Limitations of machine learning for building energy prediction: ASHRAE Great Energy Predictor III Kaggle competition error analysis

Machine learning for building energy prediction has exploded in popularity in recent years, yet understanding its limitations and potential for improvement are lacking. The ASHRAE Great Energy Predictor III (GEPIII) Kaggle competition was the largest building energy meter machine learning competition ever held with 4,370 participants who submitted 39,403 predictions. The test data set included two years of hourly electricity, hot water, chilled water, and steam readings from 2,380 meters in 1,448 buildings at 16 locations. This paper analyzes the various sources and types of residual model error from an aggregation of the competition's top 50 solutions. This analysis reveals the limitations for machine learning using the standard model inputs of historical meter, weather, and basic building metadata. The types of error are classified according to the amount of time errors occur in each instance, abrupt versus gradual behavior, the magnitude of error, and whether the error existed on single buildings or several buildings at once from a single location. The results show machine learning models have errors within a range of acceptability on 79.1% of the test data. Lower magnitude model errors occur in 16.1% of the test data. These discrepancies can likely be addressed through additional training data sources or innovations in machine learning. Higher magnitude errors occur in 4.8% of the test data and are unlikely to be accurately predicted regardless of innovation. There is a diversity of error behavior depending on the energy meter type (electricity prediction models have unacceptable error in under 10% of test data, while hot water is over 60%) and building use type (public service less than 14%, while technology/science is just over 46%)

Condensation-free radiant cooling using infrared-transparent enclosures of chilled panels

Radiant cooling power in the humid climates is inherently limited by condensation. This research investigates a type of radiant cooling methodology whereby the cold temperature source is convectively and conductively isolated from the environment with a membrane transparent to visible radiation to allow supply temperatures to be decreased for radiant cooling systems in humid climates. We conduct an FTIR analysis on three candidate membrane materials and fabricate a prototype experimental test panel that allows for thermal performance evaluation at different panel orientation and depths. Our study shows that for a 5 °C chilled panel temperature, the exterior membrane surface temperature reaches 26 °C in a 32 °C / 70% RH environment resulting in an effective panel temperature of 15.8 °C. Such a panel construction would avoid condensation in many humid environments and allow for radiant cooling without any latent load handling

Optimizing Radiant Systems for Energy Efficiency and Comfort

Radiant cooling and heating systems provide an opportunity to achieve significant energy savings, peak demand reduction, load shifting, and thermal comfort improvements compared to conventional all-air systems. As a result, application of these systems has increased in recent years, particularly in zero-net-energy (ZNE) and other advanced low-energy buildings. Despite this growth, completed installations to date have demonstrated that controls and operation of radiant systems can be challenging due to a lack of familiarity within the heating, ventilation, and air-conditioning (HVAC) design and operations professions, often involving new concepts (particularly related to the slow response in high thermal mass radiant systems). To achieve the significant reductions in building energy use proposed by California Public Utilities Commission’s (CPUC’s) Energy Efficiency Strategic Plan that all new non-residential buildings be ZNE by 2030, it is critical that new technologies that will play a major role in reaching this goal be applied in an effective manner. This final report describes the results of a comprehensive multi-faceted research project that was undertaken to address these needed enhancements to radiant technology by developing the following: (1) sizing and operation tools (currently unavailable on the market) to provide reliable methods to take full advantage of the radiant systems to provide improved energy performance while maintaining comfortable conditions, (2) energy, cost, and occupant comfort data to provide real world examples of energy efficient, affordable, and comfortable buildings using radiant systems, and (3) Title-24 and ASHRAE Standards advancements to enhance the building industry’s ability to achieve significant energy efficiency goals in California with radiant systems. The research team used a combination of full-scale fundamental laboratory experiments, whole-building energy simulations and simplified tool development, and detailed field studies and control demonstrations to assemble the new information, guidance and tools necessary to help the building industry achieve significant energy efficiency goals for radiant systems in California

Influenza A (H3) illness and viral aerosol shedding from symptomatic naturally infected and experimentally infected cases

BackgroundIt has long been known that nasal inoculation with influenza A virus produces asymptomatic to febrile infections. Uncertainty persists about whether these infections are sufficiently similar to natural infections for studying human‐to‐human transmission.MethodsWe compared influenza A viral aerosol shedding from volunteers nasally inoculated with A/Wisconsin/2005 (H3N2) and college community adults naturally infected with influenza A/H3N2 (2012‐2013), selected for influenza‐like illness with objectively measured fever or a positive Quidel QuickVue A&B test. Propensity scores were used to control for differences in symptom presentation observed between experimentally and naturally infected groups.ResultsEleven (28%) experimental and 71 (86%) natural cases shed into fine particle aerosols (P [less than] .001). The geometric mean (geometric standard deviation) for viral positive fine aerosol samples from experimental and natural cases was 5.1E + 3 (4.72) and 3.9E + 4 (15.12) RNA copies/half hour, respectively. The 95th percentile shedding rate was 2.4 log10 greater for naturally infected cases (1.4E + 07 vs 7.4E + 04). Certain influenza‐like illness‐related symptoms were associated with viral aerosol shedding. The almost complete lack of symptom severity distributional overlap between groups did not support propensity score–adjusted shedding comparisons. ConclusionsDue to selection bias, the natural and experimental infections had limited symptom severity distributional overlap precluding valid, propensity score–adjusted comparison. Relative to the symptomatic naturally infected cases, where high aerosol shedders were found, experimental cases did not produce high aerosol shedders. Studying the frequency of aerosol shedding at the highest observed levels in natural infections without selection on symptoms or fever would support helpful comparisons

Qualitative Real-Time Schlieren and Shadowgraph Imaging of Human Exhaled Airflows: An Aid to Aerosol Infection Control

Using a newly constructed airflow imaging system, airflow patterns were visualized that were associated with common, everyday respiratory activities (e.g. breathing, talking, laughing, whistling). The effectiveness of various interventions (e.g. putting hands and tissues across the mouth and nose) to reduce the potential transmission of airborne infection, whilst coughing and sneezing, were also investigated. From the digital video footage recorded, it was seen that both coughing and sneezing are relatively poorly contained by commonly used configurations of single-handed shielding maneuvers. Only some but not all of the forward momentum of the cough and sneeze puffs are curtailed with various hand techniques, and the remaining momentum is disseminated in a large puff in the immediate vicinity of the cougher, which may still act as a nearby source of infection. The use of a tissue (in this case, 4-ply, opened and ready in the hand) proved to be surprisingly effective, though the effectiveness of this depends on the tissue remaining intact and not ripping apart. Interestingly, the use of a novel ‘coughcatcher’ device appears to be relatively effective in containing coughs and sneezes. One aspect that became evident during the experimental procedures was that the effectiveness of all of these barrier interventions is very much dependent on the speed with which the user can put them into position to cover the mouth and nose effectively

Airflow Dynamics of Coughing in Healthy Human Volunteers by Shadowgraph Imaging: An Aid to Aerosol Infection Control

Cough airflow dynamics have been previously studied using a variety of experimental methods. In this study, real-time, non-invasive shadowgraph imaging was applied to obtain additional analyses of cough airflows produced by healthy volunteers. Twenty healthy volunteers (10 women, mean age 32.2±12.9 years; 10 men, mean age 25.3±2.5 years) were asked to cough freely, then into their sleeves (as per current US CDC recommendations) in this study to analyze cough airflow dynamics. For the 10 females (cases 1–10), their maximum detectable cough propagation distances ranged from 0.16–0.55 m, with maximum derived velocities of 2.2–5.0 m/s, and their maximum detectable 2-D projected areas ranged from 0.010–0.11 m2, with maximum derived expansion rates of 0.15–0.55 m2/s. For the 10 males (cases 11–20), their maximum detectable cough propagation distances ranged from 0.31–0.64 m, with maximum derived velocities of 3.2–14 m/s, and their maximum detectable 2-D projected areas ranged from 0.04–0.14 m2, with maximum derived expansion rates of 0.25–1.4 m2/s

Airflow Dynamics of Human Jets: Sneezing and Breathing - Potential Sources of Infectious Aerosols

10.1371/journal.pone.0059970PLoS ONE84