Decoupling the heat loss coefficient of an in-use office building into its transmission and infiltration heat loss coefficients

Uriarte, Irati; Erkoreka, Aitor; Legorburu, A Pérez; Martín-Escudero, Koldobika; Giraldo-Soto, Catalina; Odriozola-Maritorena, Moisés

doi:10.1016/j.jobe.2021.102591

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…In the last 20-30 years, notable advances have been made in building energy simulation, but much less progress has been made in terms of measuring, analyzing, and learning about the real operation and performance of the buildings. Numerous studies [37][38][39] show that there is a large difference between theoretical values and real data on building environments, which has been called the building performance gap (BPG), especially in heterogeneous university buildings with high complexity and variable occupation. These differences are due to the numerous simplifying assumptions required to model and simulate the real behavior of buildings.…”

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“…On the one hand, the energy demand in a building can be estimated through the energy regulations when it was built. However, several key factors (design, orientation, ubication, and use) can produce large consumption variations studies [37]. Even in new buildings, there are significant differences between calculated energy and measured consumption, reinforcing the idea of filling the gap between theoretical values and real data studies [38][39][40].…”

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Internet of Things (IoT) in Buildings: A Learning Factory

et al. 2023

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Advances towards smart ecosystems showcase Internet of Things (IoT) as a transversal strategy to improve energy efficiency in buildings, enhance their comfort and environmental conditions, and increase knowledge about building behavior, its relationships with users and the interconnections among themselves and the environmental and ecological context. EU estimates that 75% of the building stock is inefficient and more than 40 years old. Although many buildings have some type of system for regulating the indoor temperature, only a small subset provides integrated heating, ventilation, and air conditioning (HVAC) systems. Within that subset, only a small percentage includes smart sensors, and only a slight portion of that percentage integrates those sensors into IoT ecosystems. This work pursues two objectives. The first is to understand the built environment as a set of interconnected systems constituting a complex framework in which IoT ecosystems are key enabling technologies for improving energy efficiency and indoor air quality (IAQ) by filling the gap between theoretical simulations and real measurements. The second is to understand IoT ecosystems as cost-effective solutions for acquiring data through connected sensors, analyzing information in real time, and building knowledge to make data-driven decisions. The dataset is publicly available for third-party use to assist the scientific community in its research studies. This paper details the functional scheme of the IoT ecosystem following a three-level methodology for (1) identifying buildings (with regard to their use patterns, thermal variation, geographical orientation, etc.) to analyze their performance; (2) selecting representative spaces (according to their location, orientation, use, size, occupancy, etc.) to monitor their behavior; and (3) deploying and configuring an infrastructure with +200 geolocated wireless sensors in +100 representative spaces, collecting a dataset of +10,000 measurements every hour. The results obtained through real installations with IoT as a learning factory include several learned lessons about building complexity, energy consumption, costs, savings, IAQ and health improvement. A proof of concept of building performance prediction based on neural networks (applied to CO2 and temperature) is proposed. This first learning shows that IAQ measurements meet recommended levels around 90% of the time and that an IoT-managed HVAC system can achieve energy-consumption savings of between 10 and 15%. In summary, in a real context involving economic restrictions, complexity, high energy costs, social vulnerability, and climate change, IoT-based strategies, as proposed in this work, offer a modular and interoperable approach, moving towards smart communities (buildings, cities, regions, etc.) by improving energy efficiency and environmental quality (indoor and outdoor) at low cost, with quick implementation, and low impact on users. Great challenges remain for growth and interconnection in IoT use, especially challenges posed by climate change and sustainability.

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Internet of Things (IoT) in Buildings: A Learning Factory

et al. 2023

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“…Where: U j -coefficient of heat transfer through the building structure (W•m -2 •K -1 ), S j -area of the structure (m 2 ), t i , t e -indoor design temperature, outdoor area design temperature (°C). By increasing the thermal resistance of the building envelope, the heat loss through penetration decreases and the heat loss through ventilation becomes more important [15]. For this reason, elements for heat recovery from exhaust air are now being installed in ventilation systems [16].…”

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Modelling the Heat Loss of a Building

Rigo¹,

Velička²

2022

AMS

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The aim of this paper is to calculate the heat loss and annual energy demand for heating of an administrative building for three variants of thermal-technical design and their evaluation. The heat losses were determined according to the legislation in force and in accordance with the normative requirements. The calculations made can be used in the next phase for the design of the heat source and heating system for heating and for the design of forced ventilation with heat recovery. Based on the optimum choice of technical equipment, it is also possible to evaluate the investment and operating costs for the installation of the different heating and ventilation concepts. Given the current significant increase in energy prices, the present topic is very topical.

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