Medidor de consumo de agua e energia residencial com monitoramento remoto
Tipo
TCC
Data de publicação
2021-12
Periódico
Citações (Scopus)
Autores
Silva, Gabriel Panema da
Orientador
Akamine, Cristiano
Título da Revista
ISSN da Revista
Título de Volume
Membros da banca
Programa
Resumo
Em meio a crises hídricas e energéticas cada vez mais frequentes, torna-se fundamental a mudança nos hábitos de consumo por parte dos consumidores, inclusive em suas residências. Nesse cenário, este trabalho teve o objetivo de apresentar um sistema integrado de monitoramento remoto para consumo de água e energia elétrica residencial, utilizando um computador em placa única, ferramentas de previsão de séries temporais e análise de dados para alerta de anomalias. Além disso, com o objetivo de incentivar a utilização consciente dos recursos pelos consumidores residenciais, esta pesquisa apresentou uma comparação de tarifas para indicação de viabilidade para mudança de modalidade tarifária a partir do perfil de consumo. Na residência em estudo, onde foi instalado o sistema que utilizou um computador Raspberry Pi, foi possível monitorar a curva de demanda através do painel desenvolvido em Python. Além disso, o sistema foi capaz de projetar com precisão o consumo futuro da residência, através de dois modelos preditivos diferentes. A análise de anomalias permitiu a identificação de como o uso de alguns equipamentos consome energia de modo discrepante dos demais, além de alertar para um possível consumo indevido em períodos sem utilização. Por fim, foi possível identificar para a residência em estudo que o perfil de consumo torna viável a mudança de modalidade tarifária. Nesse cenário, concluiu-se que o sistema desenvolvido contribuiu através do atingimento de seu objetivo de criar um sistema integrado, incentivando o consumo consciente e abrindo caminhos para trabalhos futuros.
In the midst of increasingly frequent water and energy crises, it is essential that consumers change their consumption habits, including in their homes. In this scenario, this work aimed to present an integrated system for remote monitoring of residential water and energy consumption, using a single board computer, time series prediction tools and data analysis for anomaly alerts. Furthermore, with the objective of encouraging the conscious use of resources by residential consumers, this research presented a comparison of tariffs to indicate the viability of changing the tariff modality based on the consumption profile. In the residence under study, where the system that used a Raspberry Pi computer was installed, it was possible to monitor the demand curve through the panel developed in Python. In addition, the system was able to accurately project the future consumption of the residence through two different predictive models. The anomaly analysis allowed the identification of how the use of some equipment consumes energy in a discrepant way from the others, besides alerting to a possible improper consumption in periods of non-use. Finally, it was possible to identify for the residence under study that the consumption profile makes it feasible to change the tariff modality. In this scenario, it was concluded that the developed system contributed through the achievement of its objective of creating an integrated system, encouraging conscious consumption and opening paths for future work.
In the midst of increasingly frequent water and energy crises, it is essential that consumers change their consumption habits, including in their homes. In this scenario, this work aimed to present an integrated system for remote monitoring of residential water and energy consumption, using a single board computer, time series prediction tools and data analysis for anomaly alerts. Furthermore, with the objective of encouraging the conscious use of resources by residential consumers, this research presented a comparison of tariffs to indicate the viability of changing the tariff modality based on the consumption profile. In the residence under study, where the system that used a Raspberry Pi computer was installed, it was possible to monitor the demand curve through the panel developed in Python. In addition, the system was able to accurately project the future consumption of the residence through two different predictive models. The anomaly analysis allowed the identification of how the use of some equipment consumes energy in a discrepant way from the others, besides alerting to a possible improper consumption in periods of non-use. Finally, it was possible to identify for the residence under study that the consumption profile makes it feasible to change the tariff modality. In this scenario, it was concluded that the developed system contributed through the achievement of its objective of creating an integrated system, encouraging conscious consumption and opening paths for future work.
Descrição
Palavras-chave
medições inteligentes , computadores em placa única , séries temporais , smart metering , single board computers , time series