فصلنامه هوش محاسباتی در مهندسی برق
سال چهاردهم شماره 2 (تابستان 1402)

Despite the extensive studies that have been done regarding the restoration problems and issues of power systems, the impact of the topological extent of the power grid structure on power system restoration has not been analyzed or assessed. This objective, which is neglected in the process of planning and development of transmission systems, could make operators encounter more challenges during the restoration process and prolongation of the restoration procedures. In this study, an attempt is made to evaluate the desirability of a power system network structure according to the main requirement of the restoration process, i.e. restoration time. To address this concern, a systematic approach on the basis of a fractal-based quantitative index is introduced to measure the topological extent of a power system network as a representative of restoration time. The proposed approach combines the feeding point condition, topological extent, and support routes to deliver an index associated with the time and success probability of the power system restoration process.

Nowadays, using telecommunication systems and advanced measuring devices underlies cyberattacks on electrical grids. Bad data injection and failure to detect it on time, cause drastic damage to the network. This paper presents a new method for bad data detection (BDD) in state estimating when a cyber attacker manipulates the important measurements. Therefore, the new attack index is defined by simultaneously manipulating the network parameters and injecting incorrect data into the measured values. For this purpose, considering the masking and swamping effect, the diagnostic robust generalized potential (DRGP) algorithm detected and isolated high-leverage measurements installed in important locations from low-leverage measurements. Then, the state estimation process performs using low-leverage measurements. The Generalized Studentized Residual (GSR) algorithm detects bad data. With simultaneous manipulation of network parameters and measurement values, conventional BDD methods are unable to detect an attack. To evaluate the performance of the proposed method, they were implemented on the IEEE standard 14-bus network using MATLAB and Rstudio software. The simulation results show the ability of the proposed algorithm to detect a bad data attack.

In recent years, the development of electric vehicles has accelerated. In this manuscript, a new control method is proposed to maintain the stability of the front and rear wheel independent drive type electric vehicle (FRID EV) on the roads with a low friction coefficient. This control method specifies an optimized bound proportionally to the state of the road’s surface for the torque values produced by the front and rear electric motors to prevent the vehicle from slipping. In addition, a fuzzy logic-based braking system is proposed to improve the vehicle performance during decelerating. The vehicle is described by the model with three degrees of freedom that provides good accuracy. The tires are modeled based on the magic formula. To evaluate the effectiveness of the proposed method, simulations have been carried out in MATLAB/SIMULINK software environment. The results show that the proposed control method can well maintain the stability of the electric vehicle on dry and slippery roads, during moving straight, accelerating or decelerating, as well as turning. As a result, the vehicle is prevented from slipping and locking the wheels.

In Network-on-Chip architecture, wired structure and multi-step communication increase consumption power and latency. Combining wired media for a regular transmission and high-bandwidth wireless media for multi-step communication is a way to reduce latency and consumption of power. Wireless nodes are prone to error in on-chip wireless networks due to their complexity and relatively high usage; they are also crowded due to their sharing between several nodes, but their job is to increase efficiency. However, the presence of wireless nodes in wireless networks on the chip increases the cost and area. Therefore, finding an optimal structure for communication between cores is necessary. In this paper, a new three-dimensional architecture for a Wireless Network on Chip is presented, which has two levels; depending on the location of the error in the second level, the wireless routers in the first level are assigned to the processing elements. The demand matrix is used to optimize different traffic patterns. The performance of 3D architecture has been compared under different traffic patterns. The obtained results show that the proposed structure has a relatively good performance and increases the network's reliability.

Local hyperthermia is one of the most prevalent thermal therapies for cancerous tumors, near the skin surface or natural body orifices. Due to the requisiteness of temperature control during local hyperthermia, first, the heat conduction process during the mentioned therapy is analytically modeled via a fractional-order transfer function with time delay. Since the influence of the heat source and the patient`s physiological reaction may vary the patient body temperature and affect all of the model parameters, robust control of temperature during the treatment is necessary. Hereupon, this study suggests a novel robustness criterion to achieve the phase margin invariance despite concurrent uncertainty on different parameters of the process model. Afterward, an analytical method is presented to tune a Fractional-Order Proportional-Integral-Derivative (FO-PID) controller for desirably adjusting the values of phase margin and gaining crossover frequency, such that the proposed robustness feature is also satisfied. Finally, a numerical simulation is presented to evaluate the efficiency of the paper`s achievements, using practical parameters.

The ever-increasing of renewable distributed generation sources in distribution networks, as well as increasing network size, have faced agent-based protection schemes with a heavy communicational load. Accordingly, despite the fast and reliable nature of multi-agent systems, they have the possibility of improper performance, especially in centralized protection systems. This paper presents an intelligent self-healing method that has the ability to replace common multi-agent systems during fault conditions. Therefore, protection tasks are performed in a single control level, without dependence on higher communicational levels, to clear the fault. Decentralized operation of this structure is provided by using intelligent electronic devices and distributed communications. In this way, the proposed scheme is described with high-speed peer-to-peer communication capability using the IEC-61850 GOOSE protocol. Then, a penetration-free algorithm, without the help of a central controller, is provided by using GOOSE message capabilities, to prevent any electricity interruption due to insufficient protection settings. Finally, by planning different scenarios and simulating a practical distribution network via ETAP software, the accuracy of the proposed algorithm has been proven.

Multi-Input and Output Radar System (MIMO) is a new type of radar system that has been the subject of much research in recent years due to its many advantages. Meanwhile, the issue of target tracking in MIMO radar systems is of great importance, and providing an efficient solution for it remains an unresolved issue. In this paper, target tracking in MIMO radar systems using optimizing Kalman interactive filter is investigated. The proposed method in this research is the MIMO radar system for the simultaneous tracking of multiple targets. In the assumed system model, the interactive multiple model (IMM) based on Extended Kalman Filter (EKF) is used to understand the effective tracking of the target. Also, the optimization of the multi-objective tracking model in MIMO radar systems has been done by the proposed method using the particle swarm optimization (PSO) algorithm. This optimization algorithm estimates the fit of each studied response based on the number of energy resources and time consumed. The efficiency of the proposed method in a simulated environment has been evaluated and its performance in tracking multiple targets has been investigated in terms of different criteria. Based on the results of these experiments, the proposed method, in addition to reducing the amount of tracking error, can be effective in reducing energy consumption and reducing the sampling period. Thus, the proposed method will reduce resource consumption in the multi-objective tracking system.

This paper presents the planning of a hybrid system with wind turbines and biomass energy sources, and batteries and electric vehicles parking lot. The proposed scheme minimizes the total costs of construction and maintenance for sources and storage and the degradation cost of storage. It is subject to the operating model of sources, storage, and power electronic converters. To provide clean energy, the priority of supplying the energy demand is given to renewable sources, and then the storages cover the distance between the load profile and the generation power of the sources. Furthermore, the proposed scheme has uncertainties regarding the load, renewable power, and energy consumption of mobile storage devices. In this paper, scenario-based stochastic planning is adopted to model the mentioned parameters. The combined algorithm of Ant lion optimization and Krill Herd optimization extracts a reliable optimal solution with low dispersion in the final response. Finally, the obtained numerical results demonstrate the capability of the proposed scheme in deriving economic planning for the proposed hybrid system, in which the presence of renewable resources leads to the extraction of an environmentally-friendly hybrid system, and the energy management of mobile storage devices reduces the planning cost of the hybrid system by 1.9% compared with a case with their absence.

This paper uses the unique biometric features of fingerprints to generate random cryptographic keys. The main aspects of the security of the generated key include the privacy of the fingerprint and the randomness and complexity of the key generation algorithm. In the proposed method, first, the unique fingerprint features, which include Minutiae points, are extracted from the fingerprint image. Then, to increase the statistical properties and complexity of the algorithm, the Euclidean distance and the angle of all the points of Minutiae relative to each other are calculated and stored. In the next step, after normalizing to 8-bit numbers, these data are moved by permutation operations and combined. In the following, the proposed method is used to increase the level of security and the ability to be random from the non-linear operations of 8-bit S-boxes S0 and S1 used in the CLEFIA block cipher. Statistical analyzes performed on the generated keys show the acceptable random nature of the keys. Therefore, the proposed structure for generating a random key can be used in encrypting digital signals with large volumes of data such as image and sound.

In addition to the many advantages of Distributed Generation (DG) for the distribution networks, they change the direction and increase the level of fault current. These changes may cause the loss of protection coordination of reclosers and fuses in distribution networks. Usually, the operation time of reclosers is determined by two main settings, TDS and IP, but two other parameters (A and B), which are defined by the standards of traditional reclosers, are also influential on the operation time of reclosers. These two parameters can be modified in digital reclosers. In this article, these two characteristics are optimized with TDS and IP to restore protection coordination. For this purpose, first, the location and the size of the DGs are specified, after that to alleviate the effects of the DGs, the location and the impedance of FCLs are optimized by a multi-objective optimization function to reduce the loss, improve voltage profile, and reduce the effects of changes in the feeders’ fault current while DGs are connected to the distribution network. Then, to restore the protection coordination, and to reduce the operating time of the protection equipment, fuse, and recloser, the parameters A, B, TDS, and IP are optimized using a multi-function optimization. To validate the proposed approach, the IEEE 33-bus network in the presence of synchronous DGs and resistive SFCL has been simulated in DIgSILENT software.