Caracterização De Estações De Bombeamento Em Lavouras De Arroz Do Rio Grande Do Sul

Köpp, Luciana Marini; Peiter, Márcia Xavier; Robaina, Adroaldo Dias; Toescher, Carlos Fernando

doi:10.1590/1809-4430-eng.agric.v36n2p342-351/2016

Cited by 5 publications

(7 citation statements)

References 9 publications

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“…According to the scenario of expansion in the irrigated area with projection for 2030 carried out by the National Water Agency (ANA, 2017), non-mechanized systems such as furrow and flood irrigation are expected to undergo a retraction, being either replaced by others or discontinued in some areas, with the exception of flooded rice, which has a trend of stabilization in the main centers of the country, mainly in Rio Grande do Sul, with an irrigated area of 1,113,500 ha in the 2013/2014 season (Köpp et al, 2016). Also, according to these projections, the net estimated growth of irrigation methods will be concentrated in drip irrigation and micro-sprinkler irrigation.…”

Section: Resultsmentioning

confidence: 99%

Evolution and current scenario of irrigated area in Brazil: Systematic data analysis

Carvalho

Martins

Santos

et al. 2020

Rev. bras. eng. agríc. ambient.

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Water is an essential element to life and used in various human activities. However, because of the amount used in agriculture and the increase in irrigated area, the sustainable use of this resource has become a worldwide concern. In this study, data from the Censuses of Agriculture published by the Instituto Brasileiro de Geografia e Estatística (IBGE) from 1960 to 2017 were evaluated in relation to the regions and irrigation methods, performing a detailed analysis between the data from the 2006 and 2017 Censuses. There was an increase in irrigated area in Brazil in all geographic regions, reaching 6.9 million hectares in 2017. Sprinkler irrigation methods are the most used, with 48% of the irrigated area, followed by localized irrigation (24.4%) and surface irrigation (22.3%). Drip irrigation is the most used system in establishments up to 50 ha (617,423 ha), followed by conventional sprinkler (514,893 ha), while the center pivot stands out in areas larger than 50 ha (1,362,828 ha). The Southeast region (38.6%) and the states of Rio Grande do Sul (20.4%), Minas Gerais (16.6%) and São Paulo (16.0%) stand out as the ones with the largest irrigated area in the country. The State of Minas Gerais showed the highest growth of irrigated area in the 2006-2017 period (116.1%), due to the expansion of areas irrigated with center pivot.

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Section: Resultsmentioning

confidence: 99%

Evolution and current scenario of irrigated area in Brazil: Systematic data analysis

Carvalho

Martins

Santos

et al. 2020

Rev. bras. eng. agríc. ambient.

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“…Irrigation efficiency should also be considered, along with concerns about meeting the demand in rural activities. The irrigation systems use motors and pumps to provide water to crops [11]. Thus, improving irrigation efficiency increases productivity and producer profits.…”

Section: Energy Losses In Brazilmentioning

confidence: 99%

Detection of Non-Technical Losses in Irrigant Consumers through Artificial Intelligence: A Pilot Study

Vieira,

Bernardon,

Uberti

et al. 2023

Energies

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Non-technical losses (NTLs) verified in the power distribution grids cause great financial losses to power utilities. In rural distribution grids, fraudulent consumers contribute to technical problems. The Southern region in Brazil contains more than 70% of the total rice production and power irrigation systems. These systems operate seasonally in distribution grids with high NTL conditions. This work aimed to present an artificial intelligence-based system to help power distribution companies detect potential consumers causing NTLs. This minimizes the challenge of maintaining compliance with current regulations and ensuring the quality of services and products. In the proposed methodology, historical energy consumption information, meteorological data, satellite images, and data from energy suppliers are processed by artificial intelligence, indicating the suspicious consumer units of NTL. This work presents every step developed in the proposed methodology and the tool application in a pilot area. We detected a high number of consumers responsible for NTLs, with an accuracy of 63% and an average reduction of 78% in the search area. These results corroborated the effectiveness of the tool and instigated the research team to expand the application to other rice production areas.

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“…Na Região da Fronteira Oeste do Rio Grande do Sul, a energia elétrica é empregada para o funcionamento das estações de bombeamento utilizadas na distribuição de água nas lavouras de arroz irrigado. Esses sistemas são compostos por bombas hidráulicas, motores de indução trifásicos (com potência ativa nominal variando de 100 a 300 cv), sistema de transmissão mecânica (polias ou correias), tubulações (recalque e sucção), entre outros componentes (Kopp et al 2016). Dessa forma, a atividade de irrigação representa uma parcela muito significativa no consumo da instalação rural, pois as estações de bombeamento funcionam de maneira continua em praticamente todo o período em que compreende a safra do arroz irrigado (Pfitscher et al 2012).…”

Section: Diante De Algumas Adversidades Apresentadas Metodologiasunclassified

“…O cálculo da estimativa de consumo de energia elétrica em unidades consumidoras irrigantes, é iniciado a partir da previsão da potência instalada do sistema de irrigação apresentada em Kopp et al (2016), conforme descrito em (1). 0, 0098…”

Section: Estimativa De Consumo De Energia Elétrica Das Unidades Consu...unclassified

Metodologia para Identificação de Perdas Não Técnicas em Unidades Consumidoras localizadas em Áreas Rurais com Cultivo de Arroz Irrigado

Eichkoff

Bernardon²,

Souza

et al. 2022

Proceedings IX Simpósio Brasileiro De Sistemas Elétricos

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This work presents a proposal for the identification of non-technical losses in rural consumers directed to irrigated rice cultivation. The methodology employs in the structure of its algorithm, the k-Means and Random Forest methods, for the clustering and classification of data, using as inputs, monthly records of billed energy from a group of irrigating consumers in the county of Uruguaiana/RS. In addition, the algorithm proposed by this study performs the estimate of electricity consumption of rural consumers based on information on crop planting areas and variables of irrigation systems.Resumo: Este trabalho apresenta uma proposta para a identificação de perdas não técnicas em consumidores rurais direcionados para o cultivo do arroz irrigado. A metodologia emprega na estrutura de seu algoritmo, os métodos de k-Means e Random Forest, para o agrupamento e classificação de dados, utilizando como entradas, registros mensais de energia faturada de um conjunto de consumidores irrigantes do município de Uruguaiana/RS. Além disso, o algoritmo proposto por esse estudo, realiza a estimativa de consumo de energia elétrica das unidades consumidoras rurais a partir de informações sobre as áreas de plantio de arroz e variáveis dos sistemas de irrigação.

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Caracterização De Estações De Bombeamento Em Lavouras De Arroz Do Rio Grande Do Sul

Cited by 5 publications

References 9 publications

Evolution and current scenario of irrigated area in Brazil: Systematic data analysis

Evolution and current scenario of irrigated area in Brazil: Systematic data analysis

Detection of Non-Technical Losses in Irrigant Consumers through Artificial Intelligence: A Pilot Study

Metodologia para Identificação de Perdas Não Técnicas em Unidades Consumidoras localizadas em Áreas Rurais com Cultivo de Arroz Irrigado

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