Bing Dong

Building energy and comfort management through occupant behaviour pattern detection based on a large-scale environmental sensor network

Detection of occupant presence has been used extensively in built environments for applications such as demand-controlled ventilation and security. However, the ability to discern the actual number of people in a room is beyond the scope of most current sensing techniques. To address this issue, a complex environmental sensor network is deployed in the Robert L. Preger Intelligent Workplace (IW) at Carnegie Mellon University. The results indicate that there are significant correlations between measured environmental conditions and occupancy status. It is shown that an average of 83% accuracy on the occupancy number detection was achieved by Gaussian Mixture Model based Hidden Markov Models during testing periods. To illustrate the consequent energy impact based on the occupant behaviour detection (i.e. number and duration of occupancy) in the space, an EnergyPlus model of the IW with an assumed standard variable air volume (VAV) system is created. Simulations are conducted to compare the energy consumption consequences between a prescribed occupancy schedule according to the ASHRAE 90.1 base case with the predicted occupancy behaviour. The results show that energy saving of 18.5% can be achieved in the IW while maintaining indoor thermal comfort.

An investigation on energy-related occupancy behavior for low-income residential buildings

Previous studies show that individuals’ energy consumption tends to outweigh the technical efficiency gains. Occupancy behavior accounts for about 30% of the variance in overall heating consumption and 50% in cooling consumption. In addition, overall energy savings of 10%–20% due to simple behavioral adjustments are a reasonable expectation. Unfortunately, few studies have focused on the specific cases of behavior in low-income houses, where unique individual energy behavior, demographic, and socio-economic factors come into play. This article investigates energy-related occupancy behavior in low-income families through real-time power, indoor environment, and occupancy presence measurement. Four residential houses with different building envelope materials are used as test-beds. Occupancy behavior includes thermostat schedules, occupancy presence, and major appliance usages. A simulation study is further conducted to show the energy impact of occupancy behavior.

LiDAR-Based Solar Mapping for Distributed Solar Plant Design and Grid Integration in San Antonio, Texas

This study represents advancements in the state-of-the-art of the solar energy industry by leveraging LiDAR-based building characterization for city-wide, distributed solar photovoltaics, solar maps, highlighting the distribution of solar energy across the city of San Antonio. A methodology is implemented to systematically derive the tilt and azimuth angles of each rooftop and to quantify solar direct, diffuse, and global horizontal irradiance for hundreds of buildings in a LiDAR tile scale, by using already established methodologies that are typically only applied to a single location or building rooftop. The methodology enables the formulation of typical meteorological data, measured or forecasted time series of irradiances over distributed assets. A new concept on the subject of distributed solar plant (DSP) design is also introduced, by using the building rooftop tilt and azimuth angles, to strategically optimize the use and adoption of solar incentives according to the grid age and its vulnerabilities to solar variability in the neighborhoods. The method presented here shows that on an hourly basis DSP design could provide a 5% and 9% of net load capacity support per hour in the afternoon and morning times, respectively. Our results show that standard building rooftop tilt angles in the south Texas region has significant impact on the total amount of the energy over the course of a day, though its impact on the shapes of the daily energy profile is relatively insignificant when compared to the azimuth angle. Building surfaces’ azimuth angle is the most important factor to determine the shape of daily energy profile and its peak location within a day. The methodology developed in this study can be employed to study the potential solar energy in other regions and to match the design of distributed solar plants to the capacity needs on specified distribution grids.

Advanced building energy management system demonstration for Department of Defense buildings

This paper presents an advanced building energy management system (aBEMS) that employs advanced methods of whole‐building performance monitoring combined with statistical methods of learning and data analysis to enable identification of both gradual and discrete performance erosion and faults. This system assimilated data collected from multiple sources, including blueprints, reduced‐order models (ROM) and measurements, and employed advanced statistical learning algorithms to identify patterns of anomalies. The results were presented graphically in a manner understandable to facilities managers. A demonstration of aBEMS was conducted in buildings at Naval Station Great Lakes. The facility building management systems were extended to incorporate the energy diagnostics and analysis algorithms, producing systematic identification of more efficient operation strategies. At Naval Station Great Lakes, greater than 20% savings were demonstrated for building energy consumption by improving facility manager decision support to diagnose energy faults and prioritize alternative, energy‐efficient operation strategies. The paper concludes with recommendations for widespread aBEMS success.

Stochastic parallel gradient descent based adaptive optics used for a high contrast imaging coronagraph

An adaptive optics (AO) system based on a stochastic parallel gradient descent (SPGD) algorithm is proposed to reduce the speckle noises in the optical system of a stellar coronagraph in order to further improve the contrast. The principle of the SPGD algorithm is described briefly and a metric suitable for point source imaging optimization is given. The feasibility and good performance of the SPGD algorithm is demonstrated by an experimental system featured with a 140-actuator deformable mirror and a Hartmann-Shark wavefront sensor. Then the SPGD based AO is applied to a liquid crystal array (LCA) based coronagraph to improve the contrast. The LCA can modulate the incoming light to generate a pupil apodization mask of any pattern. A circular stepped pattern is used in our preliminary experiment and the image contrast shows improvement from 10−3 to 10−4.5 at an angular distance of 2λ/D after being corrected by SPGD based AO.

A portable solar adaptive optics system: software and laboratory developments

We present our recent process on a portable solar adaptive Optics system, which is aimed for diffraction-limited imaging in the 1.0 ~ 5.0-μm infrared wavelength range with any solar telescope with an aperture size up to 1.6 meters. The realtime wave-front sensing, image processing and computation are based on a commercial multi-core personal computer. The software is developed in LabVIEW. Combining the power of multi-core imaging processing and LabVIEW parallel programming, we show that our solar adaptive optics can achieve excellent performance that is competitive with other systems. In addition, the LabVIEWs block diagram based programming is especially suitable for rapid development of a prototype system, which makes a low-cost and high-performance system possible. Our adaptive optics system is flexible; it can work with any telescope with or without central obstruction with any aperture size in the range of 0.6~1.6 meters. In addition, the whole system is compact and can be brought to a solar observatory to perform associated scientific observations. According to our knowledge, this is the first adaptive optics that adopts the LabVIEW high-level programming language with a multi-core commercial personal computer, and includes the unique features discussed above.

Buildings-to-Grid Integration Framework

This paper puts forth a mathematical framework for Buildings-to-Grid (BtG) integration in smart cities. The framework explicitly couples power grid and building’s control actions and operational decisions, and can be utilized by buildings and power grids operators to simultaneously optimize their performance. Simplified dynamics of building clusters and building-integrated power networks with algebraic equations are presented---both operating at different time-scales. A model predictive control (MPC)-based algorithm that formulates the BtG integration and accounts for the time-scale discrepancy is developed. The formulation captures dynamic and algebraic power flow constraints of power networks and is shown to be numerically advantageous. The paper analytically establishes that the BtG integration yields a reduced total system cost in comparison with decoupled designs where grid and building operators determine their controls separately. The developed framework is tested on standard power networks that include thousands of buildings modeled using industrial data. Case studies demonstrate building energy savings and significant frequency regulation, while these findings carry over in network simulations with nonlinear power flows and mismatch in building model parameters. Finally, simulations indicate that the performance does not significantly worsen when there is uncertainty in the forecasted weather and base load conditions.

Diffractive imaging analysis of large-aperture segmented telescope based on partial Fourier transform

Large-aperture segmented primary mirror will be widely used in next-generation space-based and ground-based telescopes. The effects of intersegment gaps, obstructions, position and figure errors of segments, which are all involved in the pupil plane, on the image quality metric should be analyzed using diffractive imaging theory. Traditional Fast Fourier Transform (FFT) method is very time-consuming and costs a lot of memory especially in dealing with large pupil-sampling matrix. A Partial Fourier Transform (PFT) method is first proposed to substantially speed up the computation and reduce memory usage for diffractive imaging analysis. Diffraction effects of a 6-meter segmented mirror including 18 hexagonal segments are simulated and analyzed using PFT method. The influence of intersegment gaps and position errors of segments on Strehl ratio is quantitatively analyzed by computing the Point Spread Function (PSF). By comparing simulation results with theoretical results, the correctness and feasibility of PFT method is confirmed.

Numerical analysis of modal tomography for solar multi-conjugate adaptive optics

Multi-conjugate adaptive optics (MCAO) can considerably extend the corrected field of view with respect to classical adaptive optics, which will benefit solar observation in many aspects. In solar MCAO, the Sun structure is utilized to provide multiple guide stars and a modal tomography approach is adopted to implement three-dimensional wavefront restorations. The principle of modal tomography is briefly reviewed and a numerical simulation model is built with three equivalent turbulent layers and a different number of guide stars. Our simulation results show that at least six guide stars are required for an accurate wavefront reconstruction in the case of three layers, and only three guide stars are needed in the two layer case. Finally, eigenmode analysis results are given to reveal the singular modes that cannot be precisely retrieved in the tomography process.

Validation and Ground Truths

It is essential to ensure the validation of measurements and the reliability of the collected data. This chapter discusses several topics related to measurement validation and ground truth in occupancy and occupant behavior observations. It introduces the basic concept of measurement quality and calls for attention to the measurement of occupancy and occupant actions. It provides general guidelines for verifying and validating the reliability of collected data. It also offers suggestions for how to construct ground truth data. In this chapter, questions about measurement validation and ground truth are raised and the particularities of occupancy and occupant behavior observations are discussed.