Abstract
District heating (DH) is an energy efficient building heating system that entails low primary energy consumption and reduced environmental impact. The estimation of the required heating load provides information for operators to control district heating systems (DHSs) efficiently. It also yields historical datasets for intelligent management applications. Based on the existing virtual sensor capabilities to estimate physical variables, performance, etc., and to detect the anomaly detection in building energy systems, this paper proposes a virtual sensor-based method for the estimation of DH energy consumption in a residential building. Practical issues, including sensor absences and limited datasets corresponding to actual buildings, were also analyzed to improve the applicability of virtual sensors in a building. According to certain virtual sensor development processes, model-driven, data-driven, and grey-box virtual sensors were developed and compared in a case study. The grey-box virtual sensor surpassed the capabilities of the other virtual sensors, particularly for operation patterns corresponding to low heating, which were different from those in the training dataset; notably, a 16% improvement was observed in the accuracy exhibited by the grey-box virtual sensor, as compared to that of the data-driven virtual sensor. The former sensor accounted for a significantly wider DHS operation range by overcoming training data dependency when estimating the actual DH energy consumption. Finally, the proposed virtual sensors can be applied for continuous commissioning, monitoring, and fault detection in the building, since they are developed based on the DH variables at the demand side.
Highlights
The proposed virtual sensors can be applied for continuous commissioning, monitoring, and fault detection in the building, since they are developed based on the District heating (DH) variables at the demand side
The target district heating systems (DHSs) consisted of a heat exchanger, two circulating pumps, a differential proposed sensor method wasvalve applied to a DHS
Virtual sensor development and validation for determining DH energy consumption in a building was the focus of this study, and it considered the issue of sensor absence in real DH substations
Summary
District heating systems (DHSs) are widely adopted for heating buildings, especially in urban areas of several countries worldwide. This is because DHSs can provide efficient heating, with low primary energy resource consumption and less impact on the environment [1]. With the advancement of sensor networks, data analysis, and data-driven applications entailing building energy systems, various management and control technologies have been recently studied with regard to district heating (DH) substations [2]. The monitoring of DH energy consumption in a building can provide:. Continuous monitoring of building energy consumption is essential for optimal DHS control and operation, and for advanced application development (1) information regarding efficiently controlling the system and (2) historical energy datasets for Energies 2020, 13, 6013; doi:10.3390/en13226013 www.mdpi.com/journal/energies
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