Sharif University of TechnologyScientia Iranica1026-309832120250101Adaptive Kalman filter based on variational Bayesian approach for one-step randomly delayed measurements2289010.24200/sci.2022.59433.6243ENSri MannarayanaPoluriDepartment of Electrical Engineering, National Institute of Technology Durgapur, West Bengal, 713209, IndiaAritroDeyDepartment of Electrical Engineering, National Institute of Technology Durgapur, West Bengal, 713209, IndiaJournal Article20211201This article addresses the state estimation problem for dynamic systems with linear models wherein covariance matrices of the process and measurement noise are unknown and one step delay randomly occurs in the measurements. Due to network congestion, limited bandwidth during transmission of sensor data to the central processing unit the probability of measurements getting randomly delayed is high and this phenomenon is ignored for conventional adaptive Kalman filters. A new algorithm for Adaptive Kalman filter with one step randomly delayed measurements is proposed here wherein the randomly delayed measurements are modelled using Bernoulli’s distribution. The adaptation algorithm has been mathematically derived for such situations following the variational Bayesian approach and subsequently a recursive algorithm for variational Bayesian adaptive delayed Kalman filter is formulated. Monte Carlo simulation demonstrates the excellence of the proposed filter over the conventional Kalman filter for the estimation problem addressed in this work. The comparative study with the competing maximum likelihood estimation variant also reveals the superiority of the proposed filter. To exemplify the effectiveness of the proposed algorithm for real world applications validation with the real measurement data has been carried out for offline harmonics estimation which ensures satisfactory estimation results.https://scientiairanica.sharif.edu/article_22890_4bf0eaa162974aa7fb14f3ed35a9d8eb.pdfSharif University of TechnologyScientia Iranica1026-309832120250101Design and control of a dual-function device with simultaneous DVR and FCL capability2293910.24200/sci.2022.60047.6566ENAmir ArsalanAsterakiDepartment of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, Khozestan, IranMehdiSaradarzadehDepartment of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, Khozestan, IranImanPourfarDepartment of Electrical and Computer Engineering, Jundi-Shapur University of Technology, Dezful, Khozestan, IranJournal Article20220317Dynamic Voltage Restorer (DVR) is a protecting device for sensitive loads which compensates grid voltage fluctuations. Although using Fault Current Limiter (FCL) devices is a method of protecting loads and electrical networks against short circuits. In recent years, some methods have been proposed to combine these two devices to reduce the cost of converters and use the benefits of each device simultaneously. A new topology and control method to combine a DVR and an FCL is presented in this paper, which with just adding a switch to the conventional DVR, the FCL performance will be available for the network. The FCL-DVR has been developed to provide excellent dynamic performance and faster response time to network failures while maintaining appropriate reliability and a low converter cost. The performance ability of the proposed device is investigated by simulation results.https://scientiairanica.sharif.edu/article_22939_21b4a75a2d43c554c51000eb6c4dee17.pdfSharif University of TechnologyScientia Iranica1026-309832120250101Flux-weakening control of linear induction motor drives considering the primary resistance and end effect2299910.24200/sci.2022.60081.6623ENPegahHamedaniDepartment of Railway Engineering and Transportation Planning, University of Isfahan, Isfahan, IranJournal Article20220410Indirect field-oriented control (IFOC) of a linear induction motor (LIM) drive is an important challenge because of the end effect and nonlinear behavior of the LIM drive. It becomes more complex in high-speed applications and flux-weakening (FW) regions when current and voltage constraints must be satisfied. Moreover, considering the primary resistance in voltage constraint inequality makes the calculations even more complicated. <br />This work presents a new FW control algorithm for LIM drives, considering the end effect and the primary resistance. Consequently, the reference d-axis current and maximum q-axis current are modified considering the primary resistance and end effect. Accordingly, new control strategies for the partial and full FW regions are implemented in a LIM drive. Fuzzy Logic Controller (FLC) has been used to overcome the nonlinear behavior of LIM drive and achieve appropriate dynamic characteristics. Simulation results validate the effectiveness of the suggested LIM drive based on FLC in different speed regions. Moreover, Results manifest that in a LIM drive with end effect consideration, the base and the critical speeds are not constant. As the LIM speed increases, the base frequency reduces, whereas the critical frequency increases.https://scientiairanica.sharif.edu/article_22999_e55bc67a94ab66d4c4a4a4ded787c5f7.pdfSharif University of TechnologyScientia Iranica1026-309832120250101A method for sub-optimal control of the delayed fractional order linear time varying systems with computation reduction approach2301610.24200/sci.2022.60061.6575ENMehdiYousefi TabariDepartment of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, IranZahraRahmaniDepartment of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, IranAliVahidian KamyadDepartment of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, IranSeyed JalilSadati RostamiDepartment of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, IranJournal Article20220310A method for designing suboptimal control for a class of delayed fractional systems is proposed in this paper. Despite theoretical advances in fractional mathematics and computational techniques for solving fractional optimal control (FOC) problems, as well as a lack of comprehensive analytical methods, numerical methods have been developed. For this purpose, in this study, the necessary optimal conditions for the time-delay fractional optimal control (TDFOC) problem are presented first; Then an algorithm for the numerical solution to this problem is suggested. This algorithm is based on a fractional derivative approximation and linear interpolation for delayed arguments. According to this method, the TDFOC problem is transformed into a system of algebraic equations that can be solved numerically. The proposed method's efficiency is assessed by solving several numerical examples.https://scientiairanica.sharif.edu/article_23016_4d7acb1a2ce9400e1916ff301668ad57.pdfSharif University of TechnologyScientia Iranica1026-309832120250101Load forecasting using two-level heterogeneous ensemble method for smart metered distribution system2309810.24200/sci.2023.59765.6410ENSnehaRaiDepartment of Electrical Engineering, NIT Patna, Patna, Bihar, 800005, India0000-0001-6621-9468MalaDeDepartment of Electrical Engineering, NIT Patna, Patna, Bihar, 800005, IndiaJournal Article20220117A heterogeneous ensemble method for load forecasting (short-term and mid-term) are proposed here. The proposed approach comprises of a two-level hierarchy of machine learning based methods and classical methods to form the ensemble forecaster, where output of the first-stage forecasters are used as input in the second stage. Artificial Neural Network and Support Vector Regression methods are incorporated in the proposed approach as ML forecasters, whereas Holt’s exponential smoothening and multiple linear regression techniques are included as classical forecasters. The proposed two-level ensemble approach forecasts realistic smart metered data more accurately and efficiently for multiple short-term and mid-term load forecasting scenarios with improved accuracy compared to any individual single stage forecasting methods. The prediction accuracy is shown to improve manifolds for the tested practical system. The proposed model also shows improvements compared to existing aensemble-based model.https://scientiairanica.sharif.edu/article_23098_23bbb8487b4cca543f6f45caccf8846e.pdfSharif University of TechnologyScientia Iranica1026-309832120250101Optimal configuration of a wind-photovoltaic-hydrogen-gas-electric vehicles integrated energy system considering multiple uncertainties and carbon reduction2319510.24200/sci.2023.60272.6698ENGangZhuSchool of Management, University of Shanghai for Science and Technology, Shanghai 200093, ChinaYanGaoSchool of Management, University of Shanghai for Science and Technology, Shanghai 200093, ChinaHaoSunSchool of Management, University of Shanghai for Science and Technology, Shanghai 200093, ChinaJournal Article20220414Coupling renewable energy, electric vehicle and hydrogen storage is an effective way for Integrated Energy Systems (IES) to move toward a low-carbon approach. The uncertainties of wind power, Photovoltaic Panel (PV) power and load demand are considered, meanwhile, a ladder-type carbon trading mechanism is designed, and the model is transformed into a deterministic Mixed-Integer Linear Programming (MILP), while the reliability of spinning reserve power is measured by a proper confidence level. Meanwhile, the objective function is constructed based on the optimization strategy of deviation preference, and two objectives are introduced to optimize the annual comprehensive cost and annual carbon emission. The problem is transformed into a MILP and the optimization of the capacity configuration of this IES is performed. The results show that the IES has advantages in economic and environmental performance. The IES has significant advantages in Carbon Dioxide Emission Reduction (CDER); meanwhile, Electric Vehicle (EVs) show advantages in CDER and charging cost compared to those in the non-IES. Carbon dioxide emissions in IES are only one-fifth of those of conventional distribution system and the CDER effect is noticeable. Moreover, EV charging cost in the IES is relatively lower, while the CDER effect is an order of magnitude better than that of non-IES.https://scientiairanica.sharif.edu/article_23195_75c576631abba5d77285db68360fc3c3.pdfSharif University of TechnologyScientia Iranica1026-309832120250101Multi-port high-frequency AC-link and indirect matrix converters: A generalized structure2328310.24200/sci.2023.59375.6205ENHosseinHojabriDepartment of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman 76169-14111, IranJournal Article20220319Conventional multi-stage AC/DC/DC, AC/DC/AC, DC/DC/DC, and DC/DC/AC converters are two ports converters used to connect a resource or load to an AC or DC grid. To connect several loads or resources to a grid, these converters can easily be extended to a multi-port converter through a common DC-link, with simplified control and a reduced number of active switches. However, DC-link huge energy storage component increases the converter volume and cost and reduces its lifetime and reliability. On the other hand, most of the resources with these types of converters have fault ride-through problems and the DC-link voltage increases during the grid-side faults. The indirect matrix converter is a two-port high-frequency AC-link (HFAC) converter without any intermediate energy storage component, which can be used to connect just a single source or load to a grid. In this paper, a generalized extension of a two-port indirect matrix converter (and the other HFAC converters) to a multi-port converter is proposed. The modulation method, voltage and current gains, and the reactive power limitation of the proposed structure are also presented. Performances of the proposed structure and its modulation strategy are verified through simulation in MATLAB/SIMULINK environment.https://scientiairanica.sharif.edu/article_23283_c060d49a637ef1a03bfe05a10e61a7ee.pdfSharif University of TechnologyScientia Iranica1026-309832120250101Statistical analysis based load frequency control of multi-area system with nonlinearities using 2-DOF-PID controller with application of improved sine-cosine algorithm optimizer2330310.24200/sci.2023.60059.6574ENNeelesh KumarGuptaDepartment of Electrical Engineering, NIT Jamshedpur, Jamshedpur, India-831014Manoj KumarKarDepartment of Electrical Engineering, NIT Jamshedpur, Jamshedpur, India-831014Arun KumarSinghDepartment of Electrical Engineering, NIT Jamshedpur, Jamshedpur, India-831014Journal Article20220304In this article, for Load Frequency Control (LFC) in power system an improved sine-cosine algorithm is proposed with 2-DOF-PID controller. To facilitate the inspection, a multi-area test system (three area) has been developed. Additionally, several physical restrictions have been taken into account while investigating practical power system analysis. For every scenario considered for the experiment, the suggested approach has been employed as the optimizer of parameter of the controller of LFC. 2-DOF-PID controllers has the ability to quickly reject disturbances without noticeably increasing overshoot in set point tracking, have been utilised as the controller of LFC. The PIDF and FOPID controllers has been compare with 2-DOF-PID controller to evaluate the usefulness of it. The simulation results of SCA, SSA, ALO, and PSO are some of the algorithms with which of the proposed modified algorithm were compared, in three distinct scenarios: disturbance in three areas, disturbance in two areas, and the final scenario with physical restrictions. Wilcoxon Sign Rank Test (WSRT) has been use for the statistical analysis and 20 separate times was carried out in order to further prove the supremacy of the suggested strategy.https://scientiairanica.sharif.edu/article_23303_bea9d5f02575cef35d740d28325001d6.pdfSharif University of TechnologyScientia Iranica1026-309832120250101Cryptanalysis of full-round SFN block cipher a lightweight block cipher, targeting IoT systems2339010.24200/sci.2023.59581.6319ENSadeghSadeghiDepartment of Electrical Engineering, Sharif University of Technology, Tehran, IranMajidMahmoudzadeh NiknamDepartment of Mathematics, Faculty of Mathematical Sciences and Computer, Kharazmi University, Tehran, IranNasourBagheriDepartment of Electrical Engineering, Shahid Rajaee Teacher Training University, Tehran, Postal code: 16788-15811, IranMohammad RezaArefDepartment of Electrical Engineering, Sharif University of Technology, Tehran, IranJournal Article20211218SFN is a lightweight block cipher designed to be compact in hardware and efficient in software for constrained environment such as the Internet of Things (IoT) edge devices.<br />Compared to the conventional block ciphers it uses both the SP network structure and Feistel network structure to encrypt.<br />The SFN supports key lengths of 96 bits and its block length is 64 bits and includes 32 rounds. In this paper, we propose a deterministic related key distinguisher for 31 rounds of the SFN. we are able to use the proposed related key distinguisher to attack the SFN in the known-plaintext scenario with the time complexity of $2^{60.58}$ encryptions. The data and memory complexity of those attacks are negligible. In addition, we will extend it to a practical chosen-plaintext-ciphertext key recovery attack on full SFN (32 rounds) with the complexity of $2^{20}$. We also experimentally verified this attack.<br /><br />Also, in the single key mode, we present a meet in the middle attack against the full rounds block cipher for which the time complexity is $2^{80}$ the SFN calculations and the memory complexity is $2^{35.6}$ bytes. The data complexity of this attack is only two known plaintext and their corresponding ciphertext.https://scientiairanica.sharif.edu/article_23390_7e06d6641af5646b3b8f4ae9bdea5cff.pdfSharif University of TechnologyScientia Iranica1026-309832120250101Temporal analysis of functional brain connectivity for EEG-based emotion recognition2351210.24200/sci.2024.60201.6664ENEnsiehKhazaeiDepartment of Electrical Engineering, Sharif University of Technology, Tehran, IranHodaMohammadzadeDepartment of Electrical Engineering, Sharif University of Technology, Tehran, IranJournal Article20220402EEG signals in emotion recognition absorb special attention owing to their high temporal resolution and their information about brain activity. Different brain areas work together and the activity of brain changes over time. In this study, we investigate the emotion classification performance using functional connectivity features in different frequency bands and compare them with the classification performance using differential entropy feature, which has been previously used for this task. Moreover, we investigate the effect of different time periods on classification performance. Our results on SEED dataset show that as time goes on, emotions become more stable and the classification accuracy increases. Among different time periods, we achieve the highest classification accuracy using the time period of 140s-end. In this time period, the accuracy is improved by 4 to 6% compared to the entire signal. Pearson correlation coefficient, coherence and phase locking value features and SVM obtain the mean accuracy of about 88%. Using the proposed framework, functional connectivity features lead to better classification accuracy than DE features (with the mean accuracy of 84.89%). Finally, using the best time interval and SVM, we achieve better accuracy than using RNNs which need large amount of data and have high computational cost.https://scientiairanica.sharif.edu/article_23512_ee922e3f968ca928ae16b2400c426107.pdf