{"id":9300,"date":"2024-01-17T17:21:49","date_gmt":"2024-01-17T17:21:49","guid":{"rendered":"https:\/\/dailyai.com\/?p=9300"},"modified":"2024-01-17T20:53:30","modified_gmt":"2024-01-17T20:53:30","slug":"researchers-use-ai-to-reduce-carbon-capture-energy-consumption-by-a-third","status":"publish","type":"post","link":"https:\/\/dailyai.com\/pt\/2024\/01\/researchers-use-ai-to-reduce-carbon-capture-energy-consumption-by-a-third\/","title":{"rendered":"Investigadores utilizam a IA para reduzir em um ter\u00e7o o consumo de energia na captura de carbono"},"content":{"rendered":"

Um estudo publicado na revista Reaction Chemistry and Engineering por investigadores da Universidade de Surrey utilizou a IA para melhorar a captura de carbono em centrais el\u00e9ctricas, reduzindo o consumo de energia em mais de um ter\u00e7o.<\/b><\/p>\n

O investiga\u00e7\u00e3o<\/a>O projeto, liderado pelo Professor Jin Xuan, respons\u00e1vel pelos processos sustent\u00e1veis na Escola de Qu\u00edmica e Engenharia Qu\u00edmica da Universidade de Surrey, centrou-se na otimiza\u00e7\u00e3o dos sistemas de captura de carbono.\u00a0<\/span><\/p>\n

Apresenta um sistema modelo baseado numa central el\u00e9ctrica a carv\u00e3o real que utiliza a IA para conseguir um aumento de 16,7% na captura de di\u00f3xido de carbono (CO2), reduzindo simultaneamente o consumo de energia n\u00e3o energ\u00e9tica da rede nacional do Reino Unido em 36,3%.<\/span><\/p>\n

O Prof. Xuan sublinhou a novidade desta abordagem, <\/span>afirmando num artigo da Universidade de Surrey<\/span><\/a>\"Normalmente, os sistemas de captura de carbono funcionam constantemente, ao mesmo ritmo - independentemente das altera\u00e7\u00f5es externas do ambiente. Mas mostr\u00e1mos que ensinar o sistema a fazer pequenas adapta\u00e7\u00f5es pode produzir grandes poupan\u00e7as de energia e, ao mesmo tempo, capturar mais carbono\".<\/span><\/p>\n

A captura de carbono \u00e9 um processo fundamental para atenuar o impacto ambiental do CO2, o principal g\u00e1s com efeito de estufa produzido pela maioria das centrais el\u00e9ctricas.\u00a0<\/span><\/p>\n

Isto \u00e9 normalmente conseguido atrav\u00e9s da meteoriza\u00e7\u00e3o melhorada, um m\u00e9todo em que o g\u00e1s de combust\u00e3o \u00e9 borbulhado atrav\u00e9s de \u00e1gua contendo calc\u00e1rio, reagindo com o carbonato de c\u00e1lcio para formar bicarbonato inofensivo.\u00a0<\/span><\/p>\n

No entanto, este processo \u00e9 intensivo em termos energ\u00e9ticos, necessitando de energia para bombear \u00e1gua e CO2. A central de captura de CO2 do estudo tinha a sua pr\u00f3pria turbina e\u00f3lica para energia renov\u00e1vel, mas em tempo mais calmo, quando esta era insuficiente, utilizava energia da rede.\u00a0\u00a0<\/span><\/p>\n

Os resultados da equipa de investiga\u00e7\u00e3o consistem na utiliza\u00e7\u00e3o da IA para permitir que o sistema modelo preveja as flutua\u00e7\u00f5es na produ\u00e7\u00e3o de CO2 e na disponibilidade de energias renov\u00e1veis. Isto permitiu que o sistema ajustasse a bombagem de \u00e1gua em conformidade, optimizando a utiliza\u00e7\u00e3o de energia ao longo do tempo.<\/span><\/p>\n

\"Aprendizagem
Otimiza\u00e7\u00e3o das tecnologias de captura de carbono com aprendizagem autom\u00e1tica. Fonte: Qu\u00edmica e Engenharia das Reac\u00e7\u00f5es<\/a>.<\/figcaption><\/figure>\n

O Dr. Lei Xing, professor de qu\u00edmica e engenharia qu\u00edmica na Universidade de Surrey, sublinhou as implica\u00e7\u00f5es das suas descobertas, afirmando: \"Embora tenhamos testado o nosso modelo na meteoriza\u00e7\u00e3o melhorada, os princ\u00edpios aplicam-se de forma mais ampla. O nosso modelo pode ajudar qualquer pessoa que tente capturar e armazenar mais CO2 com menos energia - seja qual for o processo que esteja a utilizar.\"<\/span><\/p>\n

Os investigadores esperam que estas descobertas possam contribuir para os Objectivos de Desenvolvimento Sustent\u00e1vel das Na\u00e7\u00f5es Unidas, que visam reduzir a press\u00e3o sobre as fontes de energia n\u00e3o renov\u00e1veis e investir em tecnologias inovadoras de captura de carbono.\u00a0\u00a0<\/span><\/p>\n

No in\u00edcio de janeiro deste ano, a Microsoft utilizou a IA para criar um novo eletr\u00f3lito de bateria de l\u00edtio capaz de reduzir <\/span>teor de l\u00edtio das pilhas de cerca de 70%<\/span><\/a>.<\/span><\/p>\n

Mais informa\u00e7\u00f5es sobre o estudo<\/span><\/h2>\n

O estudo visava otimizar a captura de carbono para reduzir a utiliza\u00e7\u00e3o de fontes de energia n\u00e3o renov\u00e1veis, mantendo ou melhorando a captura de CO2.\u00a0<\/span><\/p>\n

Utilizou a IA para ajustar o sistema com base em pequenas altera\u00e7\u00f5es, em vez de funcionar continuamente ao mesmo ritmo.\u00a0<\/span><\/p>\n

Eis como funciona:<\/span><\/p>\n

    \n
  • Cria\u00e7\u00e3o de modelos para a captura de CO2<\/b>: Os investigadores desenvolveram modelos de aprendizagem autom\u00e1tica para prever a efici\u00eancia com que um reator poderia capturar CO2 e a quantidade de energia que consumiria. Utilizaram dois tipos de modelos: LSTM (Long Short-Term Memory) e MLP (Multilayer Perceptron).<\/span><\/li>\n
  • Previs\u00e3o de factores-chave com IA<\/b>: Utilizaram a IA para prever dois factores cruciais: a quantidade de CO2 presente no g\u00e1s de uma central de carv\u00e3o e a quantidade de energia e\u00f3lica dispon\u00edvel para alimentar o processo de captura. Estas previs\u00f5es s\u00e3o importantes para o planeamento do processo de captura.<\/span><\/li>\n
  • Testar e melhorar os modelos<\/b>: A equipa testou rigorosamente a precis\u00e3o dos seus modelos de IA utilizando m\u00e9todos estat\u00edsticos. Utilizaram tamb\u00e9m uma t\u00e9cnica denominada previs\u00e3o conforme para determinar o grau de confian\u00e7a que podiam ter nas previs\u00f5es do modelo.<\/span><\/li>\n
  • Otimiza\u00e7\u00e3o do processo de captura<\/b>: Utilizando os dados dos seus modelos de IA, os investigadores empregaram um algoritmo sofisticado para encontrar o melhor equil\u00edbrio entre a captura da maior quantidade de CO2 e a utiliza\u00e7\u00e3o da menor quantidade de energia n\u00e3o renov\u00e1vel.<\/span><\/li>\n
  • Analisar os resultados<\/b>: Os resultados foram prometedores. Mostraram que, em m\u00e9dia, o reator capturou mais 16,7% de CO2 e utilizou menos 36,3% de energia proveniente de fontes n\u00e3o renov\u00e1veis durante um m\u00eas.<\/span><\/li>\n<\/ul>\n

    Este facto demonstra a utilidade da IA na tecnologia de redu\u00e7\u00e3o de energia.\u00a0<\/span><\/p>\n

    Os sistemas leves de IA instalados em processos e aparelhos que consomem energia podem otimizar a sua funcionalidade para reduzir eficazmente o consumo de recursos. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Um estudo publicado na revista Reaction Chemistry and Engineering por investigadores da Universidade de Surrey utilizou a IA para melhorar a captura de carbono em centrais el\u00e9ctricas, reduzindo o consumo de energia em mais de um ter\u00e7o. A investiga\u00e7\u00e3o, liderada pelo Professor Jin Xuan, respons\u00e1vel pelos processos sustent\u00e1veis na Escola de Qu\u00edmica e Engenharia Qu\u00edmica da Universidade de Surrey, centrou-se na otimiza\u00e7\u00e3o dos sistemas de captura de carbono. Apresenta um sistema modelo baseado numa central el\u00e9ctrica a carv\u00e3o real que utiliza a IA para conseguir um aumento de 16,7% na captura de di\u00f3xido de carbono (CO2), reduzindo simultaneamente o consumo n\u00e3o energ\u00e9tico da rede nacional do Reino Unido em 36,3%. O Prof. Xuan sublinhou a import\u00e2ncia de<\/p>","protected":false},"author":2,"featured_media":9301,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[522,262,105],"class_list":["post-9300","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-energy","tag-energy-consumption","tag-machine-learning"],"yoast_head":"\nResearchers use AI to reduce carbon capture energy consumption by a third | DailyAI<\/title>\n<meta name=\"description\" content=\"A study published in Reaction Chemistry and Engineering by researchers at the University of Surrey used AI to enhance carbon capture at power plants, reducing energy consumption by over a third.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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