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- W4386066526 abstract "Energy efficiency has become a primary optimization objective due to the global energy crisis and high levels of CO <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</inf> emissions. Climate and energy targets have been leading to a growing utilization of solar photovoltaic power generation in residential buildings. As the number of IoT devices drastically increases, their automation through an intelligent home energy management system can provide energy and peak demand savings. The planning optimization of devices can be very challenging due to the unsophisticated user-defined preference rules. Existing solutions face convergence difficulties due to the management of multiple IoT devices tackling multiobjective problems. In this paper, we propose an innovative IoT data system, coined GreenCap, which utilizes a Green Planning evolutionary algorithm for load shifting of IoT-enabled devices, considering the integration of renewable energy sources, multiple constraints, peak-demand times, and dynamic pricing. We have implemented a complete prototype system available on Raspberry Pi and linked with openHAB framework. Our experimental evaluation with extensive real traces shows that the GreenCap prototype system efficiently generates a sustainable plan obtaining high levels of user comfort 92-99% along with ≈52% of self-consumption, while reducing ≈35% of the imported energy from the grid and ≈40% of CO <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</inf> emissions." @default.
- W4386066526 created "2023-08-23" @default.
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- W4386066526 date "2023-07-01" @default.
- W4386066526 modified "2023-10-12" @default.
- W4386066526 title "An IoT Data System for Solar Self-Consumption" @default.
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- W4386066526 doi "https://doi.org/10.1109/mdm58254.2023.00022" @default.
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