the results show the better performance of this method than the previous methods.

Abstract After the occurrence of blackouts the most important subject is that how fast the electric service is restored. Power system restoration is an immensely complex issue and there should be a plan to be executed within the shortest time period. This plan has three main stages of black start, network reconfiguration and load restoration. In the black start stage, operators and experts may face with several problems; for instance, the unsuccessful connection of the long high voltage transmission line connected to the electrical source. In this situation, the generator may be tripped because of the unsuitable setting of its line charging mode or high absorbed reactive power. In order to solve this problem, the line charging process is defined as a nonlinear programming problem, and it is optimized by using MATLAB software in this paper. Therefore, the line charging mode of a hydro power plant is defined as an optimization problem. A nonlinear programming problem with considering the effect of transmission line parameters and installed shunt reactors in sending and receiving end buses is formulated. An iterative procedure is applied for solving the proposed problem. The optimized process is performed on a small part of a large grid which includes a 250 MW hydroelectric unit and a 400 KV transmission system. Simulations and field test results show the effectiveness of the optimal planning.

Abstract Optical character recognition (OCR), also referred to as text recognition, extracts text from scanned documents and camera images. OCR has numerous applications in reading forms and cheques, converting archived documents to digital files, and reading books and papers. An accurate OCR system speeds up these processes by eliminating time-consuming manual tasks. Despite advancements, OCR remains challenging for languages like Farsi due to their complex structures and lack of diverse datasets for evaluation. IDPL-PFOD, a new synthetic Farsi dataset, addresses this gap by including various backgrounds, fonts, distortions, and blurs. This paper evaluates Tesseract and EasyOCR on IDPL-PFOD to highlight their limitations. Tesseract and EasyOCR achieve 84.41% and 73.28% overall accuracy, respectively. Tesseract outperforms EasyOCR in most cases but drops to 67.17% on textured backgrounds, while EasyOCR achieves 75.8%. Tesseract reaches its peak accuracy (92.45%) on plain backgrounds and shows robustness to Gaussian blur and slope distortion, with minimal accuracy drops. In contrast, EasyOCR performs poorly on salt-and-pepper noise (4.79%), and moderately on sinewave distortion and Gaussian blur (61.45% and 63.73%). These findings emphasize the need for training OCR engines on more diverse datasets to improve their performance under real-world conditions.