Optimización del rendimiento de plantas solares en azotea mediante monitoreo IoT de bajo costo: Un estudio de caso en Montería, Colombia
DOI:
https://doi.org/10.31908/19098367.3106Palabras clave:
Planta solar fotovoltaica, Monitorización IoT, Raspberry Pi Pico W, Sostenibilidad energética, Temperatura del inversor.Resumen
Respondiendo a la necesidad de soluciones sostenibles, este estudio introduce un sistema de monitoreo IoT de bajo costo para plantas solares en montadas en techo. Usando la Raspberry Pi Pico W y sensores económicos, se logra una monitorización adecuada en tiempo real. La validación, en Montería, Colombia, mostró alta precisión: correlaciones (Temperatura del Panel: 0.99, Radiación Solar: 0.98, Temperatura del Inversor: 0.83, Temperatura Ambiente: 0.96) y bajos REMC (Temperatura del Panel: 1.59°C, Radiación Solar: 86.38 W/m², Inversor: 3.56°C, Ambiente: 1.29°C), comparada con equipos comerciales de medida. Estos resultados subrayan la capacidad del sistema para optimizar el rendimiento de instalaciones solares, favoreciendo una transición energética más sostenible.
Descargas
Referencias
[1] A. M. Mitrašinović, “Photovoltaics advancements for transition from renewable to clean energy,” Energy, vol. 237, 2021, doi: 10.1016/j.energy.2021.121510.
[2] X. Fan, W. Liu, and G. Zhu, “Scientific linkage and technological innovation capabilities: international comparisons of patenting in the solar energy industry,” Scientometrics, vol. 111, no. 1, 2017, doi: 10.1007/s11192-017-2274-5.
[3] A. Ali, “Transforming Saudi Arabia’s Energy Landscape towards a Sustainable Future: Progress of Solar Photovoltaic Energy Deployment,” Sustainability (Switzerland), vol. 15, no. 10, 2023, doi: 10.3390/su15108420.
[4] M. Fabian, A. L. Vargas, M. M. Ángel, O. Padilla, P. Carlos, and V. Salgado, “Comparative experimental analysis of the annual energy production of a 72kWn photovoltaic solar power plant installed on a roof for self-consumption in the city of Monteria using PVsyst, PVGIS and SAM,” vol. 1, pp. 43–2024, 2024, doi: 10.24054/rcta.v1i43.2807.
[5] N. Ra, S. Varman, K. Antony Joseph, and A. Bhattacharjee, “Prediction of Optical Performance of Solar PV under the Impact of Natural Dust Accumulation: Machine Learning Approach,” in 2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies, GlobConHT 2023, 2023. doi: 10.1109/GlobConHT56829.2023.10087364.
[6] T. Atyia and M. Qasim, “Evaluating the Impact of Weather Conditions on the Effectiveness and Performance of PV Solar Systems and Inverters,” NTU Journal of Renewable Energy, vol. 5, no. 1, 2023, doi: 10.56286/ntujre.v5i1.551.
[7] Z. Wang, Y. Li, K. Wang, and Z. Huang, “Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis,” Renewable and Sustainable Energy Reviews, vol. 76. 2017. doi: 10.1016/j.rser.2017.03.119.
[8] H. Alici, B. Esenboga, I. Oktem, T. Demirdelen, and M. Tumay, “Designing and performance analysis of solar tracker system: A case study of Çukurova region,” in Design, Analysis and Applications of Renewable Energy Systems, 2021. doi: 10.1016/B978-0-12-824555-2.00004-6.
[9] H. Yazdani, M. Radmehr, and A. Ghorbani, “Smart component monitoring system increases the efficiency of photovoltaic plants,” Clean Energy, vol. 7, no. 2, 2023, doi: 10.1093/ce/zkac071.
[10] S. B. Sadineni, J. D. Realmuto, and R. F. Boehm, “An integrated performance monitoring and solar tracking system for utility scale PV plants,” in American Society of Mechanical Engineers, Power Division (Publication) POWER, 2011. doi: 10.1115/POWER2011-55243.
[11] C. B. Yahya, “Performance monitoring of solar photovoltaic systems using reference cells,” in Proceedings of the International Conference on Microelectronics, ICM, 2008. doi: 10.1109/ICM.2008.5393768.
[12] K. Rajeshwar Reddy, R. R. Arabelli, D. Rajababu, and K. Mahender, “Solar power generation system with IOT based monitoring and controlling using different sensors and protection devices to continuous power supply,” in IOP Conference Series: Materials Science and Engineering, 2020. doi: 10.1088/1757-899X/981/3/032017.
[13] S. Ansari, A. Ayob, M. S. Hossain Lipu, M. H. Md Saad, and A. Hussain, “A review of monitoring technologies for solar pv systems using data processing modules and transmission protocols: Progress, challenges and prospects,” Sustainability (Switzerland), vol. 13, no. 15, 2021, doi: 10.3390/su13158120.
[14] C. Belhadj-Yahya, “Performance monitoring of solar stand alone power systems,” in 2010 IEEE International Energy Conference and Exhibition, EnergyCon 2010, 2010. doi: 10.1109/ENERGYCON.2010.5771715.
[15] N. M. Kumar, K. Sudhakar, M. Samykano, and V. Jayaseelan, “On the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants,” in Procedia Computer Science, 2018. doi: 10.1016/j.procs.2018.07.087.
[16] L. Yun, Y. Bofeng, Q. Dan, and L. Fengshuo, “Research on Fault Diagnosis of Photovoltaic Array Based on Random Forest Algorithm,” in Proceedings of 2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021, 2021. doi: 10.1109/ICPECA51329.2021.9362559.
[17] D. Zhao, D. Hu, J. He, L. Zhang, and N. Chen, “Model validation of solar PV plant with hybrid data dynamic simulation based on fast-responding generator method,” in MATEC Web of Conferences, 2016. doi: 10.1051/matecconf/20166502006.
[18] D. W. Zhao et al., “Hybrid data simulation-based model validation method for solar PV plant,” in IET Conference Publications, 2015. doi: 10.1049/cp.2015.0533.
[19] V. Gupta, M. Sharma, R. Pachauri, and K. N. D. Babu, “Impact of hailstorm on the performance of PV module: a review,” Energy Sources, Part A: Recovery, Utilization and Environmental Effects, vol. 44, no. 1. 2022. doi: 10.1080/15567036.2019.1648597.
[20] V. V. Kulkarni and V. A. Kulkarni, “Performance Optimization of Photovoltaic Systems using Thermoelectric Cooling System,” in 2022 International Conference on Futuristic Technologies, INCOFT 2022, 2022. doi: 10.1109/INCOFT55651.2022.10094413.
[21] Vantage Pro2TM Accessories and DAVIS, “6450 Pyranomètre MANUAL EN DAVIS,” 2014. [Online]. Available: www.davisnet.com
[22] Maxim Integrated Products, “MAX6675 User Manual,” 2021. [Online]. Available: www.maximintegrated.com
[23] Zonzen, “Thermocouple. Ficha Tecnica,” 2019.
[24] Raspberry Pi Ltd, “User Manual Raspberry Pi Pico W,” 2023.
[25] P. By ALLDATASHEETCOM, “MLX90614 family Single and Dual Zone Infra Red Thermometer in TO-39 Features and Benefits.”
[26] Asair, “Digital Temperature & Humidity Module DHT11 User Manual,” 2019. [Online]. Available: www.aosong.com
[27] T. O. Hodson, “Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not,” Geoscientific Model Development, vol. 15, no. 14. 2022. doi: 10.5194/gmd-15-5481-2022.
[28] D. S. Cho, C. Chung, J. Kim, S. Ahn, S. Park, and H. S. Park, “Analysis on Reports of Statistical Testings for Correlation and Regression,” Korean Journal of Women Health Nursing, vol. 14, no. 3, 2008, doi: 10.4069/kjwhn.2008.14.3.213.
[29] Y. Wang and J. Mi, “Applying statistical methods to library data analysis,” Serials Librarian, vol. 76, no. 1–4, 2019, doi: 10.1080/0361526X.2019.1590774.
Descargas
Publicado
Número
Sección
Licencia
Derechos de autor 2025 Entre Ciencia e Ingeniería

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.