Optical Indoor Positioning System Based on TFT Technology

A novel indoor positioning system is presented in the paper. Similarly to the camera-based solutions, it is based on visual detection, but it conceptually differs from the classical approaches. First, the objects are marked by LEDs, and second, a special sensing unit is applied, instead of a camera, to track the motion of the markers. This sensing unit realizes a modified pinhole camera model, where the light-sensing area is fixed and consists of a small number of sensing elements (photodiodes), and it is the hole that can be moved. The markers are tracked by controlling the motion of the hole, such that the light of the LEDs always hits the photodiodes. The proposed concept has several advantages: Apart from its low computational demands, it is insensitive to the disturbing ambient light. Moreover, as every component of the system can be realized by simple and inexpensive elements, the overall cost of the system can be kept low

An investigation into hybrid power trains for vehicles with regenerative braking

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Inverse Dynamics based Energy Assessment and Simulation : IDEAS

The Standard Assessment Procedure (SAP) is the UK Government’s approved methodology for assessing the energy ratings of dwellings. SAP is a calculation method based upon empirical relations from measured data. A yearly calculation was used in SAP until the release of SAP 2009, which employs monthly calculations. SAP has moved from using a large time step with a coarse time resolution to a smaller time step with a medium time resolution. Rising CO2 emissions from dwellings advocate that properties designed in a sustainable method will become commonplace in the future. In tandem with enhanced sustainability, dwellings will increasingly be designed with implementations of renewable energy generation. The modelling of renewables in SAP has been highlighted as an area where SAP could benefit from additional research. Modelling future complex dwellings and systems will require an advanced calculation method which is capable of more detailed modelling and simulation; with a smaller time step which is measured in minutes and not months, producing results allowing more detailed analysis of energy performance. Dynamic Simulation Methods (DSMs) already exist which can operate at a very small time step. However with DSMs it is very difficult to make a comparison with SAP as the temperatures used in SAP are not well understood. To calculate energy consumption the SAP methodology guarantees that a standard occupancy temperature profile is met perfectly. A dynamic method which also guarantees the SAP standard occupancy temperature profile is required. This is difficult in complex DSMs as their control algorithms are often inadequate to optimise the heating system to guarantee that a temperature is met perfectly. The contribution to knowledge detailed in this thesis is the development of a novel SAP compliant advanced dynamic calculation method (IDEAS) which guarantees that the SAP standard occupancy temperature profile is perfectly tracked and is also calibrated with SAP. The Inverse Dynamics based Energy Assessment and Simulation (IDEAS) method employs the perfect inverse control law RIDE to guarantee that the SAP standard occupancy temperature profile is met. IDEAS produces SAP compliant results and allows confident (i.e. calibrated in SAP) predictions to be made regarding the impact of novel heating and renewable energy systems. Researched in depth are the temperatures used in SAP, leading to analysis of the implications of tracking air temperature and various comfort temperatures. A focused evaluation of the treatment of renewables in SAP and DSMs is also presented, leading to suggestions which were implemented into the SAP framework. The role of real life monitoring in the energy assessment process is highlighted with monitored studies conducted. Also in this thesis case studies applying IDEAS to buildings with renewable heating systems are described. The IDEAS method employs SAP as an exemplar steady state calculation to highlight the successful use and calibration of a new advanced Inverse Dynamics based symbolic method. The philosophy, research and equations derived in IDEAS are presented in this thesis demonstrating their use in Microsoft Excel and Matlab / Simulink environments. The IDEAS methodology is transparent and portable. IDEAS can be applied to other methodologies, such as those employed by PHPP and SBEM (by carrying out a calibration process), and also to different simulation environments such as ESP-r and ESL (by adopting the IDEAS equations in those methods). The contribution to knowledge of IDEAS is demonstrated in this thesis by the development of the method and the use of SAP as a comparator. The IDEAS method has many uses outwith SAP which are highlighted in the cases studies and future work sections of this body of work

Design of a Digital Choral Folder

Advances in electronic displays have led to the creation of electronic readers such as the Amazon Kindle. Electronic paper (e-paper) technology combines the benefits of electronic displays without many of their typical disadvantages. The goal of this project was to bring e-paper to the realm of choral sheet music by designing a digital choral folder. The project involved digital circuit design and embedded microprocessor programming. This report details the design process for developing a Digital Choral Folder with e-paper, as well as recommendations for completing the design. Portions of this report have been redacted to comply with a non-disclosure agreement. The author and project adviser have copies of the complete report

Transfer Learning in Transformer-Based Demand Forecasting For Home Energy Management System

Increasingly, homeowners opt for photovoltaic (PV) systems and/or battery storage to minimize their energy bills and maximize renewable energy usage. This has spurred the development of advanced control algorithms that maximally achieve those goals. However, a common challenge faced while developing such controllers is the unavailability of accurate forecasts of household power consumption, especially for shorter time resolutions (15 minutes) and in a data-efficient manner. In this paper, we analyze how transfer learning can help by exploiting data from multiple households to improve a single house's load forecasting. Specifically, we train an advanced forecasting model (a temporal fusion transformer) using data from multiple different households, and then finetune this global model on a new household with limited data (i.e. only a few days). The obtained models are used for forecasting power consumption of the household for the next 24 hours~(day-ahead) at a time resolution of 15 minutes, with the intention of using these forecasts in advanced controllers such as Model Predictive Control. We show the benefit of this transfer learning setup versus solely using the individual new household's data, both in terms of (i) forecasting accuracy ($\sim$15\% MAE reduction) and (ii) control performance ($\sim$2\% energy cost reduction), using real-world household data.Comment: 7 pages, 2 figures, workshop article at BALANCES, BuildSys'2