Steven Taniselass
Thumbnail Image
Preferred name
Steven Taniselass
Official Name
Steven, Taniselass
Alternative Name
Taniselass, S.
Taniselas, S.
Taniselass, Steven
Main Affiliation
Scopus Author ID
36998664900
Researcher ID
EAA-5755-2022

Research Output

Filters

3 1
3
Reset filters

Settings
Now showing 1 - 3 of 3
Thumbnail Image
Publication

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.

View
No Thumbnail Available
Publication

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.

View
No Thumbnail Available
Publication

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.

View