Ashik Ahmed

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• Doctor of Philosophy
• Professor at Islamic University of Technology

Low frequency oscillation (LFO) is one of the major concerns for reliable operation of the power system. This LFO occurs due to the failure of the rotor to supply sufficient damping torque to compensate the imbalance between mechanical input and electrical output. Hence, in this paper, we adopt a third generation flexible AC transmission system (FA...

The critical challenge for an efficient islanding operation of a distribution system having Distributed Generation (DG) is preserving the frequency and voltage stability. Contemporary load shedding schemes are inefficient and do not adequately assess the optimum amount of load to shed which results in either excessive or inadequate load shedding. H...

Zero-carbon energy infrastructure design has become one of the most consequential pivotal toward sustainable development. This article introduces a novel approach to energy infrastructure innovation that incorporates carbon-free energy generation resources- renewables and Micro Nuclear Reactors (MNRs). The integrated Nuclear-Renewable Microgrid (NR...

A challenging engineering optimization problem in electrical power generation is the unit commitment problem (UCP). Determining the scheduling for the economic consumption of production assets over a specific period is the premier objective of UCP. This paper presents a take on solving UCP with Binary Slime Mould Algorithm (BSMA). SMA is a recently...

Microgrids with integrated renewable energy-based distributed generation (RDG) and battery energy storage systems (BESS) should be effectively designed and controlled to reap the potential benefits. In this context, this study recommends a novel Multi-objective Artificial Hummingbird Algorithm (MOAHA) based framework for optimal RDG allocation and...

Alzheimer’s disease (AD) is one of the most prevalent chronic neurological illnesses among older persons. Early diagnosis of AD enables timely intervention and management, traditionally achieved through clinical assessments, cognitive tests, and neuroimaging techniques like Magnetic Resonance Imaging (MRI). MRI can diagnose AD at various stages, in...

The dynamic nature of consumer load demands requires power systems to make complex decisions about the operation of multiple generating units. The Unit Commitment Problem (UCP) optimizes unit scheduling over a 24–48 h horizon while considering operational constraints. Simultaneously, reducing greenhouse gas (GHG) emissions has become critical, maki...

The efficiency of photovoltaic (PV) modules significantly reduces due to accumulation of dust. To minimize the dust effect on PV in a cost-effective manner, optimal cleaning interval need to be decided. To accomplish this objective, machine learning(ML) models can be utilized to detect dust level on PV beyond predefined threshold which would then a...

Hybrid Renewable Energy System (HRES) has become a popular alternative for locations restricted to national grid connection due to geographical limitations. The study investigates the available renewable resources of a remote village in Mymensingh district of Bangladesh to propose and evaluate optimal sizing and cost of a grid independent HRES. The...

The Load Frequency Control (LFC) scheme, with its primary aim being the maintenance of uniform frequency, has been a heavily researched topic for decades. Achieving a consistent frequency necessitates a delicate balance between load demand and power generation. Researchers strive to find an optimal solution within the LFC domain—one that can effect...

Stability of power converters has always been a major concern when dealing with nonlinear behavior of the system and swarm-based optimization techniques are proven to be handy as they are widely employed. Hence, this study presents an investigative approach to explore the compatibility of applying different variants of Particle Swarm Optimization (...

Renewable energy resources are the only sustainable and environment-friendly solution to the energy crisis that the whole world is facing and the crisis is likely to exacerbate in the future unless dealt with proper emphasis. The hybridization of various renewable energy resources not only helps in alleviating the continuously rising demand of conv...

Hybrid renewable energy systems (HRES) have the potential to provide a reliable and cost-effective source of power by combining multiple sources of renewable energy. In this study, a techno-economic analysis of an HRES is conducted in Lalmonirhat, Bangladesh using load data from the Northern Electricity Supply Company (NESCO). Two population-based...

Multi-agent deep reinforcement learning (MADRL) approaches are at the forefront of contemporary research in optimum electric vehicle (EV) charging scheduling challenges. These techniques involve multiple agents that respond to a dynamic simulation environment to strategically integrate EV charging stations (EVCSs) on microgrids by incorporating the...

Depression is a psychological state of mind that often influences a person in an unfavorable manner. While it can occur in people of all ages, students are especially vulnerable to it throughout their academic careers. Beginning in 2020, the COVID-19 epidemic caused major problems in people’s lives by driving them into quarantine and forcing them t...

According to several studies, conventional fuels are a finite source of energy and have several negative effects on the environment. Therefore, it is in everyone's best interest to implement Distributed Generation Units based on renewable energy (or RDGs for short) to guarantee the proper operation of power systems. However, due to the intermittent...

In present days, estimating harmonic components has become an important research area for conventional power system. Several stochastic optimization methods have been employed to successfully estimate the amplitude and phase of a harmonic signal. A novel optimization strategy must be implemented to increase precision and reduce the computational ti...

Multi-agent deep reinforcement learning (MADRL) approaches are at the forefront of contemporary research in optimum electric vehicle (EV) charging scheduling challenges. These techniques involve multiple agents that respond to a dynamic simulation environment to strategically integrate EV charging stations (EVCSs) on microgrids by incorporating the...

Renewable resources are most effective for sustainable development of society and economically efficient for small-scale power generation. However, grid integration is challenging because of the randomness of the source effects on power system parameters. This work proposes power quality enhancement by incorporating Static VAR Compensator (SVC) in...

In today’s constantly advancing economy, fast and efficient load frequency control (LFC) schemes are imperative for stable power systems operation, whether conventional or new. Despite recent advances in this domain, professional engineers, to this day, face significant obstacles in dealing with parametric uncertainty and the rejection of external...

The COVID-19 pandemic has worsened the psychological and social stress levels of university students due to physical illness, enhanced dependence on mobile devices and internet, a lack of social activities, and home confinement. Therefore, early stress detection is crucial for their successful academic performance and mental well-being. The advent...

Microgrids with integrated renewable energy-based distributed generation (RDG) and battery energy storage systems (BESS) should be effectively designed and controlled to reap the potential benefits. In this context, this study recommends a novel Multi-objective Artificial Hummingbird Algorithm (MOAHA) based framework for optimal RDG allocation and...

An optimal energy mix of various renewable energy sources and storage devices is critical for a profitable and reliable hybrid microgrid system. This work proposes a hybrid optimization method to assess the optimal energy mix of wind, photovoltaic, and battery for a hybrid system development. This study considers the hybridization of a Non-dominant...

This work proposes the adoption of Enhanced Gradient-Based Optimizer (EGBO) as a new approach to the Load Frequency Control (LFC) problem in a two-area interconnected power system. The importance of determining the optimal parameters for the controllers for the LFC problem cannot be overstated, and the fact that estimating these parameters require...

This work proposes the adoption of Enhanced Gradient-Based Optimizer (EGBO) as a new approach to the Load Frequency Control (LFC) problem in a two-area interconnected power system. The importance of determining the optimal parameters for the controllers for the LFC problem cannot be overstated, and the fact that estimating these parameters require...

Appropriate installation of renewable energy-based distributed generation units (RDGs) is one of the most important challenges and current topics of interest in the optimal functioning of modern power networks. Due to the intermittent nature of renewable energy sources, optimal allocation and sizing of RDGs, particularly photovoltaic (PV) and wind...

In this chapter, a hybrid bare bones fireworks algorithm (HBBFWA) is proposed and its application in solving the load flow problem of islanded microgrid is demonstrated. The hybridization is carried out by updating the positions of generated sparks with the help of grasshopper optimization algorithm (GOA) mimicking the swarming behavior of grasshop...

Psychological health of postgraduate students has received significant attention with the emergence of COVID-19. However, the detection of these psychological disorders appears to be a prolonged process as rigorous clinical tests and diagnoses are involved. In this context, machine learning algorithms are capable of analyzing the hidden pattern of...

Among the renewable sources of energy, wind and photovoltaic based energy conversion processes are capturing recent interests. As the input to these two kinds of energy conversion processes is highly unpredictable, the incorporation of an energy storage device becomes imperative for an uninterruptible power supply. However, considering hybrid renew...

Swarm-based nature-inspired optimization techniques are developing rapidly due to their universal acceptance and capability in solving various real-life challenges efficiently. Hybridization of swarm intelligence based optimization algorithms with multi-objective based solution techniques is creating a wide door in the field of optimization. The ma...

Among the renewable sources of energy, wind and photovoltaic based energy conversion processes are capturing recent interests. As the input to these two kinds of energy conversion processes is highly unpredictable, the incorporation of an energy storage device becomes imperative for an uninterruptible power supply. However, considering hybrid renew...

Load flow analysis is a significant tool for proper planning, operation, and dynamic analysis of a power system that provides the steady-state values of voltage magnitudes and angles at the fundamental frequency. However, due to the absence of a slack bus in an islanded microgrid, modified load flow algorithms should be adopted considering the syst...

Global optimization algorithms are becoming popular at a fast rate as they are able to solve different real-life challenges. Metaheuristic algorithms are one of the important parts in the discussion about global optimization algorithms and computational intelligence. Most of the metaheuristic algorithms are generally nature-inspired with various in...

Low-frequency oscillations should be dealt with extreme care for secure electric networks. This paper tunes the critical parameters of power system stabilizers in three different electric networks in real-time, employing the neurogenetic approach to damp out the low-frequency oscillations. The first network is a single machine infinite bus power sy...

In this chapter, a hybrid bare bones fireworks algorithm (HBBFWA) is proposed and its application in solving the load flow problem of islanded microgrid is demonstrated. The hybridization is carried out by updating the positions of generated sparks with the help of grasshopper optimization algorithm (GOA) mimicking the swarming behavior of grasshop...

This paper proposes the application of differential evolution (DE) algorithm for the optimal tuning of proportional–integral controller designed to improve the small signal dynamic response of a grid-connected solid oxide fuel cell (SOFC) system. The small signal model of the study system is derived and considered for the controller design as the t...

In wind power system, low frequency oscillations are observed due to imbalance between mechanical input and electrical output. Hence, variable susceptance controllers are being adopted to mitigate these oscillations. However, improper modulation of control parameters also leads to system instability. Therefore, we propose an optimization methodolog...

Determination of accurate modeling parameters of optical materials prior to defining the materials in the simulation model is fundamentally important to obtain simulation results close to the experimental ones. However, extracting modeling parameters of optical materials is inherently difficult because it involves fitting both real and imaginary pa...

Particle swarm optimization (PSO) and invasive weed optimization (IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired algorithms are used here for the first time in this particular field to the best of our knowledge. The algorithms are used for model...

Application of input–output linearization control for improving the dynamic response of a stand-alone solid oxide fuel cell (SOFC) system is presented in this work. The proposed controllers are incorporated in the study system to eliminate the sluggishness in the hydrogen and oxygen partial pressure responses due to variations in the SOFC reference...

The function of Automatic Generation Control (AGC) is to regulate the output power of the corresponding generator in response to changes in system frequency or tie line loading or in both cases within a prescribed limit. In this paper Differential Evolution (DE) based Proportional-Integral (PI) controller is designed and simulated to observe its pe...

This paper proposes the application of differential evolution (DE) algorithm for the optimal tuning of proportional–integral (PI) controller designed to improve the small signal dynamic response of a stand-alone solid oxide fuel cell (SOFC) system. The small signal model of the study system is derived and considered for the controller design as the...

Load Frequency Control (LFC) for any power generating station is a subject of great concern for power system researchers. With the changes of load demand, frequency starts fluctuating which results in deviation in tie line power flow and frequency deviation at consumer end. To overcome this problem, many control techniques have been adopted. In ear...

Load Frequency Control (LFC) for any power generating station is a subject of great concern for power system researchers. With the changes of load demand, frequency starts fluctuating which results in deviation in tie line power flow and frequency deviation at consumer end. To overcome this problem, many control techniques have been adopted. In ear...

The impact of High voltage direct current (HVDC) transmission on power system dynamic stability is mainly discussed in this paper and the system dynamic response is analyzed under small disturbance. The establishment of linearized model of a single machine infinite bus (SMIB) system equipped with Voltage source converter (VSC) based HVDC is also pr...

We present the Debye model parameters of four materials which are extensively used in the field of electronics and photonics. The parameters have been extracted using a Genetic Algorithm (GA) based technique. We have determined the complex relative permittivity using the extracted modeling parameters and compared with the experimentally obtained on...

This paper proposes designing of Static Synchronous Series Compensator (SSSC) based damping controller to enhance the stability of a Single Machine Infinite Bus (SMIB) system by means of Invasive Weed Optimization (IWO) technique. Conventional PI controller is used as the SSSC damping controller which takes rotor speed deviation as the input. The d...

This paper addresses model predictive controller (MPC) as an effective solution for improving the oscillations in a single machine infinite bus (SMIB) power system connected with a Flexible AC Transmission System (FACTS) device, unified power flow controller (UPFC). UPFC is mainly used in the transmission systems which can control the power flow by...

Power system stabilizer (PSS) is used in order to damp out the low frequency oscillations among the interconnected group of generators of a large power system. Differential Evolution (DE) is one of the modern approaches for the appropriate design of PSS for multi-machine power system. This paper presents DE based PSS design and analyses its perform...

Model predictive controller (MPC) is an effective solution for improving the oscillations in a single machine infinite bus (SMIB) power system connected with a FACTS device, unified power flow controller (UPFC). UPFC is mainly used in the transmission systems which can control the power flow by controlling the voltage magnitude, phase angle and imp...

This paper addresses model predictive controller (MPC) as an effective solution for improving the oscillations in a single machine infinite bus (SMIB) power system connected with a FACTS device, unified power flow controller (UPFC). UPFC is mainly used in the transmission systems which can control the power flow by controlling the voltage magnitude...

Nowadays, switched reluctance motors (SRMs) attract more and more attention. Switched reluctance machines have emerged as an important technology in industrial automation. They represent a real alternative to conventional variable speed drives in many applications. It not only features a salient pole stator with concentrated coils, which allows ear...

In this paper, two evolutionary algorithms-Invasive Weed Optimization (IWO) based power system stabilizer (PSS) and particle swarm optimization (PSO) based power system stabilizer is designed for multi-machine power system to compare their tuning performances. IWO is a derivative-free real parameter optimization technique that mimics the ecological...

Underground cables have replaced the use of overhead lines in the main cities around the world, although costly but cables have been preferred because of its higher current carrying capability and very low maintenance. Different properties of the cable itself and also of the environment limit the current carrying capacity, ampacity, of a cable. Amp...

In this paper, an evolutionary algorithm-Invasive Weed Optimization (IWO) based power system stabilizer (PSS) is proposed for multi-machine power system. IWO is a derivative-free real parameter optimization technique that mimics the ecological behavior of colonizing weeds. Owing to its superior performance in comparison with many other existing met...

In this paper the step-by-step procedure of obtaining the network equivalent of a large power system using Power System Simulators for Engineers (PSS/E) is presented. Coherency among the generators of the study system is identified using the non-linear time domain simulation obtained by PSS/E. Generators with the most identical swing are considered...