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FRANCESCO GUARINO

Load match optimisation of a residential building case study: A cross-entropy based electricity storage sizing algorithm

  • Autori: Guarino, F; Cassarà, P; Longo, S; Cellura, M; Ferro, E
  • Anno di pubblicazione: 2015
  • Tipologia: Articolo in rivista (Articolo in rivista)
  • OA Link: http://hdl.handle.net/10447/146654

Abstract

The EU EPBD recast regulation marked the application of the net zero energy building (Net ZEB) concept in all fields of building construction in Europe as a building able to generate as much energy as it consumes over a selected time frame. A more detailed insight is however needed, as even if a building achieves a long-term energy balance between energy generated and consumed, smaller time scales must also be considered. For example, from the utility’s point of view, if a Net ZEB is a heavy consumer in the winter, it will appear to be quite similar to a conventional building, requiring the use of additional generation. The increase in the generation-load match means reducing the stress to the energy grid, the peak system energy required, and the wasted energy, thus avoiding unnecessary generation and, consequently, limiting carbon-related emissions. In this paper, the authors address the problem of determining the optimal storage size starting from the data of an Italian nearly net zero energy building that produced a detailed database on generated and consumed electricity. The study presented in this paper analyses the following steps: modelling of energy consumption through non-parametric estimators, modelling of energy generation through detailed models available in the literature, quantification of the load match levels for existing case studies, analysis of the state of charge (SOC) for a given model of the energy consumption probability distribution, and the identification of the minimum size of the storage required to improve energy load match. The results show that even when selecting unfavourable boundary conditions it could be possible to lower the energy import from the electricity grid by approximately 40%, that can possibly rise to more than 90% during summer.