Ernie Che Mid
Thumbnail Image
Preferred name
Ernie Che Mid
Official Name
Ernie, Che Mid
Alternative Name
Che Mid, Ernie Binti
Che Mid, Ernie
Mid, E. C.
Scopus Author ID
25655179600
Researcher ID
V-7047-2019

Research Output

Filters

10
2 1
10
Reset filters

Settings
Now showing 1 - 10 of 10
Thumbnail Image
Publication

Fault Detection Analysis for Three Phase Induction Motor Drive System using Neural Network

2021-06-11 , Mohar N.A. , Ernie Che Mid , Surina Mat Suboh , Nor Hanisah Baharudin , Ahamad N.B. , Rahman N.A. , Ruslan E. , Hadi D.A.

One of the most important components of the industrial process is known to be the three-phase induction motor. This device, however, is prone to electrical and mechanical faults, which may cause a substantial component or financial losses. The fault analysis received growing attention due to a need to increase reliability and to decrease potential output loss due to machine breakdown. Thus, the purpose of this paper is to present a simple and reliable fault analysis based on the Neural Network (NN) is proposed. The NN method is a simpler approach without a diagnostic professional to review data and diagnose issues. Various fault disputes of induction motor are developed and analysed using the NN method. The main types of faults considered are over-voltage, under-voltage, and unbalanced voltage faults. The trained network is tested with simulated fault current and voltage data.

View
Thumbnail Image
Publication

Feasibility Study of Future Seaports

2021-06-11 , Nor Baizura Ahamad , Othman M. , Ernie Che Mid , Muhammad Izuan Fahmi Romli , Surina Mat Suboh , Guerrero J.M.

Port is a focal point especially in the trade sector, where it is represented as hub for the import and export from one destination to another. Despite the fact that it gives positive impact to country specifically in economic sector but from the health sector, this activity leaves a negative impact on the environment and human health, especially those living near the port. Now, most of developed countries have made improvements by converting conventional engines (diesel engines) to electrical engines for major vehicles in ports. The same goes for shore-side ports, most of them using cold ironing (CI). However, all the modification is still raw and faced several challenges, especially in technical aspects such as voltage difference, frequency, supply / demand. It occurs due to the difference in standard voltage and frequency between shore-side and ship. Most of the ocean ship used 60 Hz. In addition, the main constraint faced is that the power supplied on the shore-side is not enough to meet the demand from customers. Thus, to make additions to the existing substation, it will require high initial costs. After evaluating the pros and cons, the new approach is taken to integrate this system into microgrid technology. Microgrid technology is a local cluster energy source with a control capability comprising Energy Distribution Resources (DER), which cover management request, storage, and loads. One of the advantages of a microgrid is that they can be connected or disconnected from the grid to operate autonomously.

View
Thumbnail Image
Publication

Explicit Solution of Parameter Estimate using Multiparametric Programming for Boost Converter

2023-01-01 , Ernie Che Mid , Nurhakimah Mohd Mukhtar , Syed Yunus S.H. , Hadi D.A. , Ruslan E.

This work proposes an approach to estimate the parameters of capacitance and inductance in a boost converter using an explicit solution. A multiparametric programming (MPP) algorithm is fundamental to the suggested methodology, which aims to develop parameters as explicit functions of measurements. In this method, the generalised mathematical model of the boost converter is discretised into an algebraic equation. The parameter estimation problem is then formulated and solved using Karush-Kuhn-Tucker. Finally, an explicit solution of estimate parameters such as capacitor and inductor is formulated as an explicit function of the inductor currents and capacitor voltage. Finally, the state variables of the boost converter are numerically obtained and used to test the capability of the proposed work. The results presented in this work prove the MPP algorithm can estimate the boost converter's parameters, which can be extended to other power converters and filters.

View
Thumbnail Image
Publication

Hybrid Cooling System for Solar Photovoltaic Panel

2023-01-01 , Azmi M.S.F.M. , Muhamad Hatta Hussain , Siti Rafidah Abdul Rahim , Ernie Che Mid , Shaari A.S. , Nurul Huda Hashim , Husny N. , Mohd Fairus Ahmad

Solar photovoltaic (PV) panel is one of the renewable sources of energy and produced daily nowadays. Solar panel systems have efficiency influenced by different factors, such as ambient temperature, solar panel temperature, sunlight, weather, and irradiation. The increasing of the temperature of the solar PV panel decreases its efficiency and lifetime. Thus, to maintain and decrease the temperature of the PV cell, cooling system is required. This paper presents the hybrid (water and air) cooling system method for solar PV panel. The method has been designed and developed to lower and stable the operating temperature of the system considering different weather conditions. The results revealed that the hybrid cooling system has shown improvement of output power solar PV panel as compared with water cooling system only. Furthermore, the proposed method managed to improve efficiency approximately to 4.5%.

View
No Thumbnail Available
Publication

Harmonics elimination of reduced switch multilevel inverter using henry gas solubility optimization algorithm

2025-06 , Zainuddin Mat Isa , Baharuddin Ismail , Mohd Hafiz Arshad , Ernie Che Mid

This study introduces a pioneering method to enhance the efficiency and effectiveness of three-phase five-level reduced switch cascaded H-bridge multilevel inverters (CHB MLI) by employing the Henry Gas Solubility Optimization (HGSO) algorithm. Targeting the selective harmonic elimination (SHE) technique, the research emphasizes the optimization of switching angles to significantly reduce total harmonic distortion (THD) and align the fundamental output voltage closely with the reference voltage. Central to this exploration are three distinct objective functions (OFs), meticulously designed to assess the HGSO algorithm’s performance across various modulation indices. Simulation results, facilitated by PSIM software, illustrate the impactful role these objective functions play in the optimization process. OF1 demonstrated a superior ability in generating low OF values and maintaining a consistent match between reference and fundamental voltages across the modulation index spectrum. Regarding the reduction of THD, it is crucial to emphasize that all OFs can identify the most effective switching angle to minimize THD and eliminate the fifth harmonic to a level below 0.1%. The findings highlight the potential of HGSO in solving complex optimization challenges within power electronics, offering a novel pathway for advancing modulation strategies in CHB MLIs and contributing to the development of more efficient, reliable, and compact power conversion systems.

View
Thumbnail Image
Publication

Investigation of MPC performance for wind turbine system during wind speed uncertainty

2022-01-01 , Nurul Afiqah Nabilah Zainudin , Surina Mat Suboh , Mohd Zamri Hasan , Ernie Che Mid , Ahmad N.B. , Nor Hanisah Baharudin , Shamsul Bahar Yaakob

Real-time implementation for wind turbines (WTs) needs a controller that could explicitly formulate the system constraints and uncertainty in the design process to avoid undesired behavior or breakdown. Model-Predictive-Control (MPC) approach will be used in this research due to its ability to cover actuator and state constraints as well as multivariable control in a more convenient way. To investigate the impact of ad-hoc constraints and wind speed uncertainties, the MPC controller will first be developed. This paper will observe the effect on wind turbines (WT) during uncertainty happen. Multiple uncertainties are simulated to investigate the behavior of the wind turbine system. The simulation results using MATLAB Simulink output are expected to indicate that the MPC controller can ensure the system stability to meet the desired output while satisfying all of the constraints. During the presence of uncertainty, it shows that the MPC controller takes time to stabilize the system.

View
No Thumbnail Available
Publication

Double sigmoid activation function for fault detection in wind turbine generator using artificial neural network

2025-06 , Noor Fazliana Fadzail , Samila Mat Zali , Ernie Che Mid

The activation function has gained popularity in the research community since it is the most crucial component of the artificial neural network (ANN) algorithm. However, the existing activation function is unable to accurately capture the value of several parameters that are affected by the fault, especially in wind turbines (WT). Therefore, a new activation function is suggested in this paper, which is called the double sigmoid activation function to capture the value of certain parameters that are affected by the fault. The fault detection in WT with a doubly fed induction generator (DFIG) is the basis for the ANN algorithm model that is presented in this study. The ANN model was developed in different activation functions, namely linear and double sigmoid activation functions to evaluate the effectiveness of the proposed activation function. The findings indicate that the model with a double sigmoid activation function has greater accuracy than the model with a linear activation function. Moreover, the double sigmoid activation function provides an accuracy of more than 82% in the ANN algorithm. In conclusion, the simulated response demonstrates that the proposed double sigmoid activation function in the ANN model can effectively be applied in fault detection for DFIG based WT model.

View
No Thumbnail Available
Publication

Analysis of fault detection and classification in photovoltaic arrays using neural network-based methods

2025-06 , Arizadayana Zahalan , Samila Mat Zali , Ernie Che Mid , Noor Fazliana Fadzail

Photovoltaic (PV) systems are vital in the global renewable energy landscape because of their capability to harness solar energy efficiently. Ensuring the continuous and efficient operation of PV systems is crucial in maximizing their energy contribution. However, these systems' reliability and safety remain critical because they are prone to various faults, mainly when operating in harsh environmental conditions. This study addresses these issues by exploring fault detection and classification in PV arrays using neural network (NN) -based techniques. A PV array model, consisting of 3x6 PV modules, was simulated using MATLAB Simulink to replicate real-world conditions and analyse various fault scenarios. An open circuit, a short circuit, and a degrading fault are the three types of faults considered in this study. The NN was trained on a dataset generated from the MATLAB Simulink model, encompassing normal operating and fault conditions. This training enables the network to learn the distinctive patterns associated with each fault type, enhancing its detection accuracy and classification capabilities. Simulation results demonstrate that the NN-based approach effectively identifies and classifies the three types of faults.

View
Thumbnail Image
Publication

Design and Performance Analysis of Grid Connected Photovoltaic (GCPV) based DSTATCOM for Power Quality Improvements

2021-06-11 , Nor Hanisah Baharudin , Ridzwan M.A.H. , Tunku Muhammad Nizar Tunku Mansur , Rosnazri Ali , Kumuthawathe Ananda-Rao , Ernie Che Mid , Surina Mat Suboh , Abdullah A.M.

Solar energy has become the most prominent renewable energy for electrical power generation of the sustainable development agenda. This project focuses on power quality improvement in the low voltage distribution network by using a three-phase three-wire Distributed Static compensator (DSTATCOM) supplied by a single-stage grid-connected solar photovoltaic (GCPV) system. The instantaneous reactive power theory (IRPT) or P-Q theory will be used as the control algorithm of the PV based DSTATCOM to eliminate the harmonic current caused by the non-linear loads in the distribution system. This control method has great impact on the accuracy of the harmonic current and reactive power compensation for harmonic current elimination according to the requirement of THD limit set by IEEE 519-2014. Sizing of the grid-connected solar PV system based DSTATCOM will be presented and capable to deliver the active power demand to the utility grid under variation of solar irradiances. This system is modelled and simulated in the MATLAB/Simulink environment.

View
Thumbnail Image
Publication

Output Power Maximization of DFIG Wind Turbine using Linear MPC Technique

2021-06-11 , Surina Mat Suboh , Hassan M.S. , Nor Hanisah Baharudin , Kumuthawathe Ananda-Rao , Ahamad N.B. , Ernie Che Mid , Othman M. , Sardi J.

Wind energy conversion systems have been attracting wide attention as a renewable energy source. To extract maximum energy from the wind turbine, an efficient controller plays an important role. The target of this paper is to develop a Linear Model Predictive Control (MPC) to maximize power production according to wind speed. Firstly, the DFIG wind turbine model was linearized at a specific operating point by using the Jacobian method. The MPC then was developed based on the linearized model where wind speed equal to 8 m/s is chosen as its operating area. The controller was tested to deal with different wind speed. A presence of a certain range of wind speed errors was included to evaluate the controller efficiency. Numerical simulation was done by using MATLAB software. The proposed controller has shown great performances when within its operating area but downgraded when moving away from its operating area. Imprecise wind speed measurement has shown a significant impact on the controller efficiency.

View