Author
Listed:
- Daniel Lima Lemes
(Headquarters Campus, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil)
- Matheus Mello Jacques
(Headquarters Campus, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil)
- Natalia Bastos Sousa
(Headquarters Campus, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil)
- Daniel Pinheiro Bernardon
(Headquarters Campus, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil)
- Mauricio Sperandio
(Headquarters Campus, Federal University of Santa Maria, Santa Maria 97105-900, RS, Brazil)
- Juliano Andrade Silva
(CPFL Energia, Campinas 13088-900, SP, Brazil)
- Lucas M. Chiara
(CPFL Energia, Campinas 13088-900, SP, Brazil)
- Martin Wolter
(Institute for Electrical Energy Systems (IESY), Otto-von-Guericke University Magdeburg (OVGU), 39106 Magdeburg, Sachsen-Anhalt, Germany)
Abstract
On average, 70% of the world’s freshwater is used in agriculture, with farmers transitioning to electrical irrigation systems to increase productivity, reduce climate uncertainties, and decrease water consumption. In Brazil, where agriculture is a significant part of the economy, this transition has reached record levels over the last decade, further increasing the impact of energy consumption. This paper presents a methodology that utilizes the U-Net model to detect flooded rice fields using Sentinel-2 satellite images and estimates the electrical energy consumption required to pump water for this irrigation. The proposed approach involves grouping the detected flooded areas using k-means clustering with the electricity customers’ geographical coordinates, provided by the Power Distribution Company. The methodology was evaluated in a dataset of satellite images from southern Brazil, and the results demonstrate the potential of using U-Net models to identify rice fields. Furthermore, comparing the estimated electrical energy consumption required for irrigation in each cluster with the billed energy values provides valuable insights into the sustainable management of rice production systems and the electricity grid, helping to identify non-technical losses and improve irrigation efficiency.
Suggested Citation
Daniel Lima Lemes & Matheus Mello Jacques & Natalia Bastos Sousa & Daniel Pinheiro Bernardon & Mauricio Sperandio & Juliano Andrade Silva & Lucas M. Chiara & Martin Wolter, 2023.
"Estimation of Electrical Energy Consumption in Irrigated Rice Crops in Southern Brazil,"
Energies, MDPI, vol. 16(18), pages 1-15, September.
Handle:
RePEc:gam:jeners:v:16:y:2023:i:18:p:6742-:d:1244612
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