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The goal of the Distributed Intelligent Automated Demand Response (DIADR) project at UC Berkeley is to reduce peak load of Sutardja Dai Hall by 30% while maintaining a healthy, comfortable, and productive environment for the occupants. The team consists of members fromSiemens, UC Berkeley and Lawrence Berkeley National Laboratory.This paper describes the work in progress of achieving this goal in the office portion ofthe building given an overcooled building not fully commissioned, grossly oversized chillers, and problems isolating the nanofabrication laboratory. Most of the reduction comes from HVAC: increasing supply air and zone temperatures and reducing ventilation rates. Other reductionsinvolve dimming lights and turning off the tankless water heaters. Engaging the occupants of the building should provide further reduction. The web interface for the distributed load controller allows the prioritization of curtailable appliances and visualization of energy consumption. Aweb-based lighting controller allows the workers to easily control overhead lighting and encourages conservation.Several new tools have facilitated this work, such as the grid-to-building gateway and the web-based lighting controller. In addition, an innovative data aggregator called sMAP allowed detailed analysis of the building systems operation. A smart phone application (RAP) facilitated an inventory of the building’s plug loads. Occupants were initially administered a survey on indoor environmental quality; short surveys during interventions assessed satisfaction withindoor temperature, light levels, and air quality.We have made progress towards achieving deep demand response of 30% reduction ofpeak loads, and are establishing a new energy efficient baseline.

Molecular imaging has emerged in the past few decades as a novel means to investigate atherosclerosis. From a pathophysiological perspective, atherosclerosis is characterized by microscopic inflammation and microcalcification that precede the characteristic plaque buildup in arterial walls detected by traditional assessment methods, including anatomic imaging modalities. These processes of inflammation and microcalcification are, therefore, prime targets for molecular detection of atherosclerotic disease burden. Imaging with positron emission tomography/computed tomography (PET/CT) using 18F-fluorodeoxyglucose (FDG) and 18F-sodium fluoride (NaF) can non-invasively assess arterial inflammation and microcalcification, respectively. FDG uptake reflects glucose metabolism, which is particularly increased in atherosclerotic plaques retaining macrophages and undergoing hypoxic stress. By contrast, NaF uptake reflects the exchange of hydroxyl groups of hydroxyapatite crystals for fluoride producing fluorapatite, a key biochemical step in calcification of atherosclerotic plaque. Here we review the existing literature on FDG and NaF imaging and their respective values in investigating the progression of atherosclerotic disease. Based on the large volume of data that have been introduced to the literature and discussed in this review, it is clear that PET imaging will have a major role to play in assessing atherosclerosis in the major and coronary arteries. However, it is difficult to draw definitive conclusions on the potential role of FDG in investigating atherosclerosis given the vast number of studies with different designs, image acquisition methods, analyses, and interpretations. Our experience in this domain of research has suggested that NaF may be the tool of choice over FDG in assessing atherosclerosis, especially in the setting of coronary artery disease (CAD). Specifically, global NaF assessment appears to be superior in detecting plaques in tissues with high background FDG activity, such as the coronary arteries.

The Learn-HVAC project is an effort to use a large-scale building simulation as the base for an educational tool to teach a wide variety of people how heating, ventilating, and air conditioning systems work. These systems account for a substantial fraction of energy usage in this country and by many accounts are often not operated at efficiency levels that the systems are capable of (which varies tremendously depending on their age and design). HVAC systems are extremely complex internally so inefficient system operation can result from lack of knowledge or from malfunctions in system components that are not recognized. Learn-HVAC aims specifically at the HVAC complexity issue in its educational approach. Because buildings themselves are not suitable educational tools, a large-scale computer simulation is used to give people the experiential experience needed to develop an in-depth understanding of HVAC system operation. The thesis of this effort is that using such a simulation as part of an HVAC curriculum can enable a level of understanding that is not possible with conventional curricula.

Synthetic lethality (SL) offers a new precision oncology approach, which is based on targeting cancer-specific vulnerabilities across the whole genome, going beyond cancer drivers. The authors develop an approach termed ISLE to identify clinically relevant SL interactions and use them for patient stratification and novel target identification.

The goal of residential load management is to manipulate theelectricity demand of a group of consumers to matchsome desired shape. Effective load management needs two types of controls: systemic and local. Systemic controlmanipulates the aggregate power by signaling the consumers. Local control determines how the power consumerreacts to the signals. I present a price responsive intelligent thermostat for use in local load management. Further, Iexplore two types of systemic control using electricity price as the control variable. The first approach is to identifythe system using a low order model and apply traditional control techniques. The second approach makes use ofgame theory to auction the electricity to the consumers. Both methods enable reliable and robust high resolution loadmanagement.

People living in houses consume a substantial portion of total electricity consumption— 37% of U.S. electricity end use (Energy Information Administration (EIA) 2008)—which produces greenhouse gases. U.S. households exhibit extreme variability in energy consumption from one house to another. The variation in energy consumption from differences in climate and building characteristics is well-studied; however, the effect of various appliance end use and especially the variation in the behaviors of the people that use them is less understood. Yet, this variability is critical to the effective design of technology, efficiency, and/or demand response programs in order to reduce this consumption, especially during periods of peak electricity consumption. While many techniques have been used to simulate actual residential energy consumption using models, most fail to take into account the behavioral component that contributes to the wide spectrum of residential energy consumption.Towards this end, we have developed the Residential Power Network Simulation (ResPoNSe) to capture the spectrum—not average—of the electrical consumption of California households over the course of a hot summer day. ResPoNSe models the electricity consumption of a thousand households in order to test different demand response scenarios. Distributions of household characteristics, numbers and types of appliances per house, power consumption of the appliances, and the duration these appliances are used provide a more realistic variation of energy consumption. In turn, this simulation tool can provide a model of the spectrum of consumer response to different efficiency, marketing, or demand response programs.

Demand response—the management of customer electricity demand in response to supply—has emerged as a promising means of increasing grid reliability by reducing peak demand. One potential technology to enable residential Demand Response (DR) is a Programmable Communicating Thermostat (PCT) that receives price signals from the electrical utility. However, several issues preclude the widespread adoption of this technology and policy. One is the poor adoption and energy-conserving performance of a similar technology and policy—the programmable setback thermostat. Another is lukewarm customer response to residential DR air conditioning cycling programs. Finally, financial incentive alone may not suffice to persistently reduce peak electricity consumption.A team at UC Berkeley developed an alternative model for a residential demand response enabling technology, called the Demand Response Electrical Appliance Manager (DREAM). The DREAM system acts as both an intelligent thermostat and in-home energy display. DREAM consists of a wireless network of data sensors, appliance actuators and a central controller that can communicate variable price signals. We tested the DREAM in two houses in the summer of 2007 for six weeks. The DREAM controlled the HVAC system, monitored electricity from appliances, sensed temperature and occupancy, and displayed temperature and energy consumption. This paper discusses potential issues for DR policy and technology, and describes potential solutions in improving user adoption.

A number of Demand Response (DR) technologies work by responding to variable electricity pricing, but have not yet been applied to control residential HVAC systems. An autonomous thermostat system, the Demand Response Electrical Appliance Manager (DREAM), provides possibilities to improve price-based demand responsiveness in residences.Built on low-cost, low-power wireless technology, the system uses a disaggregated set of energy- and environmental sensors. Control strategies are implemented to optimize electricity cost and user’s comfort. To perform the optimization, the system starts from default values and learns the dynamic behavior of a house and HVAC system. A graphic user interface provides easy interaction with the system. Computer simulation, lab tests and field tests have been used to validate the system infrastructure and control strategies. These tests indicate that the DREAM responds automatically to price signals with appropriate energy saving behavior. The system can reduce electricity consumption during peak price hours without significantly decreasing comfort.

The goal of the Demand Response Enabling Technology Development contract is to develop disruptive technologies that enable demand response at the residential and small commercial electricity markets. The UC Berkeley team involves four project groups: Thermostat/Controls, Communications/Network, Metering/Sensors, and Energy Scavenging. These groups collaborate to develop a new thermostat, new nodes, and new meters to allow the residential-scale sector to respond to a variable electricity pricing structure aimed at reducing peak electrical demand. These groups leverage microcomputers and MEMs technology in developing wireless communication and controls 10x cheaper with 10x the functionality of existing technology.The Phase I report, dated April 4, 2006, covers progress in initial prototypes from June 2003 – November 2005 from all four groups. This Phase II report describes the continued development, and laboratory and field testing of those prototypes and control algorithms.

A research team at the University of California, Berkeley was tasked with addressing technical questions arising from the implementation of residential programmable communicating thermostats (PCTs) in California to meet updates to Title 24 building code related to PCTs. The purpose of the project was to perform research, development, and demonstration tasks to: validate the California Energy Commission’s PCT vision, answer technical issues related to system integration and implementation, recommend a suitable technology for a statewide one-way communication system for PCTs, and develop a methodology to study the impact of PCTs on electrical demand. The team performed several tasks to achieve these goals.The team validated the Energy Commission’s vision by concluding that it was possible for manufacturers to develop PCTs that: met the proposed Title 24 system interface requirements, could be sold at a retail price less than $100, and could be manufactured within the Energy Commission’s planned Title 24 timeline. This conclusion was the result of a concept for a minimum functionality PCT that was published as a bill of materials and validated with a working proof-of-concept demonstration.The team researched PCT system interfaces and identified technical issues related to system integration and implementation that should be considered as part of the policy, technology, and system design related to PCT implementation.The team reviewed technologies that could be used for statewide PCT communication and recommended the Radio Data System (RDS) technology as a suitable solution. The team demonstrated the feasibility of this technology and developed a site survey tool and methodology to study its real-world performance.Finally, the team developed a load group simulation to characterize the result of PCT pricing and control signals and used the simulation to study certain demand response scenarios. The team found that rebound peak from demand response events can be significant and that strategies to manage this peak should be investigated further.

This study is a mixed-methods exploratory study of a Spanish Home Language Arts (HLA) pilot curriculum designed for Students with Interrupted Education (SIFE) as it was implemented across six different schools in New York State during the 2019–2020 school year before the onset of COVID-19. The focus of the study was to observe whether the HLA curriculum improved teacher practice in the increased use of the gradual release of responsibility and the curriculum-prescribed protocols. Another goal was to examine whether the use of the curriculum helped to improve student writing and bilingual literacy. A final goal of the study was to survey teachers on their perceptions of the curriculum, especially in how the lesson design fostered student engagement and collaboration with others. The results of the internal evaluation showed that the teachers improved in their practice, especially in the areas of gradual release and increased student time on task. The students were able to develop specific text analysis and writing skills using instructional protocols used in the home language and in English that were transferable across classroom contexts. In addition, the lessons encouraged students to leverage literacy skills and background knowledge in Spanish as a way to support learning new skills in both Spanish and English. Finally, the study showed that the use of the curriculum increased student engagement and collaboration in the classroom.