Sistem Pembersih Panel Surya Otomatis Berbasis Internet of Things (IoT) Menggunakan ESP32
DOI:
https://doi.org/10.21009/JEVET.0082.02Keywords:
electrical energi, new renewable energy, solar panel cleanerAbstract
Abstrak
Penelitian ini bertujuan untuk merancang sebuah alat yang dapat membersihkan permukaan panel surya secara otomatis. Penelitian ini dilakukan dengan menggunakan metode rekayasa teknik dengan jenis rekayasa maju (Forward Engineering). Proses pemindaian kekotoran permukaan panel surya menggunakan sensor TCS3200 dengan memanfaatkan frekuensi warna red (R), green (G), dan blue (B) serta Sensor HC-SR04 digunakan untuk mengukur volume air yang tersedia pada ember penampungan air. Untuk memproses hasil pemindaian, digunakan mikrokontroler ESP32. Teknologi IoT (Internet of Things) digunakan untuk menghubungkan ESP32 dengan Blynk, yang memungkinkan alat untuk mengirimkan notifikasi atau data dari perangkat fisik ke platform cloud. Dalam penelitian ini, setiap komponen dilakukan pengujian yang bertujuan untuk memastikan kinerja yang optimal dalam sistem pemantauan dan pembersihan panel surya berbasis IoT. Berdasarkan hasil pengujian volume air memiliki rata-rata selisih akurasi 3,753%. Pada pengujian sensor warna berdasarkan kondisi awal permukaan panel surya dan kondisi permukaan panel surya setelah dibersihkan, rata-rata selisih akurasinya adalah 1,6%. Berdasarkan hal tersebut alat yang dibuat dapat berfungsi dengan baik dalam membersihkan kotoran pada permukaan panel surya.
Abstract
This study aims to design a tool that can clean the surface of solar panels automatically. This research was conducted using engineering methods with the type of forward engineering. The process of scanning dirt on the surface of the solar panel uses the TCS3200 sensor by utilizing the red (R), green (G), and blue (B) color frequencies and the HC-SR04 sensor is used to measure the volume of water available in the water storage bucket. To process the scan results, the ESP32 microcontroller is used. IoT (Internet of Things) technology is used to connect the ESP32 with Blynk, which allows the tool to send notifications or data from physical devices to the cloud platform. In this study, each component was tested with the aim of ensuring optimal performance in the IoT-based solar panel monitoring and cleaning system. Based on the results of the water volume test, the average accuracy difference is 3.753%. In the color sensor test based on the initial condition of the solar panel surface and the condition of the solar panel surface after cleaning, the average accuracy difference is 1.6%. Based on this, the tool made can function well in cleaning dirt on the surface of the solar panel.
References
Evstatiev, B. I., Trifonov, D. T., Gabrovska-Evstatieva, K. G., Valov, N. P., & Mihailov, N. P. (2024). PV Module Soiling Detection Using Visible Spectrum Imaging and Machine Learning. Energies, 17(20), 5238–5238. https://doi.org/10.3390/en17205238
Fitriana, I., Hadiyanto, H., Warsito, B., Himawan, E., & Santosa, J. (2024). The Optimization of Power Generation Mix To Achieve Net Zero Emission Pathway in Indonesia Without Specific Time Target. International Journal of Sustainable Energy Planning and Management, 41, 5–19. https://doi.org/10.54337/ijsepm.8263
Grzych, G., Gernez, E., Plasse, L., Deheul, S., Niguet, J., Bennis, A., Tard, C., Douillard, C., Scliffet, D., Bossaert, C., Girot, M., Dobbelaere, D., & Diesnis, R. (2024). B-283 Biological Consequences of Nitrous Oxide Abuse: Insights from Targeted Metabolomics Investigation. Clinical Chemistry, 70(Supplement_1). https://doi.org/10.1093/clinchem/hvae106.640
Jin, A. S., & Sanders, K. T. (2024). Characterizing residential sector load curves from smart meter datasets. Applied Energy, 366, 123316. https://doi.org/10.1016/j.apenergy.2024.123316
Krasanakis, E., & Symeonidis, A. (2024). Forward-Oriented Programming: A meta-DSL for fast development of component libraries. Information and Software Technology, 171, 107474. https://doi.org/10.1016/j.infsof.2024.107474
Lee, Y. H. (2024). Beyond the Shockley-Queisser limit: Exploring new frontiers in solar energy harvest. Science, 383(6686). https://doi.org/10.1126/science.ado4308
Liao, X., Bresciani, S., Troise, C., Bukhari, W. A. A., & Bukhari, A. A. A. (2025). How Solar, Wind, and Biomass Energy Create Sustainable Pathways Towards Green Economic Growth? Insights From the Top Five Global Renewable Energy Economies. Sustainable Development. https://doi.org/10.1002/sd.3345
Lin, S., Zhang, T., Yang, H., & Li, Y. (2023). Progress and Perspectives of Solar Cells: A Critical Review. Energy & Fuels, 38(2), 761–788. https://doi.org/10.1021/acs.energyfuels.3c02908
Marquez, R., Ovalles, C., Lopez-Linares, F., Wang, W., Robinson, P., & Reynolds, M. A. (2024). Perspective from the ACS Energy & Fuels Industry Committee toward the Transition to Sustainable Energy Sources. Energy & Fuels. https://doi.org/10.1021/acs.energyfuels.4c05805
Martinez-Marroquin, E., Senadji, B., Male, S., & Wood, L. (2024). Embedding human and social aspects in engineering education. European Journal of Engineering Education, 1–18. https://doi.org/10.1080/03043797.2024.2430532
Ochoa-Correa, D., Arévalo, P., Villa-Ávila, E., Espinoza, J. L., & Jurado, F. (2024). Feasible Solutions for Low-Carbon Thermal Electricity Generation and Utilization in Oil-Rich Developing Countries: A Literature Review. Fire, 7(10), 344–344. https://doi.org/10.3390/fire7100344
Ramadhan, R., Mon, M. T., Tangparitkul, S., Tansuchat, R., & Agustin, D. A. (2024). Carbon capture, utilization, and storage in Indonesia: An update on storage capacity, current status, economic viability, and policy. Energy Geoscience, 5(4), 100335. https://doi.org/10.1016/j.engeos.2024.100335
Ramly, Z. T. A., Ishak, M. Y., Abdullah, A. M., Ismail, M., Abdullah, S., & Mansor, A. A. (2025). Investigating the Effectiveness of Coal-Fired Power Plant Operations: Management, Technical and Air Pollution Aspects. Emerging Science Journal, 9(1), 86–113. https://doi.org/10.28991/esj-2025-09-01-06
Rashak, Z. M., Hassan, K. H., Al-Fartoos, M., Chanchangi, Y., Mohammadi, M. H., & Tahir, A. A. (2024). Assessing Environmental Dynamics and Angular Influence on PV Soiling: Employing ANFIS to Mitigate Power Losses. Energies, 17(23), 5921. https://doi.org/10.3390/en17235921
Wang, Q., Huang, R., & Li, R. (2024). Renewable energy and sustainable development goals: Insights from latent dirichlet allocation thematic and bibliometric analysis. Sustainable Development, 32(6). https://doi.org/10.1002/sd.3027
