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Vol. 7, No. 3, August 2022

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High Accuracy Electric Water Heater using Adaptive Neuro-Fuzzy Inference System (ANFIS)

https://doi.org/10.22219/kinetik.v7i3.1453
Indhana Sudiharto
Politeknik Elektronika Negeri Surabaya
Farid Dwi Murdianto
Politeknik Elektronika Negeri Surabaya
Anang Budikarso
Politeknik Elektronika Negeri Surabaya
Putri Taufika
Politeknik Elektronika Negeri Surabaya

Corresponding Author(s) : Putri Taufika

putritaufika1805@pe.student.pens.ac.id

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 7, No. 3, August 2022

Abstract

Nowadays, water heater is a common household appliance. Water heater can be divided into three types, based on fuel sources: gas, diesel, and electric. Electric water heater is the most common due to its ease of use. The problems that often occur on electric water heater are over-temperature due to user error in setting up the thermostat and inaccurate readings caused by a conventional system control. These problems will cause a surge in power consumption. Over-temperature and conventional control inaccuracies can be overcome using the Artificial Intelligence (AI) control algorithm in the form of an adaptive neuro-fuzzy inference system (ANFIS). The proposed algorithm acts as a control by maintaining the stability of the temperature to obtain more accurate results. An accurate temperature reading can lower power consumption in electric water heater. This study tries to simulate Electric Water Heater temperature control using the ANFIS algorithm until stable readings can be achieved in all temperature settings. Results from disturbance tests in the form of external condition that causes sudden temperature change show that the system can maintain stability with an average error margin of 0.045% and the rate of accuracy of 99.955%.

Keywords

Adaptive Neuro-Fuzzy Inference System Electric Water Heater (EWH) Temperature Control
Sudiharto, I., Dwi Murdianto, F., Budikarso, A., & Taufika, P. (2022). High Accuracy Electric Water Heater using Adaptive Neuro-Fuzzy Inference System (ANFIS). Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 7(3), 273-288. https://doi.org/10.22219/kinetik.v7i3.1453
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