Abstract
Buildings are envisioned to play an active role in future low-carbon energy systems. The complexity of building energy management systems increases as they interface more and more subsystems and domains. As an important step to achieve a higher technology readiness level, these energy management systems need to be systematically tested in real-life conditions. Currently, there are no standard testing and experiment strategies in buildings to handle the mentioned complexity. Additionally, the levels of details reported in the existing experimental studies are heterogeneous. This paper summarizes an application of a holistic testing method to a flexible fully-equipped prosumer with the goal of facilitating test preparation, execution, replication, and comparison. Several empirical suggestions are provided, and a hybrid quantification strategy with digital twins is presented.
Highlights
Advanced building energy management systems have received much attention in recent years due to increasing digitalization, potentials to contribute to carbon neutrality targets [1] and capability of supporting future low-carbon energy systems [2]
This paper adapts the method for building applications and complements it with additional empirical insights and a hybrid quantification strategy using digital twins
This study proposes a hybrid strategy using a digital twin, which refers to an extensive model of the physical system set up in a programming environment, connected to various streams of data, and accurately calibrated to mimic the system’s dynamic behavior through simulation
Summary
Advanced building energy management systems have received much attention in recent years due to increasing digitalization, potentials to contribute to carbon neutrality targets [1] and capability of supporting future low-carbon energy systems [2]. They are envisioned to be interactive in future smart energy systems and will operate in dynamic conditions. The levels of details reported in the existing experimental studies are heterogeneous This may lead to difficulties in replication and comparison. This paper adapts the method for building applications and complements it with additional empirical insights and a hybrid quantification strategy using digital twins.
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