The presented research introduces a control strategy for a three-phase grid-tied LCL-filtered quasi-Z-source inverter (qZSI) using a Lyapunov-function-based method and cascaded proportional-resonant (PR) controllers. The suggested control strategy ensures the overall stability of the closed-loop system and eliminates any steady-state inaccuracy in the grid current. The inverter current and capacitor voltage reference values of qZSI are created by the utilization of cascaded coupled proportional-resonant (PR) controllers. By utilizing synchronous reference frame and Lyapunov function- based control, the requirement to perform derivative operations and anticipate inductance and capacitance are avoided, resulting in achieving the goal of zero steady-state error in the grid current. The qZSI can accomplish shoot-through control by utilizing a simple boost control method. Computer simulations demonstrate that the suggested control strategy effectively achieves the desired control objectives, both in terms of steady-state and dynamic performance.
This paper examines the use of non-integer switching frequency ratios in digitally controlled DC-DC converters. In particular the execution of multiple control algorithms using a Digital Signal Processor (DSP) for this application is analyzed. The variation in delay from when the Analog to Digital Converter (ADC) samples the output voltage to when the duty cycle is updated is identified as a critical factor to be considered when implementing the digital control system. Fixing the delay to its maximum value is found to produce reasonable performance using a conventional DSP. A modification of the DSP’s interrupt control logic is proposed here that minimizes the delay and thereby yields improved performance compared with that given by a standard interrupt controller. Applying this technique to a multi-rail power supply system provides the designer with the flexibility to choose arbitrary switching frequencies for individual converters, thereby allowing optimization of the efficiency and performance of the individual converters.
The occurrence of Sub-Synchronous Resonance (SSR) phenomena can be attributed to the interaction that takes place between wind turbine generators and series-compensated transmission lines. The Doubly-Fed Induction Generator (DFIG) is widely recognized as a prevalent generator form employed in wind energy conversion systems. The present paper commences with an extensive exposition on modal analysis techniques employed in a series of compensated wind farms featuring Doubly Fed Induction Generators (DFIGs). The system model encompasses various components, including the aerodynamics of a wind turbine, an induction generator characterized by a sixth-order model, a second- order two-mass shaft system, a series compensated transmission line described by a fourth-order model, controllers for the Rotor-Side Converter (RSC) and the Grid-Side Converter (GSC) represented by an eighth-order model, and a first-order DC-link model. The technique of eigenvalue-based SSR analysis is extensively utilized in various academic and research domains. The eigenvalue technique depends on the initial conditions of state variables to yield an accurate outcome. The non-iterative approach, previously employed for the computation of initial values of the state variables, has exhibited issues with convergence, lack of accuracy, and excessive computational time. The comparative study evaluates the time-domain simulation outcomes under different wind speeds and compensation levels, along side the eigenvalue analysis conducted using both the suggested and non-iterative methods. This comparative analysis is conducted to illustrate the proposed approach efficacy and precision. The results indicate that the eigenvalue analysis conducted using the proposed technique exhibits more accuracy, as it aligns with the findings of the simulations across all of the investigated instances. The process of validation is executed with the MATLAB program. Within the context of the investigation, it has been found that increasing compensation levels while simultaneously decreasing wind speed leads to system instability. Therefore, modifying the compensation level by the current wind speed is advisable.
The objective in Data Grids is to reduce access and file (replica) transfer latencies, as well as to avoid single site congestion by the numerous requesters. To facilitate access and transfer of the data, the files of the Data Grid are distributed across the multiple sites. The effectiveness of a replica selection strategy in data grids depends on its ability to serve the requirement posed by the users' jobs. Most jobs are required to be executed at a specific execution time. To achieve the QoS perceived by the users, response time metrics should take into account a replica selection strategy. Total execution time needs to factor latencies due to network transfer rates and latencies due to search and location. Network resources affect the speed of moving the required data and searching methods can reduce scope for replica selection. This paper presents a replica selection strategy that adapts its criteria dynamically so as to best approximate application providers’ and clients’ requirements. We introduce a new selection technique (EST) that shows improved performance over the more common algorithms.
Cybersecurity awareness has a huge impact on individuals and an even bigger impact on firms, universities, and institutes to those individuals belong. Consequently, it is essential to explore and asses the factors affecting the awareness level of cybersecurity. More specifically this research study examines the impact of demographic features of individuals on cybersecurity awareness. The Studied literature’s limitations have been addressed and overcome in our research from the variability, and ambiguity aspects. A questionnaire was developed and responses were collected from 613 participants. Reliability and validity tests as well as correlations have been applied for the instruments and data employed in this study. Coefficients were calculated via multiple linear regression for the weights of each of the cybersecurity components. Data reliability test showed that Cronbach’s Alpha value of 0.707 for the used data which is acceptable for research purposes. Results analysis showed r-value for each of the questions is greater than the r table which was 0.07992. Examining the proposed hypotheses showed that there is a difference as the null hypothesis is rejected for one of the demographic features being tested namely, gender. While there is no significant difference when it comes to the other two factors, education level, and age. Using the weight for each of the components, password security, technical behavior, and social influence could provide a solid base for decision-makers to focus on and implement the available resources for gender-specific developments to raise the cybersecurity awareness level..
An accurate model for a permanent magnet syn- chronous generator (PMSG) is important for the design of a high-performance PMSG control system. The performance of such control systems is influenced by PMSG parameter variations under real operation conditions. In this paper, the electrical parameters of a PMSG (the phase resistance, the phase inductance and the rotor permanent magnet (PM) flux linkage) are identified by a particle swarm optimisation (PSO) algorithm based on experimental tests. The advantages of adopting the PSO algorithm in this research include easy implementation, a high computational efficiency and stable convergence characteristics. For PMSG parameter identification, the normalised root mean square error (NRMSE) between the measured and simulated data is calculated and minimised using PSO.
Selection of the best type and most suitable size of conductors is essential for designing and optimizing the distribution network. In this paper, an effective method has been proposed for proper selection and incorporation of conductors in the feed part of a radial electricity distribution network considering the depreciation effect of conductors. Increasing the usability of the electric energy of the power grid for the subscribers has been considered per load increment regarding the development of the country. Optimal selection and reconstruction of conductors in the power distribution radio network have been performed through a smart method for minimizing the costs related to annual losses and investment for renovation of lines by imperialist competitive algorithm (ICA) to improve the productivity of the power distribution network. Backward/forward sweep load flow method has been used to solve the load flow problem in the power distribution networks. The mentioned optimization method has been tested on DAZ feeder in Ghaleganj town as test.
In This paper presents an approach for optimal placement and sizing of fixed capacitor banks and also optimal conductor selection in radial distribution networks for the purpose of economic minimization of loss and enhancement of voltage. The objective function includes the cost of power losses, voltage profile, fixed capacitor banks and also type of conductor selection. Constraints include voltage limit, maximum permissible carrying current of conductors, size of available capacitors and type of conductors. The optimization problem is solved by the Imperialism Competitive algorithm method and the size and site capacitor banks and type of conductors is determined. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on actual power network of Kerman city, Iran and the simulation results are presented and discussed.
Current automatic writing feedback systems cannot distinguish between different discourse elements in students' writing. This is a problem because, without this ability, the guidance provided by these systems is too general for what students want to achieve on arrival. This is cause for concern because automated writing feedback systems are a great tool for combating student writing declines. According to the National Assessment of Educational Progress, less than 30 percent of high school graduates are gifted writers. If we can improve the automatic writing feedback system, we can improve the quality of student writing and stop the decline of skilled writers among students. Solutions to this problem have been proposed, the most popular being the fine-tuning of bidirectional encoder representations from Transformers models that recognize various utterance elements in student written assignments. However, these methods have their drawbacks. For example, these methods do not compare the strengths and weaknesses of different models, and these solutions encourage training models over sequences (sentences) rather than entire articles. In this article, I'm redesigning the Persuasive Essays for Rating, Selecting, and Understanding Argumentative and Discourse Elements corpus so that models can be trained for the entire article, and I've included Transformers, the Long Document Transformer's bidirectional encoder representation, and the Generative Improving a pre trained Transformer 2 model for utterance classification in the context of a named entity recognition token classification problem. Overall, the bi-directional encoder representation of the Transformers model railway using my sequence-merging preprocessing method outperforms the standard model by 17% and 41% in overall accuracy. I also found that the Long Document Transformer model performed the best in utterance classification with an overall f-1 score of 54%. However, the increase in validation loss from 0.54 to 0.79 indicates that the model is overfitting. Some improvements can still be made due to model overfittings, such as B. Implementation of early stopping techniques and further examples of rare utterance elements during training.
Distributed Generation (DG) can help in reducing the cost of electricity to the costumer, relieve network congestion and provide environmentally friendly energy close to load centers. Its capacity is also scalable and it provides voltage support at distribution level. Hence, DG placement and penetration level is an important problem for both the utility and DG owner. The Optimal Power Flow (OPF) has been widely used for both the operation and planning of a power system. The OPF is also suited for deregulated environment. Four different objective functions are considered in this study: (1) Improvement voltage profile (2) minimization of active power loss (3) maximum capacity of conductors (4) maximization of reliability level. The site and size of DG units are assumed as design variables. The results are discussed and compared with those of traditional distribution planning and also with Imperialist competitive algorithm (ICA). Key words: Distributed generation, distribution network planning, multi-objective optimization, and Imperialist competitive algorithm.
Technology and digital communications have advanced so that digital photos, videos, or text may be easily manipulated by those not authorized to do so. In addition, the availability of specialized picture editing programs like Photoshop has simplified the process of altering photographs. At first glance, there may seem to be no problem, especially when an image editing method is necessary to delete or add a certain scene that increases the picture's beauty. But what about personal images or images with copyright? Attempts are constantly made to spoof these images using different approaches. Therefore, measures to reduce the likelihood of counterfeiting in digital and printed forms of media are required. The proposed approach aims to detect a counterfeit in images using a unique generator that conceals the data represented by the embedded watermark utilizing modern visual cryptography and hash algorithms. Image extractions may easily be analyzed for signs of forgery. As a result, our approach will detect and validate phony documents and images.
Development of distribution systems result in higher system losses and poor voltage regulation. Consequently, an efficient and effective distribution system has become more urgent and important. Hence proper selection of conductors in the distribution system is important as it determines the current density and the resistance of the line. This paper examines the use of different evolutionary algorithms, genetic algorithm (GA), to optimal branch conductor selection in planning radial distribution systems with the objective to minimize the overall cost of annual energy losses and depreciation on the cost of conductors and reliability in order to improve productivity. Furthermore, The Backward-Forward sweep iterative method was adopted to solve the radial load flow analysis. Simulations are carried out on 69-bus radial distribution network using GA approach in order to show the accuracy as well as the efficiency of the proposed solution technique.
The growth in energy consumption and the lack of access to the electricity network in remote areas, rising fossil fuel prices, the importance of using renewable energy in these areas is increasing. The integration of these resources to provide local loads has introduced a concept called microgrid. Optimal utilization of renewable energy systems is one of their most important issues. Due to the high price of equipment such as wind turbine, solar panels and batteries, capacity sizing of the equipment is vital. In this paper, presents an algorithm based on techno-economic for assessment optimum design of a renewable energy system including photovoltaic system, batteries and wind turbine is presented.