An IoT Data System for Solar Self-Consumption
DocUID: 2023-006 Full Text:
PDF Author: Soteris Constantinou, Nicolas Polycarpou, Constantinos Costa, Andreas Konstantinidis, Panos K. Chrysanthis, Demetrios Zeinalipour-Yazti
Abstract: Energy efficiency has become a primary optimization objective due to the global energy crisis and high levels of CO2 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 multi-objective 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 CO2 emissions.
Keywords: Green Planning, Rule Automation, Renewable Self-Consumption, Internet-of-Things, Load Shifting
Published In: 24th IEEE International Conference on Mobile Data Management (MDM)
Pages: 65-72
Place Published: Singapore
Year Published: 2023
DOI: 10.1109/MDM58254.2023.00022
Project: Green Living Subject Area: Energy Efficiency, IoT
Publication Type: Conference Paper
Sponsor: Others