Improving energy self-sufficiency of a renovated residential neighborhood with heat pumps by analyzing smart meter data

Shalika Walker, Vince Bergkamp, Dujuan Yang, T.A.J. van Goch, Katarina Katic and Wim Zeiler

Energy, 2021, vol. 229, issue C

Abstract: In the energy renovation process, usually, buildings are upgraded to become energy-neutral annually with installed photovoltaic systems and heat pumps. However, the energy self-sufficiency of these buildings is surprisingly low. Therefore, the rapid deployment of heat pump based heating systems creates a shift of natural-gas consumption from the previously consumed building side (boilers) towards the electricity production side (power-plants). Fortunately, the development of information and communication technology enables access to consumption/generation data of building-related energy systems. Thus, there is an opportunity to strategically use this data and improve energy self-sufficiency and accommodate heat pump based heating systems. In this study, the improvement of self-sufficiency is discussed using a renovated neighborhood. The presented method incorporates a smart-grid application with a data-driven clustering, prediction, and an energy management strategy. First, clustering of similar demand-profiled dwellings with the k-means algorithm, and demand-prediction using the random-forest technique was performed. Afterwards, electric energy storage was introduced and multi-objective optimization reducing annualized costs and carbon emissions have been performed. For the carbon-dioxide optimal case, when aimed at the entire neighborhood, an annual self-sufficiency increment of more than 25% can be achieved, while four months out of the twelve being 100% energy self-sufficient.

Keywords: K-means clustering; Neighborhood level; Electrical storage system; Random-forest; Multi-objective optimization (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:229:y:2021:i:c:s0360544221009592

DOI: 10.1016/j.energy.2021.120711

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