Using Personal Environmental Comfort Systems to Mitigate the Impact of Occupancy Prediction Errors on HVAC Performance

Heating, Ventilation and Air Conditioning (HVAC) consumes a significant fraction of energy in commercial buildings. Hence, the use of optimization techniques to reduce HVAC energy consumption has been widely studied. Model predictive control (MPC) is one state of the art optimization technique for HVAC control which converts the control problem to a sequence of optimization problems, each over a finite time horizon. In a typical MPC, future system state is estimated from a model using predictions of model inputs, such as building occupancy and outside air temperature. Consequently, as prediction accuracy deteriorates, MPC performance--in terms of occupant comfort and building energy use--degrades. In this work, we use a custom-built building thermal simulator to systematically investigate the impact of occupancy prediction errors on occupant comfort and energy consumption. Our analysis shows that in our test building, as occupancy prediction error increases from 5\% to 20\% the performance of an MPC-based HVAC controller becomes worse than that of even a simple static schedule. However, when combined with a personal environmental control (PEC) system, HVAC controllers are considerably more robust to prediction errors. Thus, we quantify the effectiveness of PECs in mitigating the impact of forecast errors on MPC control for HVAC systems.Comment: 21 pages, 13 figure

SDS-200 : a Swiss German speech to Standard German text corpus

We present SDS-200, a corpus of Swiss German dialectal speech with Standard German text translations, annotated with dialect, age, and gender information of the speakers. The dataset allows for training speech translation, dialect recognition, and speech synthesis systems, among others. The data was collected using a web recording tool that is open to the public. Each participant was given a text in Standard German and asked to translate it to their Swiss German dialect before recording it. To increase the corpus quality, recordings were validated by other participants. The data consists of 200 hours of speech by around 4000 different speakers and covers a large part of the Swiss German dialect landscape. We release SDS-200 alongside a baseline speech translation model, which achieves a word error rate (WER) of 30.3 and a BLEU score of 53.1 on the SDS-200 test set. Furthermore, we use SDS-200 to fine-tune a pre-trained XLS-R model, achieving 21.6 WER and 64.0 BLEU

The impact of occupants’ behaviours on building energy analysis: A research review

Over the past 15 years, the evaluation of energy demand and use in buildings has become increasingly acute due to growing scientific and political pressure around the world in response to climate change. The estimation of the use of energy in buildings is therefore a critical process during the design stage. This paper presents a review of the literature published in leading journals through Science Direct and Scopus databases within this research domain to establish research trends, and importantly, to identify research gaps for future investigation. It has been widely acknowledged in the literature that there is an alarming performance gap between the predicted and actual energy consumption of buildings (sometimes this has been up to 300% difference). Analysis of the impact of occupants’ behaviour has been largely overlooked in building energy performance analysis. In short, energy simulation tools utilise climatic data and physical/ thermal properties of building elements in their calculations, and the impact of occupants is only considered through means of fixed and scheduled patterns of behaviour. This research review identified a number of areas for future research including: larger scale analysis (e.g. urban analysis); interior design, in terms of space layout, and fixtures and fittings on occupants’ behaviour; psychological cognitive behavioural methods; and the integration of quantitative and qualitative research findings in energy simulation tools to name but a few