Semnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07865220250901Coordinated Fuzzy Control of SSSC and SMES for Frequency Control in a DFIG Integrated Power System191018210.22075/mseee.2025.34911.1182ENAhmadSasaniFaculty of Electrical and Computer Engineering, Semnan University, Semnan, IranMostafaSedighizadehFaculty of Electrical and Computer Engineering, Shahid Beheshti, Tehran, Iran.RezaKeypourFaculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran.Journal Article20241013 <span class="fontstyle0">Nowadays, one of the features of developed countries is that they benefit from a highly reliable and stable electricity grid. In recent decades, the growth of power electronics technology has assisted this development. Flexible alternating current system (FACTS) devices are power electronics devices in the AC transmission grid. This paper evaluates the static synchronous series compensator (SSSC) in series with the transmission line and superconducting magnetic energy storage (SMES) placed at the end of the line to reduce grid frequency disturbances. The challenge is addressed by finding the optimal values for SSSC and SMES in the transmission grid using fuzzy logic, which is based on human decisions. Moreover, this paper investigates the effect of the presence and absence of variable-speed doubly-fed induction generator (DFIG)-type wind turbines. By increasing the penetration of variable-speed wind turbines in the grid, the equivalent system inertial is reduced, the ability to adjust the grid frequency is weakened, and the possibility of instability and even grid collapse after the frequency drop is increased. To this end, upon detection of frequency deviation in the grid, additional power is applied to the power system as a function of the grid frequency deviation by allocating a wind turbine with a control loop. In the absence of DFIG, the effect of only the optimized SMES-SSSC is investigated. This simulation is conducted using MATLAB/Simulink, and it is indicated that the error signal in determining the SMES and SSSC parameters is significantly reduced compared to previous studies, thanks to employing the fuzzy algorithm.</span> https://mseee.semnan.ac.ir/article_10182_fc7908e2f7f608d88ea390babd8143bd.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07865220250924UHF Detection of Partial Discharge in High-Voltage Air Insulated Switchgear Using Improved Vivaldi Antenna11171010510.22075/mseee.2025.35958.1189ENMohammad-RezaNickpayTehran Regional Electric Company, Tehran, Iran.MohammadDanaieFaculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran.RoohallahAmirabadiTehran Regional Electric Company, Tehran, Iran.VahidYariTehran Regional Electric Company, Tehran, Iran.KarimGoudarzikiaTehran Regional Electric Company, Tehran, Iran.Journal Article20241117Partial discharge (PD) is a major concern in high-voltage electrical equipment, and its detection is crucial for ensuring the reliability and safety of power systems. In high voltage (HV) air-insulated switchgear (AIS), which is commonly used in the transmission and distribution of electrical power, PD can occur due to various factors such as insulation defects, voids, or impurities. Detecting PD at an early stage is essential to prevent equipment failure and costly downtime. Ultra-high frequency (UHF) detection methods are widely used for PD detection in HV AIS, as they offer high sensitivity and the capability to detect PD signals over long distances. In this paper, we will discuss using Vivaldi directional antennas for PD detection in HV AIS, focusing on their advantages, challenges, and potential applications. The simulation was carried out using CST Microwave Studio, and the result revealed that the antenna has a wide impedance bandwidth of 100% in the range of 0.5 to 1.5 GHz with S11 ˂ -10. An average gain of 5 dB and a maximum gain of 8.62 dB are achieved at the operational frequency band.https://mseee.semnan.ac.ir/article_10105_3f1d8be469dede6dd03fd8d1e17be288.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07865220250901Generalized Incremental Predictive Guidance and Control: Design, Stability, Real-Time Validation, and Simulation19281010610.22075/mseee.2025.38679.1224ENNemat AllahGhahremaniFaculty of Electrical & Computer Engineering, Malek-Ashtar University of Technology, Tehran, Iran.SaeedNasrollahiFaculty of Electrical & Computer Engineering, Malek-Ashtar University of Technology, Tehran, Iran.HusamHasanFaculty of Electrical & Computer Engineering, Malek-Ashtar University of Technology, Tehran, Iran.Journal Article20250815This paper presents a new integrated guidance and control system for an air vehicle based on incremental predictive control. Integrating guidance and control loops improves reliability, enhances performance, and reduces costs. The integration is built using the linear system, with the command signal being the pursuer's deflection angle and the output being the miss distance. The generalized incremental model predictive control is used as the commanding block to control and guide the pursuer to its target. The goal is to minimize a quadratic cost function with a cost associated with the relative displacement between the target and the pursuer and the deflection angle. At first, the dynamical system model is derived, and the target acceleration is added to the system to provide additional information to reduce the control effort. Then, the guidance-control algorithm is designed and implemented, and the stability of the proposed algorithm is proven. After that, the influence of prediction and control horizons on the integrated system is analyzed. The results show the effectiveness of the predictive integrated system. Finally, to ensure the implementation capability of the proposed algorithm, a Processor-in-the-Loop experiment is conducted using Arduino Duo, and it yielded good results.https://mseee.semnan.ac.ir/article_10106_f641990716ff038732fe452f8f3fdfa1.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07865220250901A Power-Efficient Noise-Tolerant Circuit Technique for Wide Dynamic Gates29361020910.22075/mseee.2025.38160.1221ENMohammadAsyaeiSchool of Engineering, Damghan University, Damghan, Iran.Journal Article20250722In this article, a dynamic circuit technique is suggested to lower the consumed power of wide gates without speed degradation. In the proposed circuit, the voltage swing on the evaluation network is reduced to decrease the consumed power of wide gates. To reduce the consumed power and delay of the suggested circuit, the structure of the output inverter is modified by utilizing the voltage of the footer node of the evaluation network. A current mirror is employed to decrease the contention between the evaluation network and keeper transistors, replicating the evaluation network's leakage current. In addition, the subthreshold leakage current is reduced due to the stacking effect. As a result, the leakage power is lowered and the noise immunity is improved. Wide OR gates are simulated using HSPICE in a 90nm CMOS technology. Simulation results of wide OR gates demonstrate 51% power reduction and 1.82× noise immunity improvement at the same delay as the conventional dynamic circuit for 32-input OR gates. Moreover, a 128-input multiplexer is designed by employing the suggested dynamic circuit. The results demonstrate 13% power reduction and 33% speed improvement for the suggested 128-input multiplexer compared to the conventional multiplexer at the same robustness.https://mseee.semnan.ac.ir/article_10209_baa682a1399cf9f4ed01429f3a21573f.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07865220250901Integrated Two‐Stage Stochastic Security‐Constrained Unit Commitment with EV V2G, Utility‐Scale Storage, and Flexible Loads under High Renewable Penetration37611021010.22075/mseee.2025.38263.1219ENAbbas SafariDepartment of Electrical Engineering, Ke.C., Islamic Azad University, Kerman, Iran.0009-0003-2878-568XMehdiJafari ShahbazzadehDepartment of Electrical Engineering, Ke.C., Islamic Azad University, Kerman, Iran.0000-0002-2940-141XMahdiyehEslamiDepartment of Electrical Engineering, Ke.C., Islamic Azad University, Kerman, Iran.0000-0003-1174-1595HesamRahbarimaghamDepartment of Electrical and Computer Engineering, Raf.C., Islamic Azad University, Rafsanjan, Iran.Journal Article20250714This paper presents a comprehensive two‐stage stochastic security‐constrained unit commitment (SCUC) framework that fully integrates electric vehicles (EVs) with vehicle‐to‐grid (V2G) capabilities, utility‐scale energy storage systems (ESS), and flexible demand response under high levels of wind and solar generation. In the first stage, thermal unit on/off decisions and charge/discharge statuses for ESS and EV fleets are co‐optimized to secure reserves and meet mobility constraints. The second stage dispatches generation, reserves, and flexible load adjustments for each renewable‐forecast scenario, while enforcing N‑1 contingency criteria for both generator and transmission‐line outages. Key innovations include a novel EV‐V2G submodel that tracks state‐of‐charge (SoC), enforces arrival/departure requirements, and co‐optimizes reserve provision; an ESS formulation that co‐optimizes energy arbitrage with spinning and non‐spinning reserves; and a flexible‐load shifting paradigm that permits both time‐shiftable consumption and curtailment at a user‐dissatisfaction penalty. Renewable uncertainty is captured through a scenario‐reduction technique applied to correlated wind and solar forecasting errors. A nested Benders‐decomposition algorithm exploits scenario and contingency decomposition for tractability. Numerical experiments on a modified IEEE‑118 bus system—using real‐world wind/solar traces and realistic EV/ESS parameters—demonstrate that the proposed model decreases expected operating and reserve‐procurement costs by up to 8.5% relative to deterministic SCUC, cuts renewable curtailment from 35% to 20%, and reduces expected load‐shedding under contingencies by over 75%. The joint flexibility of EVs, ESS, and flexible loads significantly enhances system reliability and economic performance in high‐renewable power systems.https://mseee.semnan.ac.ir/article_10210_54ed6c0240ce3ba8b043b6ba7a9bdf08.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07865220250901Artificial Neural Networks and Hybrid Evolutionary Algorithms for Multi-Objective Optimization of Analog Integrated Circuit Design63761021110.22075/mseee.2025.38966.1227ENAliBahadoriniaDepartment of Electrical Engineering, Faculty of Engineering, Hakim Sabzevari University, Sabzevar, Iran.Journal Article20250908The design of analog integrated circuits demands the careful optimization of multiple interdependent parameters, including transistor sizes, bias currents, and passive components, to meet stringent performance targets such as gain, bandwidth, phase margin, and power efficiency. To address this challenge, this work introduces a computational intelligence framework that combines artificial neural networks (ANNs) with a hybrid genetic algorithm–particle swarm optimization (GA–PSO) strategy. The framework was validated on two representative circuits: a two-stage CMOS operational amplifier with Miller compensation and a differential LC voltage-controlled oscillator (LC-VCO) operating at 2.8 GHz in 0.18-µm CMOS technology. Extensive HSPICE simulations generated datasets that enabled the ANN to capture the complex nonlinear relationships between design variables and performance metrics. The method successfully predicted optimal device dimensions and biasing conditions, achieving a 160% improvement in figure of merit (FoM) for the amplifier and a FoM of 118.1 dBc/Hz for the LC-VCO, comparable to state-of-the-art designs. These results demonstrate the framework’s versatility and scalability, providing a flexible soft-computing tool for multi-objective optimization across diverse analog circuit topologies.https://mseee.semnan.ac.ir/article_10211_0c52beb8575a269c9cdf8ca280bb7b75.pdf