Kumuthawathe Ananda-Rao
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Preferred name
Kumuthawathe Ananda-Rao
Official Name
Ananda-Rao, Kumuthawathe
Alternative Name
Ananda-Rao, K.
Anandarao, K
Main Affiliation
Scopus Author ID
57195510026
Researcher ID
DXC-7645-2022

Research Output

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Battery energy storage system assessment in a designed battery controller for load leveling and peak shaving applications

2017-07-01 , Kumuthawathe Ananda-Rao , Rosnazri Ali , Steven Taniselass

This paper presents an assessment of three types of battery in a designed battery controller for a battery energy storage system (BESS) integrated with a solar photovoltaic system for load leveling and peak shaving applications. Three types of battery - lead acid, lithium ion, and nickel metal hydride - are discussed in detail and assessed in this work, focusing on small-scale integration. The controller was designed using Matlab Simulink to monitor consumer load demand, control the charging and discharging process of the BESS, and regulate while fulfilling the load demand, in addition to prolonging the BESS lifetime. From the simulation results, the nickel metal hydride battery is the best option for development of a battery controller. It achieved an average 37.45% leveled load profile and a 35.75% reduction of the load peak. However, the lead acid battery is still the dominant choice among consumers, in spite of average performance, because it has the best cost performance.

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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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Integrating deep transfer learning and image enhancement for enhancing defective photovoltaic cells classification in electroluminescence images

2025-06 , Aimi Salihah Abdul Nasir , Mohammad Faridun Naim Tajuddin , Kumuthawathe Ananda-Rao , Hanim Suraya Mohd Mokhtar , Muhammad Hafeez Abdul Nasir

The rapid growth of photovoltaic (PV) systems has highlighted the need for efficient and reliable defect detection to maintain system performance. Electroluminescence (EL) imaging has emerged as a promising technique for identifying defects in PV cells; however, challenges remain in accurately classifying defects due to the variability in image quality and the complex nature of the defects. Existing studies often focus on single image enhancement techniques or fail to comprehensively compare the performance of various image enhancement methods across different deep learning (DL) models. This research addresses these gaps by proposing an in-depth analysis of the impact of multiple image enhancement techniques on defect detection performance, using various deep learning models of low, medium, and high complexity. The results demonstrate that mid-complexity models, especially DarkNet-53, achieve the highest performance with an accuracy of 94.55% after MSR2 enhancement. DarkNet-53 consistently outperformed both lower-complexity models and higher-complexity models in terms of accuracy, precision, and F1-score. The findings highlight that medium-depth models, enhanced with MSR2, offer the most reliable results for photovoltaic defect detection, demonstrating a significant improvement over other models in terms of accuracy and efficiency. This research provides valuable insights for optimizing defect detection systems in photovoltaic applications, emphasizing the importance of both model complexity and image enhancement techniques for robust performance.

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Improving the performance of solar panels by the used of dual axis solar tracking system with mirror reflection

2020-01-07 , Mohd Alif Ismail , Ramanathan K.A. , Muhd Hafizi Idris , Kumuthawathe Ananda-Rao , Mazwin Mazlan , Nur Fairuz Mohamed Yusof

This work proposes the dual axis solar tracker with mirror reflection for optimum output of solar panel by using arduino unoR3 as the control unit. The objectives of this work are to track and optimize the maximum output power of the solar panel by designing and developing a dual axis solar tracker with mirror reflection. The system includes a 10 watt solar panel, an arduino unoR3 and a customized mechanical body to carry the solar panel. This system will track and detect the angle of the sun to locate the surface of solar panel at the position and the angle where it can get maximum amount of energy. The sensors will detect the position of the sun and servo motors act as free moving neck to make it easier to move freely depending on the angle detected. The Light Depending Resistor (LDR) will be used in tracking system. These LDR will detect the existence of sunlight and therefore the mechanical hardware will move horizontal and vertical axis depending on the value of LDR detected to follow the angular degree of sun in order to get maximum and best result of absorbing energy. The final result obtained from dual axis solar tracker showed that the output power has been maximized compared to stationary panel. Based on the experimental result, it show that the designed system successful improve the performance of the solar panel.

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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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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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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.

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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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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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A Potential Controller for Smart Electrical Energy Management System

2021-06-11 , Kumuthawathe Ananda-Rao , Mohd Alif Ismail , Afifah Shuhada Rosmi , Leow Wai Zhe , Surina Mat Suboh , Muhammad Izuan Fahmi Romli , Abdullah A.M.

Integrated energy utilization has been recognized as a productive way towards better energy management, besides increasing Renewable Energy (RE) penetration. Thus, the combination of RE integrated with the Battery Energy Storage System (BESS) has been recognized as the primary solution where it is necessary to have a controller to interface the system efficiently. Hence, a smart electrical energy management system controller is designed and developed based on load leveling and peak shaving applications for real-time AC power management in this work. The main function of the controller is to continuously monitor and maintain the load demand and to produce a leveled or shaved load profile that will be seen at the grid network by controlling the battery operation. The testing results concluded that the controller able to perform both the energy applications. Overall, a dual function controller based on energy applications to maintain consumer load demand usage more securely and reliably, so that the utility bill is reduced and the battery lifetime is prolonged simultaneously is achieved in this work.

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