Energy Sustainability in the Usumacinta River: An Energy Management System for a Microgrid in Boca del Cerro, Tabasco.
Saved in:
| Title: | Energy Sustainability in the Usumacinta River: An Energy Management System for a Microgrid in Boca del Cerro, Tabasco. |
|---|---|
| Authors: | Sosa, David Abraham Uribe1 (AUTHOR), Rivera, Víctor Manuel Ramírez1,2 (AUTHOR), Pinto, Víctor Darío Cuervo2,3 (AUTHOR), Córdoba, Diego Langarica1,3 (AUTHOR) |
| Source: | Energies (19961073). May2026, Vol. 19 Issue 10, p2390. 23p. |
| Subject Terms: | *Microgrids, *Renewable energy source management, *Energy industry forecasting, *Photovoltaic power systems, *Hydraulic turbines, *Clean energy, *Recurrent neural networks, *Fuzzy control systems |
| Geographic Terms: | Mexico, Tabasco (Mexico : State) |
| Abstract: | The growing energy demand in rural areas such as the ejido Boca del Cerro, located in Tenosique, Tabasco (Mexico), near the Usumacinta River, calls for sustainable energy solutions such as microgrids. This study proposes an energy management system combining renewable energy forecasting and fuzzy control for a simulated small autonomous rural microgrid scenario designed to supply a fixed priority load of 5 kW and a variable flexible load ranging from 1 to 10 kW. Three LSTM architectures (vanilla, stacked, and bidirectional) are compared for predicting solar irradiance, wind speed, and river flow. The vanilla model is optimized using Hyperband to improve prediction accuracy, particularly for flow rate, which is rarely addressed in similar studies. Forecasts feed into models of photovoltaic, wind, and hydro systems within the microgrid. Energy dispatch is managed through fuzzy logic control. The fuzzy controller supports load prioritization, battery charge/discharge management, and surplus energy redirection to an absorbing load. The final vanilla LSTM achieved RMSE values of 25.741, 0.302, and 12.644 for solar irradiance, wind speed, and river flow, respectively, with NSE values above 0.949 in all cases. These results indicate high forecasting accuracy for solar irradiance and river flow, with limited improvement for wind speed. Overall, the proposed EMS enables effective energy flow management, while the integration of hydrokinetic turbines with AI-based forecasting represents a novel contribution. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | The growing energy demand in rural areas such as the ejido Boca del Cerro, located in Tenosique, Tabasco (Mexico), near the Usumacinta River, calls for sustainable energy solutions such as microgrids. This study proposes an energy management system combining renewable energy forecasting and fuzzy control for a simulated small autonomous rural microgrid scenario designed to supply a fixed priority load of 5 kW and a variable flexible load ranging from 1 to 10 kW. Three LSTM architectures (vanilla, stacked, and bidirectional) are compared for predicting solar irradiance, wind speed, and river flow. The vanilla model is optimized using Hyperband to improve prediction accuracy, particularly for flow rate, which is rarely addressed in similar studies. Forecasts feed into models of photovoltaic, wind, and hydro systems within the microgrid. Energy dispatch is managed through fuzzy logic control. The fuzzy controller supports load prioritization, battery charge/discharge management, and surplus energy redirection to an absorbing load. The final vanilla LSTM achieved RMSE values of 25.741, 0.302, and 12.644 for solar irradiance, wind speed, and river flow, respectively, with NSE values above 0.949 in all cases. These results indicate high forecasting accuracy for solar irradiance and river flow, with limited improvement for wind speed. Overall, the proposed EMS enables effective energy flow management, while the integration of hydrokinetic turbines with AI-based forecasting represents a novel contribution. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 19961073 |
| DOI: | 10.3390/en19102390 |
