Journal of Mechatronics and Artificial Intelligence
Vol. 3 No. 1 (2026): JMAI: June 2026

Savonius Turbine Suitability Analysis Based on Low Wind Speed Characteristics

Adi Nugraha (Sultan Ageng Tirtayasa University)
Fajar Ramadhan (Sultan Ageng Tirtayasa University)
Muhammad Fathurrizki (Sultan Ageng Tirtayasa University)
Reza Abdillah Prastian (Sultan Ageng Tirtayasa University)
Muhamad Khadavy (Sultan Ageng Tirtayasa University)
Muhammad Ilham Daifullah (Sultan Ageng Tirtayasa University)



Article Info

Publish Date
30 Jun 2026

Abstract

Wind energy is one of the renewable energy sources with significant potential to be developed as an environmentally friendly power generation alternative. However, the selection of wind turbine types must be adjusted to the wind speed characteristics of the implementation area to ensure optimal performance. This study aims to analyze the suitability of the Savonius turbine based on low wind speed characteristics. The research was conducted at the Faculty of Engineering, Universitas Sultan Ageng Tirtayasa (FT UNTIRTA), by measuring wind speed at three different locations using an anemometer. The measurement locations included an open sports field, a building rooftop, and a green open space area. The measurement results showed that the wind speed ranged from 1.5 m/s to 3.2 m/s, categorized as low wind speed below 4 m/s. The obtained data were analyzed and compared with the wind turbine performance characteristic graph based on the relationship between power coefficient (Cp) and turbine tip speed ratio (TSR). The analysis results indicate that the Savonius turbine has the most suitable characteristics for low wind speed conditions because it can operate at low TSR values and has good self-starting capability and high starting torque. In addition, the Savonius turbine offers simple construction, ease of manufacturing, and the ability to operate under varying wind directions. Based on the research results, the Savonius turbine is recommended as an alternative small-scale wind power generation system for areas with low wind speed characteristics.

Copyrights © 2026






Journal Info

Abbrev

jmai

Publisher

Subject

Description

The Journal of Mechatronics and Artificial Intelligence (JMAI) (E-ISSN 3048-4227 P-ISSN 3062-729X) serves as a platform for disseminating scholarly research related to the fields of mechatronics and artificial intelligence, as well as related sub-disciplines. We extend an invitation to researchers, ...