4.7 Article

Enhancing self-consumption for decarbonization: An optimization strategy based on a calibrated building energy model

期刊

ENERGY AND BUILDINGS
卷 298, 期 -, 页码 -

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2023.113576

关键词

Building energy models (BEM); HVAC; Internal thermal mass; Variable refrigerant flow (VRF); EnergyPlus; Set-point optimization

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In order to achieve the decarbonization target set by the European Union, the trend in the building industry is to electrify building services and replace fossil fuels with renewable energy sources. However, concerns about grid-network security and stability arise from the widespread use of PV systems. Therefore, optimizing the consumption of a building's own PV production is crucial to reduce excess output. This study proposes a demand side optimization strategy for the thermostatic controllable loads of a building, resulting in significant improvements in self-consumption.
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 bidimensional 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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