نشریه فناوری های نوین مهندسی برق در سیستم انرژی سبز
سال چهارم شماره 4 (پیاپی 16، زمستان 1404)

This paper proposes optimal energy management for multiple microgrids (MMG) connected to a distribution network (DN), in which various objective functions including network cost, pollutant reduction and losses, and distribution network resilience are considered. Also, the effect of the placement of distributed generation sources and the distribution network's reconfiguration in the optimization process to reduce losses, increasing reliability and resilience are considered. Uncertainties are formulated using Information Gap Decision Theory (IGDT). The decision variables, including the location of resources and microgrids, installation capacity, power factor, and uncertainty radius, have been optimally determined using the Modified Harris Hawk Optimization algorithm (MHHO) and the CPLEX solver. In the MHHO algorithm, the rabbit energy parameter (E) changes dynamically with the behavior and value of the objective function. Finally, the proposed method on the IEEE 33-bus Radial Distribution System in the first stage in a 24-hour time horizon including three micro-grids with different renewable energy sources to determine the structure of the network due to the buses connecting micro-grids and scattered sources by the placement algorithm and in the next stage in time Different resilience indicators are investigated due to the disconnection of the distribution network with the upstream network. The simulation results show the MHHO algorithm's optimal performance in placing microgrids, distributed generation sources, and network reconfiguration to improve the optimal energy management and resilience index.

In this paper, a step-up converter with very high voltage gain and low input current ripple for photovoltaic systems is presented. One of the main features of the converter is not using coupled- inductors and increasing gain by using switched-capacitors, so the volume and weight of the converter has been greatly reduced. The auxiliary circuit has provided zero voltage switching conditions for the main and auxiliary switches, and due to the low number of elements, the efficiency of the converter has been significantly improved. The input current ripple of the converter is very low, which makes it easy to track the maximum power point from the photovoltaic cells. Due to the increase in gain and decrease in voltage stress on the switches, it is possible to use switches with lower RDS(on), and conduction losses are subsequently reduced. Also, due to the complementary function of the switches, the design of the control circuit is simple and the control of the converter remains as PWM. The converter is simulated in PSPICE software with a power of 110 W and an output of 330 V, and finally a prototype is made of it, and the laboratory results confirm the simulation results.

This paper introduces a new double-switch quadratic DC-DC converter with ultra-high voltage gain ratio, low current stress, and low input current ripple for renewable energy applications. This suggested topology uses a coupled-inductor and voltage multiplier cells to achieve the ultra-high voltage conversion ratio. The main benefits of the suggested structure are its ultra-high voltage conversion ratio, low voltage and current stresses, common ground between the input and output sides, and continuous input current with low ripple. Also, in the proposed converter, the current sharing between the magnetic components including the coupled-inductor and input inductor leads to a reduction of their passing current values, which alleviates the overall power losses of the magnetic components and power switches. Furthermore, the voltage stresses on the active switches of the proposed converter are restricted using the regenerative passive clamp circuits. The operating principle, the steady-state analysis, the comparison study, the efficiency estimation as well as design considerations of the introduced circuit are provided in detail. Finally, to justify the performance of the presented converter, a sample prototype (200 W, 25 V- 400 V) is implemented. Regarding the experimental results, the proposed topology can provide a high DC output voltage of 400V under the efficiency of about 96.2%. Moreover, the voltage stress across the power switch of the converter is limited to about 15% of the output DC voltage.

This article presents a novel approach to monitoring car batteries, based on the recording of battery terminal voltage signals during the vehicle's startup. The objective is to introduce a new capability for modifying warranty service terms and enhancing energy efficiency. In contrast to the existing approach, the proposed method would provide warranty services based on the number of times the battery is used for starting the car, rather than on the battery's usage time. To facilitate the implementation of the methodology outlined in this article, a microcontroller circuit has been designed and constructed. The microcontroller circuit employs an ATmega328P microcontroller and a micro SD card for monitoring the battery voltage signal and as external memory, respectively. Furthermore, a resistive voltage divider has been utilized to calibrate the range of battery terminal voltage fluctuations to a level that the microcontroller can process. The circuit was designed, assembled, and installed on several different passenger cars, and tested under real-world operating conditions. The results of this examination demonstrate that the designed and built system accurately counts the number of times the car is started and records the desired characteristics of the battery voltage signal during startup in the allocated memory. The successful performance of the prototype under various conditions confirms the high efficiency and reliability of the proposed method presented in this article.

While the market for new electric vehicles is growing significantly, some environmental issues, such as carbon emissions, are often attributed to the production of electric cars. In this research, a supply chain including a manufacturer that sells electric and gasoline vehicles through a retailer was investigated. A game theory approach has been used for modeling and problem solving. The assumption was made that the government, as a leader or pioneer, implements various policies based on the concept of sustainability. Consequently, the manufacturer and retailer seek to maximize their profits in the Stackelberg competition based on these policies. As a result of this research, managerial insights for real-world application were obtained. For instance, thresholds for coefficients and parameters, such as the conversion rate of environmental value to financial value, were identified. These show that if green investment in production lines depends on product demand, the market (or consumer) price and the factory price of electric cars will be higher compared to a scenario where the importance of green investment for the government is independent of demand. However, in the first scenario explained, the government provides more support for electric cars. To provide practical managerial insights in the real world, this research focused on parametric analyses.

One of the crucial methods to achieve guaranteed secure communication is the implementation of Quantum Key Distribution (QKD). In fact, QKD, as an interdisciplinary security technology, utilizes the principles of quantum mechanics to share a one-time-pad encryption key. From an architectural perspective, QKD systems are complex and costly physical systems composed of hardware components (including optical, laser, electro-optical, electronic, etc.) and software elements. The design and analysis of these systems require skills and expertise in various fields such as quantum optics, information theory, electrical engineering (electronics and telecommunications), and computer science. One of the fundamental needs related to the practical implementation of a QKD system is using a simulation platform. More precisely, conducting simulations before practical implementation plays a significant role in analyzing and identifying model bottlenecks, mitigating risks, increasing speed, and reducing setup costs. Additionally, by employing simulations, the selection of optimal subsystems is also facilitated. This article presents the requirements and considerations for a mathematical model and a suitable simulation platform for QKD systems. A comprehensive review of various computer software, programming languages, packages, and toolboxes for simulating QKD systems is conducted. The most important virtual labs and quantum games suitable for the education and design of QKD systems are discussed. The advantages and limitations of each laboratory are stated and compared with each other.