فصلنامه روشهای هوشمند در صنعت برق
پیاپی 59 (پاییز 1403)

In this paper, a bi-level optimization model is proposed for the coordinated management of integrated transmission and distribution networks. The problem of the security-constrained unit commitment as an upper-level problem to reduce operating costs, startup/shutdown costs, and no-load along with load shedding as a mixed integer linear programming model and the problem of optimal operation in independent distribution networks by considering renewable and non-renewable resources along with charging stations for electric vehicles as a lower-level problem to reduce the costs of purchasing power from the upstream network and reduce the costs of power outages. The resources and charging power of electric vehicle charging stations are considered a linear model. To solve the bi-level problem, the proposed lower-level model is modeled as Karush-Kahn-Tucker optimality conditions. Several different networks have been considered for validating the model and the proposed method, and the results obtained from the simulation prove the efficiency of the model and the proposed method in considering the coordinated operation of intelligent transmission and distribution networks. To show the superiority of the proposed method over other algorithms for solving multilevel models, the proposed method has been compared with decomposition algorithms, and the results show the superiority of the proposed method in terms of execution time and faster convergence.

The quantum-dot cellular automata (QCA) technology is a computational technology used to build nano-scale circuits. When the dimensions of the components decrease, the sensitivity of the circuit increases and the quantum circuits become more vulnerable to the occurrence of defects and radiation in the environment. The two major gates in this technology are inverter and majority gates, and most circuits are built based on these two gates. This paper aimed to design a seven-input majority gate in quantum-dot cellular automata by imposing low overhead on the circuit. Using a majority gate with more inputs reduces cell count, latency, and complexity in the QCA circuit. However, perhaps the need to use the seven-input gate is not yet felt we then design and implement a number of logic circuits. A new 7-input majority gate is designed in this paper, with 19 cells. The proposed structure is single-layer with an occupied area of 24564 nm2 that produces the correct output in one clock phase, then a four-input AND gate, a four-input OR gate, a two-input XOR gate, a two-input XNOR, a three-input XOR gate and a full adder are implemented using the designed seven-input gate. Including all multi-bit full adders, using the proposed seven-input gate. The proposed full adder is designed by the seven-input majority gate proposed and a fault-tolerant three-input majority gate. Therefore, it can be said that the designed full adder is somewhat tolerable, that means, it is somewhat tolerable against the fault that occur in this technology. QCAPro software is used to analyze the energy consumption of the recommended structure. Then, the circuit performance is evaluated using QCADesigner 2.0.3 simulator software for quantum-dot cellular automata.

Virtual clothing try-on can be a great option for the online clothing industry. In this paper, we propose a method to map the 3D model of selected clothes on the customer's 3D model. For this purpose, the point clouds of the customer and mannequin are captured by the Kinect camera. These models are segmented into corresponding parts using surface descriptors to ease the matching. Then, individual parts of the mannequin are mapped on the corresponding parts of the customer. Finally, the color information from the clothes on the mannequin is transformed to the customer's body point cloud. The proposed method has two main advantages over the existing methods. First, no need for an expert to design 3D models in graphic software. Second, any style and texture of clothes can be chosen by the customer. The results of the experiments show the ability of the proposed method compared to existing methods.

One of the intelligent transportation systems' goals is to improve safety and increase the quality of service on road journeys. Transmitting the message in critical situations with minimal delay and on time is essential for ensuring the health and safety of citizens on road trips. Frequent topological changes pose significant challenges to the operation of safety programs and reduce the probability of sending critical messages in real-time. This article proposes the reliable relay node selection to real-time messaging (RRRM) routing algorithm to increase the reliability of sending real-time messages in vehicular networks. To expedite the transmission of information, by introducing three indicators for selecting intermediate vehicles entitled "Record of vehicle displacement", "Similarity of vehicle velocity with the velocity average of neighbor vehicles", and "Amount of trusty adjacent vehicles", the route vehicles are scored. The worthiest vehicles are selected as members of the route. RRRM measures the temporal conformity of the vehicles' previous presence in the current route and the stability of their connection with neighboring vehicles. It avoids route failure, increased delays, and failure to send critical messages to the destination by preventing the selection of unreliable vehicles as relays. Extensive simulations with multiple scenarios in the NS-3 and SUMO demonstrate the superiority of the RRRM in reducing route-failure, mean latency, and control overload, as well as increasing packet delivery rates in urban and highway environments.

One method for determining motor commands to control hand prostheses is to use surface electr omy ogr am (sEMG) signal patterns. Due to the random and non-stationary nature of the signal, the idea of using signal information in small time intervals was investigated. In this study, with the aim of more accurate and faster detection of hand movements, two signal decomposition methods, namely discrete wavelet transform (DWT) and empirical mode decomposition (EMD) were evaluated. The sEMG sign als of the Ninapro-DB1 dataset, which were extracted from 27 healthy subjects while performing hand and finger movements, were used to design the system. Simple time domain features with fast calculation capability were extracted for each subband of the decomposed signals. Also, support vector machine (SVM) using different kernel functions was applied as a classifier. The results show that the use of DWT and EMD methods with the ability to access the information of time and frequency sub-intervals of the signals, provides better results in identifying hand movements compared to previous studies. With the EMD method and eight intrinsic mode functions (IMF), the highest recognition accuracy of 83.3% was obtained for six movements. Also, the DWT with the Bior5.5 mother wavelet and five levels of decomposition, achieved 80% recognition accuracy for ten movements and with the Coif2 mother wavelet and six levels of decomposition, the accuracy was 83.33% for eight movements. The results show the better performance of the DWT decomposition method compared to EMD for the design of the hand movement recognition system using sEMG signal patterns.

In this paper, a new interleaved step-up converter with leakage inductances energy recovery is presented. The auxiliary circuit in the proposed converter not only provides zero voltage switching conditions for all switches, but also the leakage inductance energy of the coupled inductors is recovered and also helps to increase the voltage gain and reduce the voltage stress of the switches. Therefore, the converter does not need passive clamp circuits to control voltage spikes on the switches. Also, all switches do not have capacitive turn-on losses in the switches. On the other hand, the output diodes operate under zero current switching and do not have the reverse recovery problem. The converter is also controlled by pulse width modulation, and since the auxiliary switches are turned on in complimentary with the main switches, they do not have a complex control circuit. The proposed converter has been completely analyzed and to confirm its correctness, a 100W sample of the converter has been made and its practical results have been presented.

This paper presents the optimal planning of renewable hybrid systems including wind turbines and bio-waste energy units according to hydrogen and thermal storages considering feeding of electrical and thermal energies. Bio-waste unit is based on the operation of the combined power and heat system, which produces electrical and thermal energy at the same time. Hydrogen storage is hybrid of an electrolyze, hydrogen tank, and fuel cell. The proposed scheme minimizes the total annual investment and maintenance costs. It is subject to the operation model of the mentioned elements. In the operation model of sources and storage, renewable sources supply loads of energy, then storage uses to cover the gap between the load and renewable power profiles. This paper uses the hybrid solver of the Gray wolf optimizer and the sine-cosine algorithm to obtain a reliable optimal solution with a low standard deviation in the final response. Finally, based on numerical results according to Espoo in Finland data, the proposed scheme's capability is confirmed in the Economic extraction of a 100% renewable island hybrid system suitable for simultaneous supply of electrical and thermal energy.

Utilizing the structure of multi-agent systems is one of the methods proposed today to improve the performance of network protection systems. Given that the presence of distributed generation resources as well as network restructuring has always been a concern for network managers, so it is expected that with the introduction of smart equipment and capabilities that provide network managers, better performance and maintenance They help. Intelligent devices are able to exchange information by communicating on a telecommunications platform. The purpose of this paper is to coordinate the protection relays in the presence of distributed generation sources by removing the connection between the relay agents and the information collected from the entire network by the central controller. The proposed method, in addition to improving the speed of the traditional multi agent system protection system, increases the security of the protection system and eliminates the need for information from one agent of one section to the agents of another sections.

Since it might delay making significant expenditures in substations and generation, increasing the efficiency of power systems is an important priority. By altering the status of switches, the distribution feeder reconfiguration (DFR) can reduce system losses in this regard. Power loss and voltage deviation of buses are frequently taken into account as objective functions while solving the distribution feeder reconfiguration problem, however reliability indices have received less consideration. The proposed reliability index, coupled with power loss and switching number in the presence of distributed generators, are used in this study to address DFR as a multi-objective problem. The DFR problem is complex inherently, considering impacts of distributed generators makes the problem more be complex than before. For this purpose, an evolutionary method based on the combination of particle swarm optimization and modified shuffled frog leaping has been used to solve the nonlinear optimization problem in this study. Two 33-bus and 70-bus systems are evaluated to gauge the effectiveness of the suggested hybrid algorithm.

In recent few decades, due to various reasons, including energy crisis and environmental problems, renewable energy sources such as wind energy, solar systems and fuel cells have received much attention. Solar or photovoltaic systems are one of the most widely used renewable energy sources that have a low output voltage. For this reason, research on dc-dc converters has increased in recent years. In this paper, a non-isolated high voltage gain converter with three input-output ports is proposed. This converter provides two separate paths for power flow from each input source to the output load. In order to reduce the number of converter components, some components play multiple roles. Therefore, the energy storage device (battery) will charge with the same components used to transfer the power to the load. In this converter, to increase the voltage gain, the coupled inductor technique is used. Moreover, to reduce the leakage inductance as well as achieving the soft switching condition, two active clamps are used. Since the voltage across the switches is limited, the switches can be used with low voltage stress and thus low conduction losses. In this converter, the ripple of the input current will reduce by adding an inductor at its input. This has a significant impact on the performance and the lifespan of the solar cells. The various operational modes of the converter are discussed and the designing considerations are presented. A prototype of the proposed converter is simulated to supply a 130 W, 330 V load with a switching frequency of 50 kHz, in OrCAD software. Finally, a laboratory sample is implemented and the theoretical analysis are validated by the practical results.