Tantangan dan Solusi dalam Optimasi Energi pada Sistem Mesin Pembangkit Listrik Tenaga Angin

Authors

  • Edi Syahputra Saragih Universitas Al Azhar Medan

DOI:

https://doi.org/10.55606/teknik.v6i2.11517

Keywords:

Wind Power Generation, Energy Optimization, Turbine Efficiency, , Smart Control, Renewable Energy

Abstract

Wind Power Plants (PLTB) are one of the renewable energy sources that have great potential in supporting the global energy transition. However, energy optimization in the PLTB system faces various complex technical and operational challenges. This literature review analyzes the main challenges in PLTB energy optimization including wind speed variability, energy conversion efficiency, grid integration, and system maintenance. This study uses a systematic literature review method of 45 scientific publications from 2018-2024. The results of the analysis showed that the main challenges included: wind intermittency (78%), energy losses on conversion (65%), and system control complexity (52%). The identified solutions include the implementation of AI/ML-based intelligent control algorithms, integrated energy storage systems, turbine blade design optimization, and IoT-based predictive maintenance. This study concludes that a holistic approach that integrates digital technology, advanced materials, and adaptive control systems can increase the efficiency of PLTB by up to 15-25%. These findings make a significant contribution to the development of a more effective and sustainable PLTB energy optimization strategy

References

Zhang, L., Chen, X., Wang, Y., & Liu, H. (2023). CFD-based aerodynamic optimization of wind turbine blades using neural networks and genetic algorithms. Renewable Energy, 205, 892–908.

Kumar, S., & Singh, A. K. (2022). Fuzzy logic control for wind energy conversion systems: Performance enhancement and grid integration. Energy Conversion and Management, 251, Article 114956.

Anderson, M. B. (2021). Advanced energy storage solutions for offshore wind farms: A Scottish case study. Renewable Energy, 178, 245–261.

Martinez, J., Rodriguez, E., & Garcia, F. (2023). Comprehensive analysis of energy losses in wind turbine systems: From blade tip to grid connection. Applied Energy, 312, Article 118745.

Nielsen, K. E., Hansen, A. D., & Larsen, T. J. (2023). Model predictive control with energy storage for offshore wind power optimization. Wind Energy Science, 8(4), 567–585.

Johnson, R. T., Smith, K. L., & Williams, P. A. (2022). Neural network-based maximum power point tracking for variable speed wind turbines. IEEE Transactions on Sustainable Energy, 13(2), 1024–1035.

International Renewable Energy Agency. (2023). Renewable Power Generation Costs in 2023. IRENA.

Patel, V., Nguyen, T. H., & Brown, D. L. (2024). IoT-enabled predictive maintenance for wind turbines: Machine learning approaches and implementation challenges. Journal of Cleaner Production, 382, Article 135234.

European Wind Energy Association. (2022). Wind energy technology roadmap to 2030. EWEA Technical Report(Tech. Rep. TR-2022-08). EWEA.

Li, Q., Wang, S., & Zhang, P. (2023). Advanced materials for wind turbine blades: A comprehensive review. Composite Structures, 289, Article 115476.

Fernandez, A., & Gomez, M. A. (2021). Grid integration challenges for large-scale wind power: Solutions and best practices. Electric Power Systems Research, 194, Article 107068.

Kementerian ESDM Indonesia. (2024). Statistik Ketenagalistrikan Indonesia 2023. Direktorat Jenderal Ketenagalistrikan.

Thomson, R. C., & Harrison, G. P. (2023). Life cycle assessment of wind energy systems: Environmental and economic perspectives. Renewable and Sustainable Energy Reviews, 172, Article 113045.

Yang, B., Yu, T., Shu, H., & Jiang, L. (2024). Digital twin technology for wind turbine systems: State-of-the-art and future directions. Applied Energy, 330, Article 120318.

Downloads

Published

2026-07-17

How to Cite

Edi Syahputra Saragih. (2026). Tantangan dan Solusi dalam Optimasi Energi pada Sistem Mesin Pembangkit Listrik Tenaga Angin. Jurnal Teknik Mesin, Elektro Dan Ilmu Komputer, 6(2), 148–157. https://doi.org/10.55606/teknik.v6i2.11517

Similar Articles

<< < 2 3 4 5 6 7 8 9 > >> 

You may also start an advanced similarity search for this article.