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Dive into the research topics where David S. Watson is active.

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Featured researches published by David S. Watson.


Lawrence Berkeley National Laboratory | 2007

Demand Response Spinning Reserve Demonstration

Joseph H. Eto; Carlos Torres; Scott Hirth; Bob Yinger; John D. Kueck; Brendan Kirby; Clark Bernier; Roger Wright; A. Barat; David S. Watson

The Demand Response Spinning Reserve project is a pioneeringdemonstration of how existing utility load-management assets can providean important electricity system reliability resource known as spinningreserve. Using aggregated demand-side resources to provide spinningreserve will give grid operators at the California Independent SystemOperator (CAISO) and Southern California Edison (SCE) a powerful, newtool to improve system reliability, prevent rolling blackouts, and lowersystem operating costs.


Lawrence Berkeley National Laboratory | 2004

Development and evaluation of fully automated demand response in large facilities

Mary Ann Piette; Osman Sezgen; David S. Watson; Naoya Motegi; Christine Shockman; Laurie ten Hope

CALIFORNIA ENERGY COMMISSION January 2005 CEC-500-2005-013 PIER C OLLABORATIVE R EPORT DEVELOPMENT AND EVALUATION OF FULLY AUTOMATED DEMAND RESPONSE IN LARGE FACILITIES


Lawrence Berkeley National Laboratory | 2006

Automated Critical Peak Pricing Field Tests: Program Description and Results

Mary Ann Piette; David S. Watson; Naoya Motegi; Sila Kiliccote; Peng Xu

Automated Critical Peak Pricing Field Tests: Program Description and Results April 6, 2006 Mary Ann Piette David Watson Naoya Motegi Sila Kiliccote Peng Xu Lawrence Berkeley National Laboratory Sponsored by the Pacific Gas and Electric Company Emerging Technologies Program California Institute for Energy and the Environment LBNL Report Number 59351


Journal of Computing and Information Science in Engineering | 2009

Design and Operation of an Open, Interoperable Automated Demand Response Infrastructure for Commercial Buildings

Mary Ann Piette; Girish Ghatikar; Sila Kiliccote; David S. Watson; Ed Koch; Dan Hennage

Design and Operation of an Open Interoperable Automated Demand Response Infrastructure for Commercial Buildings Mary Ann Piette, Girish Ghatikar, Sila Kiliccote, David Watson Lawrence Berkeley National Laboratory Ed Koch, Dan Hennage Akuacom


Lawrence Berkeley National Laboratory | 2010

Using Dimmable Lighting for Regulation Capacity and Non-Spinning Reserves in the Ancillary Services Market. A Feasibility Study.

Francis Rubinstein; Li Xiaolei; David S. Watson

The objective of this Feasibility Study was to identify the potential of dimmable lighting for providing regulation capacity and contingency reserves if massively-deployed throughout the State. We found that one half of the total electric lighting load in the California commercial sector is bottled up in larger buildings that are greater an 50,000 square feet. Retrofitting large California buildings with dimmable lighting to enable fast DR lighting would require an investment of about


Archive | 2005

Adapting Wireless Technology to Lighting Control and Environmental Sensing

Dana Teasdale; Francis Rubinstein; David S. Watson; Steve Purdy

1.8 billion and a fleet of about 56 million dimming ballasts. By upgrading the existing installed base of lighting and controls (primarily in large commercial facilities) a substantial amount of ancillary services could be provided. Though not widely deployed, todays state-of-the art lighting systems, control systems and communication networks could be used for this application. The same lighting control equipment that is appropriate for fast DR is also appropriate for achieving energy efficiency with lighting on a daily basis. Thus fast DR can leverage the capabilities that are provided by a conventional dimming lighting control system. If dimmable lighting were massively deployed throughout large California buildings (because mandated by law, for example) dimmable lighting could realistically supply 380 MW of non-spinning reserve, 47percent of the total non-spinning reserves needed in 2007.


Lawrence Berkeley National Laboratory | 2009

Barrier Immune Radio Communications for Demand Response

Francis Rubinstein; Girish Ghatikar; Jessica Granderson; Paul Haugen; Carlos Romero; David S. Watson

The high cost of retrofitting buildings with advanced lighting control systems is a barrier to adoption of this energy-saving technology. Wireless technology, however, offers a solution to mounting installation costs since it requires no additional wiring to implement. To demonstrate the feasibility of such a system, a prototype wirelessly-controlled advanced lighting system was designed and built. The system includes the following components: a wirelessly-controllable analog circuit module (ACM), a wirelessly-controllable electronic dimmable ballast, a T8 3-lamp fixture, an environmental multi-sensor, a current transducer, and control software. The ACM, dimmable ballast, multi-sensor, and current transducer were all integrated with SmartMesh{trademark} wireless mesh networking nodes, called motes, enabling wireless communication, sensor monitoring, and actuator control. Each mote-enabled device has a reliable communication path to the SmartMesh Manager, a single board computer that controls network functions and connects the wireless network to a PC running lighting control software. The ACM is capable of locally driving one or more standard 0-10 Volt electronic dimmable ballasts through relay control and a 0-10 Volt controllable output. The mote-integrated electronic dimmable ballast is designed to drive a standard 3-lamp T8 light fixture. The environmental multi-sensor measures occupancy, light level and temperature. The current transducer is used to measure the power consumed by the fixture. Control software was developed to implement advanced lighting algorithms, including daylight ramping, occupancy control, and demand response. Engineering prototypes of each component were fabricated and tested in a bench-scale system. Based on standard industry practices, a cost analysis was conducted. It is estimated that the installation cost of a wireless advanced lighting control system for a retrofit application is at least 30% lower than a comparable wired system for a typical 16,000 square-foot office building, with a payback period of less than 3 years.


Lawrence Berkeley National Laboratory | 2004

Machine to machine (M2M) technology in demand responsive commercial buildings

David S. Watson; Mary Ann Piette; Osman Sezgen; Naoya Motegi; Laurie ten Hope

Various wireless technologies were field-tested in a six-story laboratory building to identify wireless technologies that can scale for future DR applications through very low node density power consumption, and unit cost. Data analysis included analysis of the signal-to-noise ratio (SNR), packet loss, and link quality at varying power levels and node densities. The narrowband technologies performed well, penetrating the floors of the building with little loss and exhibiting better range than the wideband technology. 900 MHz provided full coverage at 1 watt and substantially complete coverage at 500 mW at the test site. 900 MHz was able to provide full coverage at 100 mW with only one additional relay transmitter, and was the highest-performing technology in the study. 2.4 GHz could not provide full coverage with only a single transmitter at the highest power level tested (63 mW). However, substantially complete coverage was provided at 2.4 GHz at 63 mW with the addition of one repeater node.


Lawrence Berkeley National Laboratory | 2006

Dynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Study Case in New York

Sila Kiliccote; Mary Ann Piette; David S. Watson; Glenn Hughes


Lawrence Berkeley National Laboratory | 2007

Automated Critical Peak Pricing Field Tests: 2006 Pilot Program Description and Results

Mary Ann Piette; David S. Watson; Naoya Motegi; Sila Kiliccote

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Mary Ann Piette

Lawrence Berkeley National Laboratory

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Naoya Motegi

Lawrence Berkeley National Laboratory

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Sila Kiliccote

Lawrence Berkeley National Laboratory

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Francis Rubinstein

Lawrence Berkeley National Laboratory

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Osman Sezgen

Lawrence Berkeley National Laboratory

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Girish Ghatikar

Lawrence Berkeley National Laboratory

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Brendan Kirby

Oak Ridge National Laboratory

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Ed Koch

Lawrence Berkeley National Laboratory

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Jessica Granderson

Lawrence Berkeley National Laboratory

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