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Dive into the research topics where Leslie K. Norford is active.

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Featured researches published by Leslie K. Norford.


Automation in Construction | 2002

A design optimization tool based on a genetic algorithm

Luisa Gama Caldas; Leslie K. Norford

Abstract Much interest has been recently devoted to generative processes in design. Advances in computational tools for design applications, coupled with techniques from the field of artificial intelligence, have lead to new possibilities in the way computers can inform and actively interact with the design process. In this paper, we use the concepts of generative and goal-oriented design to propose a computer tool that can help the designer to generate and evaluate certain aspects of a solution towards an optimized behavior of the final configuration. This work focuses mostly on those aspects related to the environmental performance of buildings. Genetic Algorithms (GAs) are applied as a generative and search procedure to look for optimized design solutions in terms of thermal and lighting performance in a building. The GA is first used to generate possible design solutions, which are then evaluated in terms of lighting and thermal behavior using a detailed thermal analysis program (DOE2.1E). The results from the simulations are subsequently used to further guide the GA search towards finding low-energy solutions to the problem under study. Solutions can be visualized using an AutoLisp routine. The specific problem addressed in this study is the placing and sizing of windows in an office building. The same method is applicable to a wide range of design problems like the choice of construction materials, design of shading elements, or sizing of lighting and mechanical systems for buildings.


Energy and Buildings | 1996

Non-intrusive electrical load monitoring in commercial buildings based on steady-state and transient load-detection algorithms

Leslie K. Norford; Steven B. Leeb

Abstract Increased interest in energy scorekeeping, load forecasting and improved control of electricity-consuming equipment has focused attention on the instrumentation required to obtain the desired data. Work performed by the authors and other researchers has shown that individual loads can be detected and separated from rapid sampling of power at a single point serving a number of pieces of equipment, for example the electrical service entrance for an entire house or all of the central space-conditioning equipment in a commercial building. This technique has worked well in tests in houses but faces more difficult challenges in commercial buildings. We present our results for this centralized or non-intrusive load monitoring technique, applied to the space-conditioning equipment in an office/laboratory building in which equipment start-up and shut-down was centrally observed and analyzed on the basis of changes in steady-state power. We further describe our enhanced technique for distinguishing loads by matching start-up transients to known patterns, and present laboratory tests of fully automated detection hardware and software.


IEEE Transactions on Instrumentation and Measurement | 2008

Nonintrusive Load Monitoring and Diagnostics in Power Systems

Steven R. Shaw; Steven B. Leeb; Leslie K. Norford; Robert W. Cox

This paper describes a transient event classification scheme, system identification techniques, and implementation for use in nonintrusive load monitoring. Together, these techniques form a system that can determine the operating schedule and find parameters of physical models of loads that are connected to an AC or DC power distribution system. The monitoring system requires only off-the-shelf hardware and recognizes individual transients by disaggregating the signal from a minimal number of sensors that are installed at a central location in the distribution system. Implementation details and field tests for AC and DC systems are presented.


Environment International | 2015

The rise of low-cost sensing for managing air pollution in cities.

Prashant Kumar; Lidia Morawska; Claudio Martani; G. Biskos; Marina K.-A. Neophytou; Silvana Di Sabatino; Margaret Bell; Leslie K. Norford; Re Britter

Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, while addressing the major challenges for their effective implementation.


Journal of Solar Energy Engineering-transactions of The Asme | 2003

Genetic Algorithms for Optimization of Building Envelopes and the Design and Control of HVAC Systems

Luisa Caldas; Leslie K. Norford

Many design problems related to buildings involve minimizing capital and operating costs while providing acceptable service. Genetic algorithms (GAs) are an optimization method that has been applied to these problems. GAs are easily configured, an advantage that often compensates for a sacrifice in performance relative to optimization methods selected specifically for a given problem, and have been shown to give solutions where other methods cannot. This paper reviews the basics of GAs, emphasizing multi-objective optimization problems. It then presents several applications, including determining the size and placement of windows and the composition of building walls, the generation of building form, and the design and operation of HVAC systems. Future work is identified, notably interfaces between a GA and both simulation and CAD programs. @DOI: 10.1115/1.1591803#


IEEE Transactions on Energy Conversion | 2005

Estimation of variable-speed-drive power consumption from harmonic content

Kwangduk Douglas Lee; Steven B. Leeb; Leslie K. Norford; Peter R. Armstrong; Jack W. Holloway; Steven R. Shaw

Nonintrusive load monitoring can be used to identify the operating schedule of individual loads strictly from measurements of an aggregate power signal. Unfortunately, certain classes of loads present a continuously varying power demand. The power demand of these loads can be difficult to separate from an aggregate measurement. Variable-speed drives (VSDs) are industrially important variable-demand loads that are difficult to track non-intrusively. This paper proposes a VSD power estimation method based on observed correlations between fundamental and higher harmonic spectral content in current. The technique can be generalized to any load with signature correlations in harmonic content, including many power electronic and electromechanical loads. The approach presented here expands the applicability and field reliability of nonintrusive load monitoring.


Building and Environment | 2014

Improving air quality in high-density cities by understanding the relationship between air pollutant dispersion and urban morphologies

Chao Yuan; Edward Ng; Leslie K. Norford

Abstract In high-density megacities, air pollution has a higher impact on public health than cities of lower population density. Apart from higher pollution emissions due to human activities in densely populated street canyons, stagnated air flow due to closely packed tall buildings means lower dispersion potential. The coupled result leads to frequent reports of high air pollution indexes at street-side stations in Hong Kong. High-density urban morphologies need to be carefully designed to lessen the ill effects of high density urban living. This study addresses the knowledge-gap between planning and design principles and air pollution dispersion potentials in high density cities. The air ventilation assessment for projects in high-density Hong Kong is advanced to include air pollutant dispersion issues. The methods in this study are CFD simulation and parametric study. The SST κ–ω model is adopted after balancing the accuracy and computational cost in the comparative study. Urban-scale parametric studies are conducted to clarify the effects of urban permeability and building geometries on air pollution dispersion, for both the outdoor pedestrian environment and the indoor environment in the roadside buildings. Given the finite land resources in high-density cities and the numerous planning and design restrictions for development projects, the effectiveness of mitigation strategies is evaluated to optimize the benefits. A real urban case study is finally conducted to demonstrate that the suggested design principles from the parametric study are feasible in the practical high density urban design.


Hvac&r Research | 2002

Demonstration of Fault Detection and Diagnosis Methods for Air-Handling Units

Leslie K. Norford; Jonathan A. Wright; Richard A. Buswell; Dong Luo; C. J. Klaassen; A. Suby

Results are presented from controlled field tests of two methods for detecting and diagnosing faults in HVAC equipment. The tests were conducted in a unique research building that featured two air-handling units serving matched sets of unoccupied rooms with adjustable internal loads. Tests were also conducted in the same building on a third air handler serving areas used for instruction and by building staff. One of the two fault detection and diagnosis (FDD) methods used first-principles-based models of system components. The data used by this approach were obtained from sensors typically installed for control purposes. The second method was based on semiempirical correlations of submetered electrical power with flow rates or process control signals. Faults were introduced into the air-mixing, filter-coil, and fan sections of each of the three air-handling units. In the matched air-handling units, faults were implemented over three blind test periods (summer, winter, and spring operating conditions). In each test period, the precise timing of the implementation of the fault conditions was unknown to the researchers. The faults were, however, selected from an agreed set of conditions and magnitudes, established for each season. This was necessary to ensure that at least some magnitudes of the faults could be detected by the FDD methods during the limited test period. Six faults were used for a single summer test period involving the third air-handling unit. These fault conditions were completely unknown to the researchers and the test period was truly blind. The two FDD methods were evaluated on the basis of their sensitivity, robustness, the number of sensors required, and ease of implementation. Both methods detected nearly all of the faults in the two matched air-handling units but fewer of the unknown faults in the third air-handling unit. Fault diagnosis was more difficult than detection. The first-principles-based method misdiagnosed several faults. The electrical power correlation method demonstrated greater success in diagnosis, although the limited number of faults addressed in the tests contributed to this success. The first-principles-based models require a larger number of sensors than the electrical power correlation models, although the latter method requires power meters that are not typically installed. The first-principles-based models require training data for each subsystem model to tune the respective parameters so that the model predictions more precisely represent the target system. This is obtained by an open-loop test procedure. The electrical power correlation method uses polynomial models generated from data collected from “normal” system operation, under closed-loop control. Both methods were found to require further work in three principal areas: to reduce the number of parameters to be identified; to assess the impact of less expensive or fewer sensors; and to further automate their implementation. The first-principles-based models also require further work to improve the robustness of predictions.


Journal of Building Performance Simulation | 2013

The urban weather generator

Bruno Bueno; Leslie K. Norford; Julia Hidalgo; Grégoire Pigeon

The increase in air temperature produced by urbanization, a phenomenon known as the urban heat island (UHI) effect, is often neglected in current building energy simulation practices. The UHI effect can have an impact on the energy consumption of buildings, especially those with low internal heat gains or with an inherent close interaction with the outdoor environment (e.g. naturally-ventilated buildings). This paper presents an urban weather generator (UWG) to calculate air temperatures inside urban canyons from measurements at an operational weather station located in an open area outside a city. The model can be used alone or integrated into existing programmes in order to account for the UHI effect in building energy simulations. The UWG is evaluated against field data from Basel (Switzerland) and Toulouse (France). The error of UWG predictions stays within the range of air temperature variability observed in different locations of the same urban area.


applied power electronics conference | 2006

Transient event detection for nonintrusive load monitoring and demand side management using voltage distortion

Robert W. Cox; Steven B. Leeb; Steven R. Shaw; Leslie K. Norford

This paper describes a simple system that can be used for autonomous demand-side management in a load site such as a home or commercial facility. The system identifies the operation of individual loads using transient patterns observed in the voltage waveform measured at an electric service outlet. The theoretical foundation of the measurement process is introduced, and a preprocessor that computes short-time estimates of the spectral content of the voltage waveform is described. The paper presents several example measurements demonstrating the ability of the system to obtain estimates of the spectral content of the voltage waveform.

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Jianmin Miao

Nanyang Technological University

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Steven B. Leeb

Massachusetts Institute of Technology

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Peter R. Armstrong

Masdar Institute of Science and Technology

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Re Britter

Massachusetts Institute of Technology

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Jin Wu

Nanyang Technological University

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Kai Tao

Northwestern Polytechnical University

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Afshin Afshari

Masdar Institute of Science and Technology

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Bruno Bueno

Massachusetts Institute of Technology

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Christopher Laughman

Mitsubishi Electric Research Laboratories

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Dara Entekhabi

Massachusetts Institute of Technology

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