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Open Access Publications from the University of California
Cover page of Sensitivity of passive design strategies to climate change

Sensitivity of passive design strategies to climate change

(2018)

Observed global warming trends undermine the conventional practice of using historic weather files, such as Typical Meteorological Year (TMY), to predict building performance during the design process. In order to limit adverse impacts such as improperly sized mechanical equipment or thermal discomfort, it is important to consider how the building will perform in the future. Like all passive design strategies, natural ventilation, relies on local climate to be effective in improving building performance. This paper combines future weather files with whole building energy simulations to assess the sensitivity and feasibility of natural ventilation in providing thermal comfort in three locations, representing different climate types. The results show how building performance, as measured by thermal comfort metrics, changes over time. Natural ventilation can provide a buffer against warming climate, but only to a certain extent. Future weather files are useful for identifying where and when there is a risk that an exclusively passive design is no longer possible.

Cover page of Designing for the future: Are today’s building codes locking in the wrong strategies by using past climate data?

Designing for the future: Are today’s building codes locking in the wrong strategies by using past climate data?

(2018)

California has set goals for zero net energy buildings and greenhouse gas emissions reductions that will be achieved in part through the state’s building energy codes. Decisions about what measures to include in code are informed by building energy models that rely on historical climate data. However, even under moderate emissions scenarios, by 2050 mean temperatures in California are projected to increase by almost 4 degrees Fahrenheit compared to pre-1990 levels and there is evidence that current day temperatures are already shifted from the historical record. Not only do these energy models underlie cost-effectiveness analyses which influence the prescriptive code, they inform building system selection and sizing, and they are the basis for program incentive awards. While the general trends are predictable – as temperatures increase, average cooling energy increases and heating decreases – the effects of future climate on the state’s building policies have not been thoroughly analyzed. To what extent will lower winter heating loads increase the business case for buildings to electrify? Under future climate, are increased cooling efficiency measures cost-effective that aren’t today? How will future climate affect the energy and emissions performance of California’s buildings and what policies can be adopted today to future-proof them? This paper starts to address these questions by examining the performance of prototype buildings within a subset of California’s climate zones under past and future climate scenarios. It models energy efficiency measure variants to these prototypes and compares the energy, emission, cost, and thermal load outcomes under future climate scenarios compared to historical design weather and makes policy recommendations based on the results.

Cover page of PMV-based event-triggered mechanism for building energy management under uncertainties

PMV-based event-triggered mechanism for building energy management under uncertainties

(2017)

This paper provides a study of the optimal scheduling of building operation to minimize its energy cost under building operation uncertainties. Opposed to the usual way that describes thermal comfort using a static range of air temperature, the optimization of a tradeoff between energy cost and thermal comfort predicted mean vote (PMV) index is addressed in this paper. In order to integrate the calculation of the PMV index with the optimization procedure, we develop a sufficiently accurate approximation of the original PMV model which is computationally efficient. We develop a model-based periodic event-triggered mechanism (ETM) to handle the uncertainties in the building operation. Upon the triggering of predefined events, the ETM determines whether the optimal strategy should be recalculated. In this way, the communication and computational resources required can be significantly reduced. Numerical results show that the ETM method is robust with respect to the uncertainties in prediction errors and results in a reduction of more than 60% in computation without perceivable degradation in system performance as compared to a typical closed-loop model predictive control.

Cover page of Measuring the effectiveness of San Francisco's planning standard for pedestrian wind comfort

Measuring the effectiveness of San Francisco's planning standard for pedestrian wind comfort

(2016)

In 1985, San Francisco adopted a wind comfort standard in its Downtown Area Plan in response to increasing concerns about the city’s downtown public open spaces becoming excessively windy. After 30 years of implementation, this study revisits the standard and examines its effectiveness in promoting pedestrian comfort. 701 valid samples were collected from 6 months of field study, which combined surveying pedestrians and on-site collection of microclimate data. Statistical analysis and an assessment using the physiological equivalent temperature (PET) show that 11 mph (4.92 m/s), the comfort criterion in places for walking, performs as an effective determinant of outdoor comfort in San Francisco. This study sheds light on climate-resilience of cities as they have become key urban challenges today.

Cover page of Performance, Prediction and Optimization of Night Ventilation across Different Climates

Performance, Prediction and Optimization of Night Ventilation across Different Climates

(2016)

Night ventilation, or night flushing, is a passive cooling technique that utilizes the outdoor diurnal temperature swing and the building’s thermal mass to pre-cool a building through increased outdoor airflow at night, allowing radiant cooling to take place during the day when the building is occupied.  Previous studies have demonstrated a potential reduction in cooling load and improvement in comfort from the implementation of night ventilation.  However, very few field studies have been done looking at the impact of location and climate on night ventilation performance.

 

This thesis describes the performance, in terms of indoor environmental conditions, of three buildings from both the U.S. and India that use night ventilation as their primary cooling method.  The analysis is based on monitored data collected from each building (ranging in duration from two months to one year), including indoor and outdoor air temperature, mass temperature, supply temperature, and airflow rate. The first building, located in Oakland, California, uses forced ventilation at night to increase the airflow.  The second building, located in Sunnyvale, California, uses natural ventilation by means of automated windows.  The third building, in Auroville, India, uses natural ventilation by means of occupant-controlled windows.  The research methods used the following approach: 1) Assess the cooling strategy by comparing indoor conditions from days that did and did not use night ventilation, specifically in relation to the adaptive comfort model;  2) Develop a hybrid model, using both first principle equations and the collected data, to predict the instantaneous air and mass temperatures within each building; 3) Determine an optimized ventilation control strategy for each building to minimize energy and maintain comfortable temperatures.

 

The study yielded the following results: 1) The buildings in the mild climate are successfully keeping the indoor temperature low, but also tend to be overcooling;  2) The night ventilation strategy has very little impact on the indoor conditions of the buildings in the mild climate; 3) The impact of night ventilation is less significant when there is low internal loads and heavy mass; 4) The building in the hot and humid climate is keeping the indoor temperature within the comfort bounds for 88% of the year; 5) The night ventilation strategy has advantageous impact on indoor conditons of the building in the hot and humid climate, but not enough to cool the space on its own; 6) Model predictive control has the potential to further improve the performance of night ventilation.

Cover page of Does Wind Discourage Sustainable Transportation Mode Choice? Findings from San Francisco, California, USA

Does Wind Discourage Sustainable Transportation Mode Choice? Findings from San Francisco, California, USA

(2016)

This paper explores whether and to what extent wind discourages sustainable transportation mode choice, which includes riding public transportation, bicycling, and walking. A six month-long field study was carried out at four locations in San Francisco, a city that has been promoting sustainable transportation mode choice but that experiences high wind levels. It involved surveying pedestrians and on-site recording of microclimate data using various instruments. The survey adopted a mixed-method approach to collect both quantitative and qualitative data. Statistical analyses using Kruskal Wallis tests and ordinal logistic regression models identified the significant effect of wind speed on San Francisco’s residents in estimating their discouragement for waiting at transit stop without shelter, bicycling, and walking. Qualitative data revealed a deeper understanding of how wind influences their sustainable transportation mode choice. This research argues for the need to adopt climate-based efforts in urban planning and policy and sheds light on the climate resilience of cities

Cover page of Wind and the city: An evaluation of San Francisco's planning approach since 1985

Wind and the city: An evaluation of San Francisco's planning approach since 1985

(2015)

In 1985, San Francisco adopted a downtown plan on ground-level wind currents intended to mitigate the negative effects of wind on pedestrians’ perceived comfort in public open spaces. The plan mandates that new buildings in designated parts of the city associated with high density or development potential be designed or adopt measures to not cause wind in excess of accepted comfort levels. This study examines whether and to what degree the plan has successfully shaped an urban form that mitigates wind by comparing the ground-level wind environment in 1985 and 2013. A series of wind tunnel tests found that during San Francisco’s windiest season when the westerly winds are prevalent, the overall mean wind speed ratio measured at 318 locations in four areas of the city dropped by 22 percent. However, there still exist many excessively windy places that are associated with specific urban form conditions, including streets oriented to have direct exposure to westerly winds, flat façades on high-rise buildings, and horizontal street walls where building façades align. Recommendations based on the findings include incorporating more tangible guidance on the built form conditions, expanding the plan’s reach to cover more parts of the city, and learning from strategies used elsewhere. By evaluating the urban form impacts of a wind mitigation policy that has been in place for 30 years, the research offers insights for other cities that have implemented or plan to adopt similar approach and sheds light on issues related to wind comfort in high-density urban areas.

Cover page of Commercial Office Plug Load Energy Consumption Trends and the Role of Occupant Behavior

Commercial Office Plug Load Energy Consumption Trends and the Role of Occupant Behavior

(2015)

Plug loads are an increasingly important end-use in commercial office buildings. They currently account for 12-50% of total commercial building energy consumption, and as the efficiencies ofregulated major end-uses, such as space conditioning and lighting systems, continue to increase, plugload energy use is expected to rise. This study evaluates patterns in collected plug load data and the effect of a behavior-based intervention to reduce plug load energy consumption.This project leverages a data collection effort originally funded for a study by the California AirResources Board, where 100 plug load monitoring power strips were installed at individualworkstations in the Franklin Building, an office building in Oakland owned by the UC Office of thePresident (UCOP). Each occupant received one power strip and connected up to four devices to beindividually monitored.  For this project, only the labeled devices (desktop, laptop, monitor, task light)are included. An analysis of the collected data reveals a clear distinction between work days and non-work days(weekends and holidays). Overall, the monitored occupants have regular work schedules, turn off theirequipment at the end of the work day, and do not often stay late or come in on the weekends. Desktops consume the most power per person, followed by monitors and then task lights. Laptop power trendswere more difficult to discern because users often disconnect them to work in other locations (that werenot monitored).  Desktops demonstrate the widest range of power consumption among the devicesmonitored. During unoccupied periods (overnight and on non-work days), desktops draw the mostpower, followed by laptops. All devices draw more power overnight on work days than over weekendsand holidays, indicating that users are more likely to turn equipment off before a longer break from theoffice. Much of the literature on reducing plug load energy consumption in commercial buildings is focusedon technology-based solutions, such as purchasing new equipment or installing sophisticated controlsto turn off equipment when not in use. The literature on changing occupant behavior to reduce energyuse is focused on residential occupants, however multiple studies show that even when occupants donot pay their own bills and have no financial incentive to save energy, other factors can encouragebehavior change.  One such motivating method is by using gamification, or turning an everyday activity into a game to encourage behavior change by making it more fun and interesting.With the help of leadership at UCOP, an online sustainability game, Cool Choices, was initiated in theFall of 2014 and 30 employees signed up to play. Cool Choices encourages occupant behavior changesto save water, energy, and reduce waste; players earn points for each action they complete at work or athome and compete with each other on teams.  Survey responses from game participants showed thatplayers were motivated to play because the game looked fun, and because the actions suggested wereeasy to perform. An analysis of the energy impact revealed that because occupants were alreadyengaging in relevant energy saving behaviors (e.g. turning equipment off at the end of the day), therewas limited opportunity for further behavior-based reductions. Using trends identified in the baseline analysis, a simplified plug load model was developed to predictpower consumption based on device type, day type (work day or non-work day), and time step, using aMonte Carlo simulation.  The model used day type and time step as proxies for occupancy, so when occupancy was not well predicted by the work day/non-work day dichotomy, the model becameincreasingly unreliable. Even after adding an additional variable (month), the model was still not ableto predict power consumption to an acceptable degree of accuracy per industry standards. The model demonstrated a need for a new, more accurate proxy for occupancy, perhaps based on individualoccupants, rather than devices.