TY - JOUR
T1 - Design of Adaptive Neuro-Fuzzy Inference Control Based One-Axis Solar Tracker on Battery Charging System
AU - Abadi, Imam
AU - Oktavia Hardiana, Tiara
AU - Imron, Chairul
AU - Nur Fitriyanah, Dwi
AU - Jani, Yahya
AU - Abdullah, Kamaruddin
N1 - Publisher Copyright:
© The Authors, published by EDP Sciences, 2020.
PY - 2020/9/23
Y1 - 2020/9/23
N2 - The photovoltaic (PV) panel can produce electrical energy that is very environmentally friendly and easy to use. The use of PV panels is suitable for supplying peak loads or at night using batteries as energy storage. However, the battery needs to manage for control, and the battery can last long. The solution to battery management problems is through research about the battery charging system. The DC-DC converter used is the Single Ended Primary Inductance Converter (SEPIC) type. Voltage Control of the battery charging using Adaptive Neuro-Fuzzy Inference System (ANFIS). In the simulation of bright conditions, ANFIS controls can track the charging point set point and obtain a voltage response with a rise time of 0.0028 s, a maximum overshoot of 0.027 %, a peak time of 0.008 s, and a settling time of 0.0193 s. When charging a solar tracker, PV battery gets a 0.25 % increase compared to a fixed PV panel. PV solar tracker can follow the direction of the sun's position. The irradiation value and maximum temperature affect the input voltage and input current that enters the converter.
AB - The photovoltaic (PV) panel can produce electrical energy that is very environmentally friendly and easy to use. The use of PV panels is suitable for supplying peak loads or at night using batteries as energy storage. However, the battery needs to manage for control, and the battery can last long. The solution to battery management problems is through research about the battery charging system. The DC-DC converter used is the Single Ended Primary Inductance Converter (SEPIC) type. Voltage Control of the battery charging using Adaptive Neuro-Fuzzy Inference System (ANFIS). In the simulation of bright conditions, ANFIS controls can track the charging point set point and obtain a voltage response with a rise time of 0.0028 s, a maximum overshoot of 0.027 %, a peak time of 0.008 s, and a settling time of 0.0193 s. When charging a solar tracker, PV battery gets a 0.25 % increase compared to a fixed PV panel. PV solar tracker can follow the direction of the sun's position. The irradiation value and maximum temperature affect the input voltage and input current that enters the converter.
KW - Battery management
KW - Electrical energy
KW - Photovoltaic
KW - Renewable energy
KW - Solar tracker
UR - http://www.scopus.com/inward/record.url?scp=85092461316&partnerID=8YFLogxK
U2 - 10.1051/e3sconf/202019000015
DO - 10.1051/e3sconf/202019000015
M3 - Conference article
AN - SCOPUS:85092461316
SN - 2267-1242
VL - 190
JO - E3S Web of Conferences
JF - E3S Web of Conferences
M1 - 0000
T2 - 1st International Conference on Renewable Energy Research and Challenge, ICoRER 2019
Y2 - 12 November 2019 through 13 November 2019
ER -
