Automated data labeling of building automation systems using time series data and conditional probabilitiesMaghnie, M; Stinner, F; Kümpel, A; Müller, D
doi: 10.1088/1742-6596/2600/13/132013pmid: N/A
As energy efficiency demands increase, buildings get smarter, and the amount of data to analyze grows, where each building device may generate multiple data streams. These extensive quantities of monitoring data serve as a great opportunity for detecting anomalies in building automation systems and for optimizing their control. However, each building usually uses a custom format for data labels, therefore requiring an individual data label analysis per building. This makes the conceptually manageable task of detecting energy systems from the raw data increasingly complex and error-prone, which is a further hurdle that any building operation optimizer must resolve. This paper presents a methodology for automatically categorizing and labeling raw monitoring data from building automation systems. Using statistical features of the data, the method checks which data streams follow which known building operation rules and patterns. Therefore, an initial labeling of the data streams takes place. Furthermore, examining the correlation between the data streams indicates possible related system components using the concept of conditional probability. As a use case for the methodology, unlabeled data from a real building automation system are examined. The results show that, using unlabeled time series, data types from certain sensors and actuators can be reliably identified. The proposed methodology could therefore simplify the implementation of energy applications such as operation optimization and fault detection of building automation systems
Quantifying the impact of Covid-19 on the energy consumption in the low-income housing in Greater LondonMohajeri, N; Javanroodi, K; Fergouson, L.; Zhou, J; Nik, V; Gudmundsson, A; Anvari, E Arab; Taylor, J; Symonds, P; Davies, M
doi: 10.1088/1742-6596/2600/13/132002pmid: N/A
Covid-19 has caused great challenges to the energy sector, particularly in residential buildings with low-income households. This study investigates the impact of the confinement measures due to the Covid-19 outbreak on the energy demand of seven residential archetype buildings in Greater London. Three levels of confinement for occupant schedules are proposed and compared with the base case before Covid-19. The archetypes, their boundary conditions, and input parameters are set up according to statistics from English Housing Survey (EHS) sample data for low-income housing. The base case scenario (normal life without confinement measures) is validated against the measured data energy consumption from the National Energy Efficiency Data-Framework (NEED) statistics. The results show that electricity consumption is significantly lower than that for heating and hot water for all the archetypes. By comparing the base case scenario with the full Covid-19 lockdown scenario, the results indicate that heating and hot water consumption (kWh) for all the residential archetypes increases, on average, by 10%, and total electricity demand (kWh) increases by 13%. The study highlights the importance of introducing detailed occupancy profiles in multi-zone building energy simulation models during a pandemic that leads to a greater shift towards home working, which may increase the risk of fuel poverty in low-income housing.
Potentials of radar sensor detecting the presence of an imitated user for optimising short-range presence-sensing lighting in homesSithravel, RatnaKala; Landré, Jérôme; Hurtig-Wennlöf, Anita; Aries, Myriam
doi: 10.1088/1742-6596/2600/13/132010pmid: N/A
Current presence-sensing technologies for energy-efficient lighting control and building optimisation are (i) catered to commercial and institutional environments, and (ii) focused on lamp technology and occupancy detection. They often ignore user behaviour characteristics, which significantly influence energy consumption. Therefore, this study aims to identify alternative sensing techniques as part of a lighting control system that can energy-efficiently support user’s behavioural needs in mixed-function residential spaces. An exploratory study investigated the optimal placement of a non-wearable radar sensor to detect an imitated user’s breathing frequency at varying pre-set horizontal distance positions, and the sensor’s performance was validated with a spirometer. The procedure measured a balloon’s radar-detected distance, radar-detected breathing frequency, and spirometer-registered breathing frequency at each pre-set position. The radar sensor detected all simulated breathing frequencies with almost 100% data accuracy but was not comparable in detecting all distances. The radar offers a less intrusive short-range presence-sensing for homes, accurately detecting breathing frequencies in a contactless way between 0.2m to 0.8m. Further investigations are recommended to develop radar sensing that could predict lighting options based on user’s objective feedback.
Are the next-generation households ready for the energy transition? A survey on their positioning and practice with energy management toolsAntonini, E; Marchi, L; Gaspari, J
doi: 10.1088/1742-6596/2600/13/132001pmid: N/A
In the last decades, significant effort has been put towards technological advancement in housing for energy transition. Massive retrofitting actions have been called for, and innovative technologies for smart energy management at home have been deployed. However, undesired energy trends in housing suggest that relevant factors have been neglected. Among these, increasing importance is now given to occupants’ behaviour, and their capacity to interact with energy management devices available in dwellings. This study investigates what is the position of next-generation users on energy transition at home. Two years ago, the authors launched a survey to explore people’s awareness of energy use practices, interaction with metering devices, and user motivation to change when informed. As a pilot survey, over 300 people from the academy were involved to see what was the position of a sample which was supposed to be informed more than the average, in Italy. The test yielded early outcomes on how people become more interested to change as they gain knowledge and are offered suggestions. Despite the expectations, the sample’s level of awareness was low. This suggested that a more user-centred approach is needed for wide-scale progress. Especially results from the youngest were below prospects. The questionnaire was relaunched to examine if the pandemic, energy crisis and latest news on climate change have affected positions of the youngsters. A testing session involving university students was performed, and results have been compared with the previous. As a result, reflections on the energy use patterns of the next-generation households are provided.
Do the customers remember? The fade-out effect from the demand response applied in the district heating system in DenmarkMarszal-Pomianowska, A; Jensen, O M; Wittchen, K B; Jokubauskis, B; Melgaard, S P
doi: 10.1088/1742-6596/2600/13/132003pmid: N/A
Buildings can deliver short-term thermal energy storage to energy systems. In district heating (DH) systems, it is mainly desk studies and simulations that reveal a large thermal flexibility potential. Knowledge from real-life case studies on how residents participate in demand management campaigns is crucial for the successful utilisation of buildings’ flexibility potential for minimizing bottlenecks in the daily operation of DH systems. In the field study including 72 single-family houses connected to the 3GDH network in southern Denmark, the demand response (DR) strategy “night setback” was applied for two heating periods. The houses were equipped with control and monitoring equipment, which allowed the deactivation of the heating system while monitoring the indoor temperature, so it does not drop below the defined value. The occupants controlled the DR events settings and could at any time stop utilisation of the night setback strategy (implicit participation in the DR). All 72 houses applied the night setback during both heating periods. Yet, the participation time decreased from 89% to 81%. The lowest participation rate was noted for the farm house, 60% and 9% of heating periods 1 and 2, respectively. In around 60% of the DR events, the night setback strategy was activated at 20:00.
Enhancing personalised thermal comfort models with Active Learning for improved HVAC controlsTekler, Zeynep Duygu; Lei, Yue; Dai, Xilei; Chong, Adrian
doi: 10.1088/1742-6596/2600/13/132004pmid: N/A
Developing personalised thermal comfort models to inform occupant-centric controls (OCC) in buildings requires collecting large amounts of real-time occupant preference data. This process can be highly intrusive and labour-intensive for large-scale implementations, limiting the practicality of real-world OCC implementations. To address this issue, this study proposes a thermal preference-based HVAC control framework enhanced with Active Learning (AL) to address the data challenges related to real-world implementations of such OCC systems. The proposed AL approach proactively identifies the most informative thermal conditions for human annotation and iteratively updates a supervised thermal comfort model. The resulting model is subsequently used to predict the occupants’ thermal preferences under different thermal conditions, which are integrated into the building’s HVAC controls. The feasibility of our proposed AL-enabled OCC was demonstrated in an EnergyPlus simulation of a real-world testbed supplemented with the thermal preference data of 58 study occupants. The preliminary results indicated a significant reduction in overall labelling effort (i.e., 31.0%) between our AL-enabled OCC and conventional OCC while still achieving a slight increase in energy savings (i.e., 1.3%) and thermal satisfaction levels above 98%. This result demonstrates the potential for deploying such systems in future real-world implementations, enabling personalised comfort and energy-efficient building operations.
Management tool of highly efficient social housing to provide healthy indoor conditions and fight energy povertyCiria, R.; Garayo, S. Díaz de; Fernández, M.
doi: 10.1088/1742-6596/2600/13/132009pmid: N/A
This research work presents and analyses the monitoring results of a 42 social dwellings building block during two year (2021 and 2022) showing indoor environmental conditions and energy consumption (DHW and heating), considering not only the energy consumption of the dwellings, but also the heat production in a centralized biomass boiler, and thus, the distribution energy losses. The building has been constructed under Passivhaus standard, so the paper studies the gap between expected and real performance, and highlights the importance of user behavior in the final results, showing the savings potential with the change in the usage of the heating systems.
Leveraging campus-scale Wi-Fi data for activity-based occupant modeling in urban energy applicationsMosteiro-Romero, Martín; Miller, Clayton; Quintana, Matias; Chong, Adrian; Stouffs, Rudi
doi: 10.1088/1742-6596/2600/13/132008pmid: N/A
The widespread availability of open datasets in urban areas is transforming how urban energy systems are planned, simulated, and visualized. Urban energy models, however, require an understanding of urban dwellers, as their activities create the demands for energy in buildings. In this paper, we explore using campus-scale Wi-Fi data to identify typical occupant activity patterns as an input to an agent-based model of building occupants at the district scale. The data is taken from a Singaporean university’s Wi-Fi network at high resolution. Each record comprises a timestamp, a device identifier, the location of the device within the campus, and the access point to which it is connected. The Wi-Fi dataset contains 120 different buildings on campus and 10,300 anonymized individual devices. Activities are then assigned to each location on campus according to the building use type. In order to test the methodology, the activity plans of 27,604 undergraduate students, 8,304 graduate students, and 12,018 employees were simulated over a workweek. The results show the model’s ability to produce plausible activity plans but could be improved by implementing sampling rules and expanding the source dataset to include off-peak dates. Nevertheless, using such an agent-based modeling approach at the district scale appears to be a promising methodology to assess the impacts of different planning strategies on occupant behavior and district energy demand.
Towards multi-domain user archetypes for user-centred façade designLuna-Navarro, A; Khandhachani, P; Brembilla, E; Barra, P de la; Andriotis, C
doi: 10.1088/1742-6596/2600/13/132012pmid: N/A
User experience and satisfaction with the facade play a significant role in user comfort and energy efficiency of buildings. This paper explores the concept of User-Facade archetypes to inform the user-centred design of shading devices based on the perceived level of importance of different environmental domains at the workplace. A questionnaire was developed to collect data on users’ perceived level of importance of different environmental domains, user characteristics and other preferences. Based on the associated level of importance of the domains affected by shading devices (thermal conditions, access to daylight, access to outdoor view, privacy and glare mitigation), users were then clustered into eight different archetypes, which associated different “weights” to each comfort domain. The study also found a significant correlation between the associated level of importance and the reported frequency of interaction with shadings because of thermal comfort, glare mitigation or privacy. Overall, users that associated high levels of importance to several environmental domains also reported high perceived levels of importance for personal control at the workplace. Only one archetype reported low importance for personal control at the workplace. Further work is required to validate these archetypes by capturing actual user behaviour and preferences in real workplaces. However, these findings provide preliminary and valuable insights into the possibility of clustering users on their preferences and using this for informing a more user-centred design or operation of shading devices.
Greenery, sun exposure and ventilation of public spaces in residential units in TiranaTashi, P.; Tola, A.; Tashi, A.
doi: 10.1088/1742-6596/2600/13/132014pmid: N/A
When referring to residential units, well-ventilated and lit green spaces are considerable contributors to increasing the quality of life of its residents. This research aims to analyse the transformation of the spaces between the buildings in the context of Tirana, by simultaneously stressing the key distinctions between their original design and their current situation. A typical residential complex close to Tirana’s centre is used as a case study to further illustrate this topic. The research starts with a qualitative morphological analysis of greenery, lighting, and ventilation condition of public space between residential units. It expands with a quantitative-comparative analysis, based on questionnaires conducted with residents, as well as by-passers of the selected residential area. The apparent reduction of greenery in spaces between residential units was one of the study’s most obvious findings. Originally intended as green spaces, public spaces between residential units have since been used for a variety of purposes, including being occupied by extensions of buildings or open parking lots. These interventions have resulted in a shift of usage to the inner streets of the residential block, which are now used for vehicles and are no longer either quiet or exclusively dedicated to pedestrians. The overall value of this space has been transferred from a straightforward recreational area to an economic space. Consequently, designers and urban planners have a responsibility to re-evaluate the significance of green surfaces, in addition to the shape and orientation of the residential unit as a foundation of sustainable urban development.