Development and validation of an intelligent algorithm for synchronizing a low-environmental-impact electricity supply with a building’s electricity consumption

Standard algorithm of building’s energy strategy often use electricity and its tariff as the sole criterion of choice. This paper introduced an algorithmic regulation using global warming potential (GWP) of energy flux, to select which installation will satisfy the building energy demand (BED). In the frame of the Correlation Carbon project conducted by the Smart Living Lab (SLL), a research center dedicated to the building of the future, this paper presents the algorithm behind the design, the selection and the operation of appropriate energy installations for low-carbon buildings. The control strategy governing the building’s energy flow takes into account demand, supply and storage. The latter being mainly linked to economic or energy benefits, which standard algorithms often use as the only criterion of choice, thus increasing the environmental impact of the energy flowing through the building. In contrast to those, the algorithm introduced in this paper controls the energy fluxes of the electrical grid, photovoltaic (PV) panels, static and vehicle batteries according to their GWP. A simulation over one year at an hourly time step – enabling one to take into account small but significant variations of the GWP of the electricity from grid – is presented for different scenarios, in order to draw an annual balance for a given combination of energy systems. The algorithm chooses the “cleanest” instantaneous energy source combination to meet the BED. Simulations show that a building using this algorithm can satisfy its BED while reducing its GWP by as much as 40% compared to an energy supply using the grid only.

Published in:
Proceedings of The 4th International Conference on Renewable Energy Technologies (ICRET 2018)
Presented at:
The 4th International Conference on Renewable Energy Technologies (ICRET 2018), Kuala Lumpur, Malaysia, January 16-18, 2018
Kuala Lumpur, IOP Conference Series

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 Record created 2018-01-16, last modified 2020-07-29

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