Enhancing self-consumption for decarbonization: An optimization strategy based on a calibrated building energy model
Building energy models (BEM)
Internal thermal mass
Variable refrigerant flow (VRF)
Set-point optimization
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© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
Fernández-Vigil, M. (María); Pachano, J. E. (José Eduardo); Fernández-Bandera, C. (Carlos); et al. "Enhancing self-consumption for decarbonization: An optimization strategy based on a calibrated building energy model". Energy and Buildings. 298, 2023, 1 - 16
To face the challenge of climate change and achieve the decarbonization target set by the European Union, the current trend is to electrify building services, replacing the use of fossil fuels for renewable energy sources. The installation of grid-connected photovoltaic (PV) systems is becoming a popular strategy. However, the widespread application of PV solutions carries certain concerns about grid-network security and stability, since intermittent renewable energy excess pouring into the grid may exceed voltage limits. Therefore, an optimization of the consumption of a building's own PV production (self-consumption) to reduce the excess output is vital. The following paper performs a demand side optimization strategy of the building's thermostatic controllable loads (heating and cooling), which represent at least 50% of the total energy consumed by the building. The process is applied in a previously calibrated building energy model (BEM) that describes a fully operational building under a typical Mediterranean climate (Greece). The site contains a PV plant and a multi-split Variable Refrigerant Flow (VRF) system dedicated to maintain indoor comfort conditions. The technology used is simple, able to perform 15 minute time-step yearly optimizations while saving a large amount of computational time. It performs a bi-dimensional optimization of both: indoor thermal-zone set-points and ventilation air supply temperature. The optimization process performed is based on 2019 data gathered from European Project SABINA, resulting in a self-consumption improvement of 11.6% for summer scenario (reaching 69.16%) and 78.7% for winter (reaching 57.47%) in comparison to a non-optimized “business as usual” base model.

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