Rancang Bangun Prototipe Pembangkit Listrik Tenaga Gelombang Laut (PLTGL) Skala Laboratorium

  • Muhammad Khaisar Wirawan Program Studi Teknik Kelautan, Fakultas Pembangunan Berkelanjutan, Institut Teknologi Kalimantan
  • Luh Putri Adnyani Program Studi Teknik Kelautan, Fakultas Pembangunan Berkelanjutan, Institut Teknologi Kalimantan
  • Febryan Melanchton Program Studi Teknik Kelautan, Fakultas Pembangunan Berkelanjutan, Institut Teknologi Kalimantan
  • Nurmawati Program Studi Teknik Kelautan, Fakultas Pembangunan Berkelanjutan, Institut Teknologi Kalimantan
  • Thorikul Huda Program Studi Teknik Kelautan, Fakultas Pembangunan Berkelanjutan, Institut Teknologi Kalimantan

Keywords

Wave Energy, Wave Energy Power Plant (PLTGL), Wave Flume, Linear Regression, MAPE

Abstract

Wave energy is one of the renewable energy resources with significant potential for development in Indonesia as an archipelagic country. This study aimed to design and develop a laboratory-scale Wave Energy Power Plant (PLTGL) prototype and analyze the effects of wave height and wave period variations on the generated electrical output. The prototype consisted of a horizontal turbine, a DC generator, and a real-time monitoring system based on Arduino Nano and ESP8266. Experimental tests were conducted in a wave flume using wave heights of 10, 11, 13, and 15 cm and wave periods of 0.67, 0.90, and 1.00 s. The observed parameters included voltage, current, and electrical power. The results demonstrated that variations in wave height and wave period affected the electrical output of the prototype. The best performance was achieved at a wave height of 13 cm and a wave period of 0.90 s, producing a voltage of 0.71 V, a current of 211 mA, and a power output of 0.61 W. Validation of 21 empirical models indicated that 13 models were classified as highly accurate, with an average Mean Absolute Percentage Error (MAPE) of 16.83%, while the best-performing model achieved a coefficient of determination (R²) of 0.9806 and a MAPE of 0.0839%. The developed prototype successfully converted wave energy into electrical energy and produced empirical models with good predictive accuracy for estimating electrical output based on wave characteristics

References

Alexander, S. (2019). Electric Machinery Fundamentals. McGraw-Hill Education.

Aminuddin, J., Abdullatif, R. F., & Wihantoro. (2015). Persamaan Energi untuk Perhitungan dan Pemetaan Area yang Berpotensi untuk Pengembangan Pembangkit Listrik Tenaga Gelombang Laut. Jurnal Kelautan, 8(2), 89–96.

Boscaino, V., Cipriani, G., Di Dio, V., Franzitta, V., & Trapanense, M. (2017). Experimental Test and Simulations on a Linear Generator-Based Prototype of a Wave Energy Conversion System Designed with a Reliability-Oriented Approach. Sustainability, 9(1), 98.

Bouhrim, H., El Marjani, A., Nechad, R., & Hajjout, I. (2024). Ocean Wave Energy Conversion: A Review. Renewable and Sustainable Energy Reviews, 198, 114389.

Faizal, M., Ahmed, M. R., & Lee, Y. H. (2010). On Utilizing the Orbital Motion in Water Waves to Drive a Savonius Rotor. Renewable Energy, 35(1), 164–169.

Falcão, A. F. O. (2010). Wave Energy Utilization: A Review of the Technologies. Renewable and Sustainable Energy Reviews, 14(3), 899–918.

Fauzan, A., dkk. (2024). Monitoring Sistem Kelistrikan Tiga Fasa Berbasis IoT dengan Sensor. Jurnal Teknologi Elektro, 13(1), 24–29.

Halder, P., Takebe, H., Pawitan, K., Fujita, J., & Misumi, S. (2020). Turbine Characteristics of Wave Energy Conversion Device for Extraction Power Using Breaking Waves. Ocean Engineering, 217, 107907.

Hyndman, R. J., & Koehler, A. B. (2006). Another Look at Measures of Forecast Accuracy. International Journal of Forecasting, 22(4), 679–688. International Energy Agency (IEA). (2024). World Energy Outlook 2024. International Energy Agency.

Islam, M. M., Hasanuzzaman, M., Pandey, A. K., & Rahim, N. A. (2020). Modern Energy Conversion Technologies. Dalam: Energy for Sustainable Development. Elsevier, pp.21–45.

Izzinnahdi, A., Murdiantoro, R. A., & Armin, E. U. (2021). Sistem Pemantauan Kondisi Air Hidroponik Berbasis Internet of Things Menggunakan NodeMCU ESP8266. Jurnal Teknologi Informasi dan Komunikasi, 8(2), 56–63.

José, J., Moreno, M., Pol, A. P., Abad, A. S., & Blasco, B. C. (2013). Using the R-MAPE Index as a Resistant Measure of Forecast Accuracy. Psicothema, 25(4), 500–506.

Mintarso, C. S. J. (2010). Rancang Bangun Pembangkit Listrik Tenaga Ombak Naga Listrik Skala Laboratorium. Wave: Jurnal Ilmiah Teknologi Maritim, 3(1), 33–36.

Ringwood, J. V. (2021). Rotors for Wave Energy Conversion: Practice and Possibilities. IET Renewable Power Generation, 15(14), 3091–3108.

Rusu, E., & Onea, F. (2018). A Review of the Technologies for Wave Energy Extraction. Clean Energy, 2(1), 10–19.

Starbuck, A. (2023). The Fundamentals of People Analytics: With Applications in R. Springer.

2026-10-05