Nor Hanisah Baharudin
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Preferred name
Nor Hanisah Baharudin
Official Name
Nor Hanisah, Baharudin
Alternative Name
Baharudin, N. H.
Baharudin, Nor Hanisah
Main Affiliation
Scopus Author ID
49061032600
Researcher ID
EKZ-0397-2022

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Microcontroller based MPPT solar charge controller

2021-07-21 , Nor Hanisah Baharudin , Tunku Muhammad Nizar Tunku Mansur , Cong T.L. , Sobri N.F.A. , Rosnazri Ali

This paper presents the Arduino Nano microcontroller based maximum power point tracking (MPPT) solar charge controller. The optimum solar photovoltaic power is extracted using the Perturb and Observe (P&O) MPPT algorithm. Whilst there are many MPPT solar charge controllers available in the market, the Arduino Nano based MPPT solar charge controller is an attractive method for MPPT controller due to its adaptability, simple, cheap, and durable with good performance for remote areas application with cheaper cost than conventional MPPT charge controllers. This system ensures maximum power is harvested from the photovoltaic panel and capable to charge the battery as well as maintain the battery health condition. This will increase the battery lifespan and increases the efficiency of the photovoltaic panel under varying solar insolations. In this paper, the Perturb and Observe (P&O) algorithm method is developed by using an Arduino Nano based MPPT controller for the photovoltaic generation system. The test result has shown the performance of the proposed controller is capable of tracking the photovoltaic maximum power point and extracting the optimum available power whilst charging the battery in the healthy mode.

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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.

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MPPT charge controller using fuzzy logic for battery integrated with solar photovoltaic system

2025-05 , Kumuthawathe Ananda-Rao , Afifah Shuhada Rosmi , Steven Taniselass , Nor Hanisah Baharudin , Leow Wai Zhe

In comparison to other Renewable Energy (RE) resources, solar energy has become the most prominent and prospective source for generating electricity, substituting conventional sources. However, solar Photovoltaic (PV) energy production is dependent on solar irradiance and cell temperature. By implementing the Maximum Power Point Tracking (MPPT) algorithm, it is achievable to maximize the power from solar PV. In spite of this, there is still a slower convergence rate, a significant fluctuation around Maximum Power Point (MPP), and a drift issue caused by rapid irradiance variations in solar PV. In order to prevent oscillation and attain a steady state and continuous output of the PV module, a Fuzzy Logic (FL)-based MPPT has been designed in this work. With the buck converter as the DC-DC converter and the lead acid battery as the input, the Perturb & Observe (P&O) MPPT method is selected. The overall design will be developed using Matlab Simulink, and the efficiency of the FL-MPPT charge controller will be evaluated under constant and step irradiance. Additionally, the battery's State of Charge (SOC) will be monitored to prevent overcharging and discharge. In addition, the effectiveness of the controller will be evaluated with and without the MPPT method. On the basis of simulation results obtained from constant and step irradiance levels, the FL-MPPT charge controller with the P&O algorithm and the lead acid battery as the load was able to maintain maximum system efficiency while extending battery life. The FL-MPPT charge controller obtained about 96% efficiency for both irradiance profiles, whereas the system without the FL-MPPT algorithm only achieved 42% efficiency.

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Voltage Stability Prediction In Power Systems Using Modified Artificial Neural Network

2022-01-01 , Abdullah A.M. , Rosnazri Ali , Yaacob S.B. , Tunku Muhammad Nizar Tunku Mansur , Nor Hanisah Baharudin

This paper presents the indicator system status in the distribution network by using the technique voltage stability index with the artificial neural network to predict the power system. Voltage stability is an indicator from value index zero (0) until one (1). The value index zero is no loading in the system bus, where else one is maximum loading in system buses. IEEE 30 bus practical system was used to test and indicator to predict the power system. Using MATLAB to program and develop Artificial Neural Networks (ANN) in distribution networks. The voltage stability indicator was trained by application ANN to predict each bus system's load status. Therefore, the voltage instability will be early to be known by using the prediction ANN. The information stability index is very important in the power system because it helps to solve the major problems in the distribution system power system.

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Performance analysis of smart lighting control system for sustainable campus operation

2021-01-01 , Tunku Muhammad Nizar Tunku Mansur , Rosnazri Ali , Nor Hanisah Baharudin , Kumuthawathe Ananda-Rao

Global warming is a growing issue today due to the concerns of carbon emissions to the environment. Meanwhile, learning institutions such as university could play a significant role in promoting energy conservation and sustainable campus operations. The objective of this paper is to highlight the performance of smart lighting control system for restrooms where the project has been carried out at the Faculty of Electronic Engineering Technology, Universiti Malaysia Perlis. The methodology processes include the initial study and field measurement of the energy consumption for lighting system during pre-retrofit condition, design, and development of the lighting control system and lastly analysis of the designed system in post-retrofit condition after installation. On the overall, 58 motion sensors have been installed at 30 restrooms where the result shows that in average 77.5% of reduction in energy consumption per day for each restroom. This situation has given tremendous benefits to the university operation where the university could save 9377 kWh per year and reduced RM 3423 from electricity bill per annum. In addition, this project also contributes to the environmental sustainability where the amount of electrical energy that has been successfully reduced is equivalent to 6508 kg of CO2 avoidance to the environment.

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Design of MPPT charge controller using zeta converter for battery integrated with solar Photovoltaic (PV) system

2020-01-07 , Kumuthawathe Ananda-Rao , Matar Y. , Nor Hanisah Baharudin , Mohd Alif Ismail , Muiez Abdullah A.

In this work, the advantage of using Maximum Power Point Tracking (MPPT) algorithm in solar Photovoltaic (PV) system was investigated. By simulation, the performance and efficiency of the system with and without the tracking algorithm was analyzed. By using MATLAB's SimPower System block set, a model compromised of KC130TM solar panel powering a Zeta converter controlled by MPPT algorithm driving a lead acid battery as a load was designed. The main objective was to track the Maximum Power Point (MPP) of the solar PV module by modulating the zeta converter's duty cycle, thereby, optimizing the power output of the panel. The Perturb and Observe (P&O) algorithm preformed with higher overall efficiency compared with the system without MPPT. Additionally, the tracking algorithm was able to track the MPP quickly. The analysis of the algorithm led to a greater understanding of where the inefficiencies of this type of system are located, allowing improvement in future work on this field.

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Hybrid conjugate gradient backpropagation of GCPV based DSTATCOM for power conditioning

2025-04 , Nor Hanisah Baharudin , Tunku Muhammad Nizar Tunku Mansur , Rosnazri Ali

This paper studies the performance of a hybrid conjugate gradient backpropagation (HCGBP) grid-connected solar photovoltaic (GCPV) based DSTATCOM. This paper proposes a hybrid control algorithm of instantaneous reactive power theory and conjugate gradient backpropagation neural network for an application of a grid-connected solar PV (GCPV) based DSTATCOM for three-phase three-wire system. The fundamental weighted value of active power components of load currents, which is necessary for estimating reference source currents, is extracted using a conjugate gradient backpropagation control algorithm. The performance of the proposed control algorithm has reduced the THD of the line current up to 1.32%. It is proven that HCGBP has better efficiency, faster response and easy to implement. The steady-state performance of the three-phase GCPV-DSTATCOM under non-linear load has been analysed through simulation and Hardware-in-loop (HIL) simulation based on real time DSP system using Texas Instrument TI C2000 32-bit microcontroller in MATLAB/Simulink. Furthermore, the simulation results have shown that the THD of the line current at the PCC has reduced less than 8%, according to the IEEE standard 519:2014.

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Control of a multi-functional grid-connected solar PV system using instantaneous reactive power (PQ) theory for current harmonic alleviations

2020-01-07 , Nor Hanisah Baharudin , Tunku Muhammad Nizar Tunku Mansur , Rosnazri Ali , Azahid W.N.A. , Kumuthawathe Ananda-Rao , Muhammad Irwanto Misrun , Abdullah A.M. , Surina Mat Suboh

In recent years, the advance usages of non-linear loads have led to the serious power quality problem in the distribution system. Non-linear load will inject the current harmonics and cause power quality problem at Point of Common Coupling (PCC). This problem can be improved by using power filter. Power filter can be divided into passive power filter and active power filter. Passive filter is an appropriate solution to solve power quality problem in term of harmonic mitigation due to a simple circuit, low cost and less energy requirement. However, active power filter (APF) is more suitable due to better performance to solve power quality problem for current harmonics issue. This paper focuses in designing the application of a multi-functional grid-connected solar PV system integrated with DSTATCOM by using Instantaneous Reactive Power (PQ) theory controller to mitigate the current harmonics injected by non-linear load at the distribution system. MATLAB/SIMULINK software is used to simulate the performance of the multi-functional GCPV based SAPF according to IEEE Standard 519:2014 which THD of the line current at the Pont of Common Coupling (PCC) should be less than 8%.

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Photovoltaic powered DC-DC boost converter based on PID controller for battery charging system

2020-01-07 , Muhammad Irwanto Misrun , Leow W.Z. , Ismail B. , Nor Hanisah Baharudin , Juliangga R. , Alam H. , Masri M.

The input voltage of battery charging system is always above the battery nominal voltage and it should be remained constant. But it depends on the type of input voltage sources. A battery charged directly by photovoltaic (PV) module as the input voltage source can cause the output voltage of PV module or the input voltage of battery charging system can fluctuate, because the output voltage of PV module depends on the solar irradiance. This problem can be solved by installing DC-DC boost converter between the PV module and battery. This paper presents a DC-DC boost converter based on PID controller for battery charging system. It is designed for the input voltage of 12V and output voltage of 14.7V system because it is applied to charge a 12 V, 7 Ah lead acid battery. Based on the simulation result of battery charging system shows that the output voltage of DC-DC boost converter can be remain around 14.7 V. It is due to the PID controller can damp the voltage oscillation and remain its steady state voltage. The time needed by the DC-DC boost converter to charge the battery in the fully charging condition is 1 hour: 3 minutes: 37seconds.

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Design and performance analysis of fuzzy logic controller for solar photovoltaic system

2025-06 , Kumuthawathe Ananda-Rao , Steven Taniselass , Afifah Shuhada Rosmi , Aimi Salihah Abdul Nasir , Nor Hanisah Baharudin , Indra Nisja

This study presents a Fuzzy Logic Controller (FLC)-based Maximum Power Point Tracking (MPPT) system for solar Photovoltaic (PV) setups, integrating PV panels, a boost converter, and battery storage. While FLC is known for its robustness in PV systems, challenges in battery charging and discharging efficiency can affect performance. The research addresses these challenges by optimizing battery charging, preventing overcharging, and enhancing overall system efficiency. The FLC MPPT system is designed to regulate the battery's State of Charge (SOC) while evaluating system performance under varying solar irradiance and temperature conditions. The system is modeled and simulated using MATLAB/Simulink, incorporating the PV system, MPPT algorithm, and models for the PV module and boost converter. System efficiency is assessed under different scenarios, with results showing 97.92% efficiency under Standard Test Conditions (STC) at 1000 W/m² and 25°C. Additionally, mean efficiencies of 97.13% and 96.13% are observed under varying irradiance and temperature, demonstrating the effectiveness of the FLC MPPT in regulating output. The system also extends battery life by optimizing power transfer between the PV module, boost converter, and battery, ensuring regulated SOC.

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