Abstract

The residential sector accounts for 30% of the total green house gas emissions in Europe, which can be reduced either by switching to low-carbon technologies or reducing the amount of fossil fuel energy consumed. In this work, a new greenhouse gas emission (GHGE) reduction system at the house (nanogrid) level is investigated. The originality of the proposed system and underlying algorithm lies in the fact that it acts in a proactive manner, by continuously controlling and optimizing energy flows between on-site local power production systems (photovoltaics - PV - array in our case), loads, and storage units (combining battery and thermal storage reservoirs). This system/algorithm is evaluated based on real-life input datasets from the United Kingdom (UK) and France, and compared with traditional house energy infrastructures, namely (i) a house not fitted with battery, and (ii) a house fitted with battery but without additional “smart” software layer. Results show that it performs better in terms of CO2 (capacity of the algorithm to reduce the amount of non carbon-free energy consumed from the grid), Power to Grid (capacity to maximize the use of local green energy), and financial cost (capacity to reduce the overall electricity bill), respectively improving performance by up to 8%, 10% and 37%.

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