Mohd Herwan Sulaiman

• PhD
• Professor (Associate) at Universiti Malaysia Pahang Al-Sultan Abdullah

The increasing integration of wind energy into power grids necessitates accurate and reliable wind power generation forecasts. Precise predictions are crucial for grid stability, efficient energy management, and optimal economic dispatch. However, the inherent variability and intermittency of wind resources pose significant challenges to traditiona...

Heart failure is a critical condition with a high mortality rate, making accurate survival prediction essential for timely interventions. This study proposes an optimized machine learning approach using Gradient Boosting Machine (GBM) and Adaptive InertiaWeight Particle Swarm Optimization (AIW-PSO) to predict heart failure survival. The dataset, so...

Mathematical models of Barnacle Mating Optimization (BMO) are based on observations of real-world barnacle mating behaviors such as sperm casting and self-fertilization. Nevertheless, BMO considers penis length to produce new offspring through pseudo-copulated mating behavior, with no constraints like strong wave motion, food availability, or wind...

Short-term load forecasting (STLF) plays a vital role in effective power system management by assisting power dispatch centers in developing generation plans and ensuring smooth system operation. This study introduces a novel hybrid prediction model called iSSA-LSSVM to tackle the STLF challenge. By integrating the Salp Swarm Algorithm (SSA) with L...

Similar to multi-frequency techniques in eddy current and magnetic flux leakage testings, the harmonic evaluation technique using a square wave excitation field improves the defect detection performance of conductive materials compared to single-frequency techniques. However, in the case of mild steel, its nonlinear frequency-dependant magnetizatio...

Accurately estimating the remaining useful life (RUL) of batteries is crucial for optimizing maintenance, preventing failures, and enhancing reliability, thereby saving costs and resources. This study introduces a hybrid approach for estimating the RUL of a battery based on the firefly algorithm–neural network (FA–NN) model, in which the FA is empl...

This paper presents the development of overcurrent relay coordination (OCRC) problem formulation by implementing five well known metaheuristic algorithms that are Ant Lion Optimizer (ALO), Moth Flame Optimizer (MFO), Grey Wolf Optimizer (GWO), Particles Swarm Optimizer (PSO) and Barnacles Matting Optimizer (BMO). The algorithms are assisted with pe...

This paper introduces the Gooseneck Barnacle Optimisation Algorithm (GBO) as a novel evolutionary method inspired by the natural mating behaviour of gooseneck barnacles, which involves sperm casting and self-fertilization. GBO is mathematically modelled, considering the hermaphroditic nature of these microorganisms that have thrived since the Juras...

In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. The high-Tc SQUID magnetometer is constructed from a high-Tc SQUID sensor couple...

Detection of crack propagation, such as its direction and depth, is one of the important aspects in ensuring the safety and reliability of steel structures. This study presents a development of a circular eddy current excitation probe using a planar differential miniature fluxgate to detect vertical and horizontal slits. The probe utilizes a circul...

A wind turbine is a structure that converts the energy generated by the wind into electrical power by utilizing wind vans called wind blades. Thus, wind blades play an essential role in a wind turbine. Due to open and high terrain construction, wind turbines are continuously exposed to lightning strikes. Therefore, electrical field activity may var...

Wind turbines are one of the most important natural sources of energy. The components of atmosphere gases in the surrounding wind turbines that are installed may significantly affect the increasing of electrical field resulting from lighting strikes. Here, we use the initiation and spread of electrical field in various gases O 2 , N 2 , Ar, Ne and...

Microorganisms may cause illness when theyenter the body, multiply, and spread to other parts. The rapidspread of COVID-19 to neighboring countries is examined inthis research. Anticipating a positive COVID-19 occurrencehelps in determining risks and creating countermeasures. As aresult, developing robust mathematical models with small errormargins...

This paper introduces an optimal control strategy for pneumatic servo systems (PSS) positioning using Finite-time Prescribed Performance Control (FT-PPC) with Particle Swarm Optimization (PSO). Pneumatic servo systems are widely used in industrial automation, as well as medical and cybernetics systems that involve robotics applications. Precision i...

SARS-CoV-2 is a multi-organ disease characterized by a wide range of symptoms, which also causes the severe acute respiratory syndrome. When it initially began, it rapidly spread from its origin to adjacent nations, infecting millions of people around the globe. In order to take appropriate preventative and precautionary actions, it is necessary to...

Reliability and controls are essential for preventing outages, load disparity, and synchronization mismatch in a power system. Smart Grid (SG) is a cost-effective solution for minimizing inter-regional variations, optimizing load demand, stabilizing equipment operations, and managing conventional and renewable power sources. However, SGs are still...

Every country must have an accurate and efficient forecasting model to avoid and manage the epidemic. This paper suggests an upgrade to one of the evolutionary algorithms inspired by nature, the Barnacle Mating Optimizer (BMO). First, the exploration phase of the original BMO is enhanced by enforcing and replacing the sperm cast equation through Le...

Artificial Neural Network (ANN) is an effective machine learning technique for addressing regression tasks. Nonetheless, the performance of ANN is highly dependent on the values of its parameters, specifically the weight and bias. To improve its predictive generalization, it is crucial to optimize these parameters. In this study, the Barnacles Mati...

This paper proposes a simulation study to solve the optimal allocation of the Battery Energy Storage System (BESS) problem in distribution networks. The effect of BESS's installation in the selected distribution networks is surveyed for a 24-hour period, where time-of-use electricity charges are divided into three periods: standard, peak, and off-p...

In recent years, the environmental and economic consequences of coal, gasoline and other conventional energy sources have been widely discussed. Currently, Pakistan's energy output is highly dependent on these resources; as a consequence, the country is facing a severe energy crisis. The government spends more than $3.7 billion annually on fossil f...

This paper proposes the implementation of metaheuristic algorithm namely, teaching-learning-based optimization (TLBO) algorithm to solve optimal power flow (OPF) problem. TLBO is inspired by philosophy of teaching and learning in the classroom. OPF on the other hand, is one of the most complex problems in power system operation, where in this paper...

A wind turbine is a structure that converts the energy generated by the wind into electrical power by utilizing wind vans called wind blades. Thus, wind blades play an essential role in a wind turbine. Due to open and high terrain construction, wind turbines are continuously exposed to lightning strikes. Therefore, electrical field activity may var...

This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve constrained optimization problems. The algorithm is based on the adoption of random mating concept from Hardy–Weinberg equilibrium and crossover index in order to produce new offspring. In this algorithm, effect of the environmental factor (i.e. the...

The variables that maximize an objective function, specific equality requirements, such as the power balancing and power flow equations, and inequality constraints, restrictions on the variables, are the most crucial elements of the optimal power flow (OPF). The set of parameters and constraints, as well as the shape of the objective, will vary dep...

The power grid, one of the most crucial components of smart cities, faces significant challenges in operating efficiently, dependably, and economically. One of these challenges is forecasting the demand for electricity. Grid managers can balance supply and demand properly while also minimizing operating expenses for generating and transmitting powe...

The reduction of line losses due to current heating is known as loss minimization in optimal power flow (OPF). This is accomplished by selecting and enhancing an existing power solution from the system's past cost reduction. This paper offers a collection of methods for assessing congested power networks to achieve the lowest operating cost with th...

In this study, we report a development of a benchtop induction-based AC magnetometer to realize a simple, wideband, and sensitive AC magnetometer for bio-sensing applications and characterization of magnetic nanoparticles (MNPs). We investigate the inductance and parasitic capacitance of six different pickup coil geometries and compare their sensit...

This paper proposes the implementation of various metaheuristic algorithms in solving the optimal power flow (OPF) with the presence of Flexible AC Transmission System (FACTS) devices in the power system. OPF is one of the well-known problems in power system operations and with the inclusion of the FACTS devices allocation problems into OPF will ma...

This paper proposes an application of evolutionary optimization algorithm, Barnacles Mating Optimizer (BMO) to solve the optimal chiller loading (OCL) problem for minimization of the power consumption in the multi chiller system. BMO mimics the mating behaviour of barnacles in nature. To generate new off-springs, the concept of Hardy-Weinberg princ...

Optimal Power Flow (OPF) solution is one of the active research topics in power system optimization problems. It is one of the complex non-linear optimization problems where the determination of economical and efficient operation should be done by obtaining the steady state of electrical components in power networks. Various metaheuristic algorithm...

Optimal load dispatching is an important challenge for modern electric and computational engineering. Considering different linear and nonlinear constraints optimal load analysis is done to predict the utility and operating duration of the different power stations. This paper reports the optimal loading analysis method using the Brute Force method...

This paper proposes an improvement of bio inspired metaheuristic algorithm namely Salp Swarm Algorithm (ISSA) which later to be implemented in solving the Optimal Power Flow (OPF) problem. OPF is a well-known optimization problem in power system operation and the proposed ISSA has been utilized to solve one of the objective functions viz. loss mini...

This paper presents a study in maximum power point tracking (MPPT) technique in solar photovoltaic (PV) using moth flame optimization (MFO) algorithm. Despite the solar PV is one of the most popular method for power generation, the effort to maximize the energy yield from the installed PV system remains a challenge. The study aims to identify the p...

The Covid19 has significantly changed the global landscape in every aspect including economy, social life, and many others. After almost two years of living with the pandemic, new challenges are faced by the research community. It may take some time before the world can be declared as totally safe from the virus. Therefore, prediction of Covid19 co...

Optimal power flow (OPF) is one of the complex problems in power system operation that includes multi-modal, large-scale, non-convex and non-linear constrained optimization problems. Due to these features, solving the OPF problem is becoming an active topic to be solved by power engineers and researchers. In this paper, recent metaheuristic algorit...

This work proposes the implementation of recent evolutionary metaheuristic algorithm namely, barnacles mating optimizer (BMO) to solve the Optimal Power Flow (OPF) issue. BMO is inspired by the mating behaviour of barnacles which happened in two ways: by normal copulation and sperm‐cast. The effectiveness of the proposed BMO in solving the OPF is t...

Characterization of structural and magnetic properties of MNP ensembles is crucial in tailoring their performance for biomedical applications. In this work, we evaluate the size distribution of magnetic cores in single- and multi-core nanoparticles in water suspension using transmission electron microscopy (TEM) and static magnetization curve, with...