Uma modelagem visando economia de energia em smarthomes

• Ano de defesa: 2019
• Autor(a) principal: Raphael Luciano de Pontes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Casas Inteligentes; Energia Renovável; Balanceamento de Carga; Economia de Energia; Balanceamento de carga; Energia renovável; Computação; Casas inteligentes
• Link de acesso: http://hdl.handle.net/1843/SLSC-BBKH5S

The ascension of electricity consumption and its consequent growth of carbon footprints becomes a major incentive for implementation of renewable energy in electric utilities. High peaks demand implies great cost for electric power generation and also contributing with carbon emissions, which results in increasing the cost of energy for the final user. Therefore, the power business model adopted by some companies is also a great incentive for the models that prioritize, not only the reduction of consumption, but a homogenization of the peak demand throughout the day. Existing approaches that applies renewable energy (NetMetering) and simulation with real consumption trace (PeakCharge) were considered in this work, for comparison and improvement of our model. In this work, we introduce GreenPeaks, a modeling to deploy the use of clean energy, and using storage batteries, to SmartHomes. Through a reactive workflow, GreenPeaks promotes a significant reduction of the peak demand and bill for the final user, as well as a reduction of the power cost generation for electric utilities.