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Dive into the research topics where Bernie Neenan is active.

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Featured researches published by Bernie Neenan.


Lawrence Berkeley National Laboratory | 2004

A Survey of Utility Experience with Real Time Pricing

Galen Barbose; Charles Goldman; Bernie Neenan

While more than 70 utilities in the U.S. have offered voluntary RTP tariffs on either a pilot or permanent basis, most have operated in relative obscurity. To bring this broad base of experience to bear on policymakers current efforts to stimulate price responsive demand, we conducted a survey of 43 voluntary RTP tariffs offered in 2003. The survey involved telephone interviews with RTP program managers and other utility staff, as well as a review of regulatory documents, tariff sheets, program evaluations, and other publicly available sources. Based on this review of RTP program experience, we identify key trends related to: utilities motivations for implementing RTP, evolution of RTP tariff design, program participation, participant price response, and program outlook. We draw from these findings to discuss implications for policymakers that are currently considering voluntary RTP as a strategy for developing price responsive demand.


Lawrence Berkeley National Laboratory | 2005

Real Time Pricing as a Default or Optional Service for C&ICustomers: A Comparative Analysis of Eight Case Studies

Galen Barbose; Charles Goldman; Ranjit Bharvirkar; Nicole Hopper; Michael Ting; Bernie Neenan

LBNL-57661 Real Time Pricing as a Default or Optional Service for C&I Customers: A Comparative Analysis of Eight Case Studies G. Barbose, C. Goldman, R. Bharvirkar, N. Hopper, and M. Ting Lawrence Berkeley National Laboratory B. Neenan Neenan Associates Ernest Orlando Lawrence Berkeley National Laboratory 1 Cyclotron Road, MS90R4000 Berkeley, CA 94720-8136 August 2005 This work described in this report was coordinated by the Demand Response Research Center and funded by the California Energy Commission, Public Interest Energy Research Program, under Work for Others Contract No. 500-03-026 and by the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.


Lawrence Berkeley National Laboratory | 2007

Estimating Demand Response Market Potential Among Large Commercialand Industrial Customers:A Scoping Study

Charles R. Goldman; Nicole Hopper; Ranjit Bharvirkar; Bernie Neenan; Peter Cappers

ABSTRACT=Demand response (DR) is increasingly recognized asan essential ingredient to well-functioning electricity markets. DRmarket potential studies can answer questions about the amount of DRavailable in a given area, from which market segments. Several recent DRmarket potential studies have been conducted, most adapting techniquesused to estimate energy-efficiency (EE) potential. In this scoping study,we: reviewed and categorized seven recent DR market potential studies;recommended a methodology for estimating DR market potential for large,non-residential utility customers that uses price elasticities to accountfor behavior and prices; compiled participation rates and elasticityvalues from six DR options offered to large customers in recent years,and demonstrated our recommended methodology with large customer marketpotential scenarios at an illustrative Northeastern utility. We recommendan elasticity approach for large-customer DR options that rely oncusto!Demand response is increasingly recognized as an essential ingredient to well functioning electricity markets. This growing consensus was formalized in the Energy Policy Act of 2005 (EPACT), which established demand response as an official policy of the U.S. government, and directed states (and their electric utilities) to consider implementing demand response, with a particular focus on price-based mechanisms. The resulting deliberations, along with a variety of state and regional demand response initiatives, are raising important policy questions: for example, How much demand response is enough? How much is available? From what sources? At what cost? The purpose of this scoping study is to examine analytical techniques and data sources to support demand response market assessments that can, in turn, answer the second and third of these questions. We focus on demand response for large (>350 kW), commercial and industrial (C&I) customers, although many of the concepts could equally be applied to similar programs and tariffs for small commercial and residential customers.Demand response (DR) is increasingly recognized as an essential ingredient to well-functioning electricity markets. DR market potential studies can answer questions about the amount of DR available in a given area and from which market segments. Several recent DR market potential studies have been conducted, most adapting techniques used to estimate energy-efficiency (EE) potential. In this scoping study, we: reviewed and categorized seven recent DR market potential studies; recommended a methodology for estimating DR market potential for large, non-residential utility customers that uses price elasticities to account for behavior and prices; compiled participation rates and elasticity values from six DR options offered to large customers in recent years, and demonstrated our recommended methodology with large customer market potential scenarios at an illustrative Northeastern utility. We observe that EE and DR have several important differences that argue for an elasticity approach for large-customer DR options that rely on customer-initiated response to prices, rather than the engineering approaches typical of EE potential studies. Base-case estimates suggest that offering DR options to large, non-residential customers results in 1-3% reductions in their class peak demand in response to prices or incentive payments of


Lawrence Berkeley National Laboratory | 2007

A Methodology for Estimating Large-Customer Demand Response Market Potential

Charles R. Goldman; Nicole Hopper; Ranjit Bharvirkar; Bernie Neenan; Peter Cappers

500/MWh. Participation rates (i.e., enrollment in voluntary DR programs or acceptance of default hourly pricing) have the greatest influence on DR impacts of all factors studied, yet are the least well understood. Elasticity refinements to reflect the impact of enabling technologies and response at high prices provide more accurate market potential estimates, particularly when arc elasticities (rather than substitution elasticities) are estimated.


Lawrence Berkeley National Laboratory | 2007

Estimating Large-Customer Demand Response Market Potential:Integrating Price and Customer Behavior

Charles R. Goldman; Nicole Hopper; Ranjit Bharvirkar; Bernie Neenan; Peter Cappers

ABSTRACT=Demand response (DR) is increasingly recognized asan essential ingredient to well-functioning electricity markets. DRmarket potential studies can answer questions about the amount of DRavailable in a given area, from which market segments. Several recent DRmarket potential studies have been conducted, most adapting techniquesused to estimate energy-efficiency (EE) potential. In this scoping study,we: reviewed and categorized seven recent DR market potential studies;recommended a methodology for estimating DR market potential for large,non-residential utility customers that uses price elasticities to accountfor behavior and prices; compiled participation rates and elasticityvalues from six DR options offered to large customers in recent years,and demonstrated our recommended methodology with large customer marketpotential scenarios at an illustrative Northeastern utility. We recommendan elasticity approach for large-customer DR options that rely oncusto!Demand response is increasingly recognized as an essential ingredient to well functioning electricity markets. This growing consensus was formalized in the Energy Policy Act of 2005 (EPACT), which established demand response as an official policy of the U.S. government, and directed states (and their electric utilities) to consider implementing demand response, with a particular focus on price-based mechanisms. The resulting deliberations, along with a variety of state and regional demand response initiatives, are raising important policy questions: for example, How much demand response is enough? How much is available? From what sources? At what cost? The purpose of this scoping study is to examine analytical techniques and data sources to support demand response market assessments that can, in turn, answer the second and third of these questions. We focus on demand response for large (>350 kW), commercial and industrial (C&I) customers, although many of the concepts could equally be applied to similar programs and tariffs for small commercial and residential customers.Demand response (DR) is increasingly recognized as an essential ingredient to well-functioning electricity markets. DR market potential studies can answer questions about the amount of DR available in a given area and from which market segments. Several recent DR market potential studies have been conducted, most adapting techniques used to estimate energy-efficiency (EE) potential. In this scoping study, we: reviewed and categorized seven recent DR market potential studies; recommended a methodology for estimating DR market potential for large, non-residential utility customers that uses price elasticities to account for behavior and prices; compiled participation rates and elasticity values from six DR options offered to large customers in recent years, and demonstrated our recommended methodology with large customer market potential scenarios at an illustrative Northeastern utility. We observe that EE and DR have several important differences that argue for an elasticity approach for large-customer DR options that rely on customer-initiated response to prices, rather than the engineering approaches typical of EE potential studies. Base-case estimates suggest that offering DR options to large, non-residential customers results in 1-3% reductions in their class peak demand in response to prices or incentive payments of


International Energy Program EvaluationConference, Chicago, Il Aug. 14-16, 2007, Chicago, IL, Aug. 14-16,2007 | 2007

A Methodology for Estimating Large-Customer Demand Response MarketPotential

Charles Goldman; Nicole Hopper; Ranjit Bharvirkar; Bernie Neenan; Peter Cappers

500/MWh. Participation rates (i.e., enrollment in voluntary DR programs or acceptance of default hourly pricing) have the greatest influence on DR impacts of all factors studied, yet are the least well understood. Elasticity refinements to reflect the impact of enabling technologies and response at high prices provide more accurate market potential estimates, particularly when arc elasticities (rather than substitution elasticities) are estimated.


Lawrence Berkeley National Laboratory | 2005

Customer Strategies for Responding to Day-Ahead Market HourlyElectricity Pricing

Chuck Goldman; Nicole Hopper; Ranjit Bharvirkar; Bernie Neenan; Dick Boisvert; Peter Cappers; Donna Pratt; Kim Butkins

ABSTRACT=Demand response (DR) is increasingly recognized asan essential ingredient to well-functioning electricity markets. DRmarket potential studies can answer questions about the amount of DRavailable in a given area, from which market segments. Several recent DRmarket potential studies have been conducted, most adapting techniquesused to estimate energy-efficiency (EE) potential. In this scoping study,we: reviewed and categorized seven recent DR market potential studies;recommended a methodology for estimating DR market potential for large,non-residential utility customers that uses price elasticities to accountfor behavior and prices; compiled participation rates and elasticityvalues from six DR options offered to large customers in recent years,and demonstrated our recommended methodology with large customer marketpotential scenarios at an illustrative Northeastern utility. We recommendan elasticity approach for large-customer DR options that rely oncusto!Demand response is increasingly recognized as an essential ingredient to well functioning electricity markets. This growing consensus was formalized in the Energy Policy Act of 2005 (EPACT), which established demand response as an official policy of the U.S. government, and directed states (and their electric utilities) to consider implementing demand response, with a particular focus on price-based mechanisms. The resulting deliberations, along with a variety of state and regional demand response initiatives, are raising important policy questions: for example, How much demand response is enough? How much is available? From what sources? At what cost? The purpose of this scoping study is to examine analytical techniques and data sources to support demand response market assessments that can, in turn, answer the second and third of these questions. We focus on demand response for large (>350 kW), commercial and industrial (C&I) customers, although many of the concepts could equally be applied to similar programs and tariffs for small commercial and residential customers.Demand response (DR) is increasingly recognized as an essential ingredient to well-functioning electricity markets. DR market potential studies can answer questions about the amount of DR available in a given area and from which market segments. Several recent DR market potential studies have been conducted, most adapting techniques used to estimate energy-efficiency (EE) potential. In this scoping study, we: reviewed and categorized seven recent DR market potential studies; recommended a methodology for estimating DR market potential for large, non-residential utility customers that uses price elasticities to account for behavior and prices; compiled participation rates and elasticity values from six DR options offered to large customers in recent years, and demonstrated our recommended methodology with large customer market potential scenarios at an illustrative Northeastern utility. We observe that EE and DR have several important differences that argue for an elasticity approach for large-customer DR options that rely on customer-initiated response to prices, rather than the engineering approaches typical of EE potential studies. Base-case estimates suggest that offering DR options to large, non-residential customers results in 1-3% reductions in their class peak demand in response to prices or incentive payments of


Archive | 2003

How and why customers respond to electricity price variability: A study of NYISO and NYSERDA 2002 PRL program performance

Bernie Neenan; Donna Pratt; Peter Cappers; James Doane; Jeremey Anderson; Richard N. Boisvert; Charles Goldman; Osman Sezgen; Galen Barbose; Ranjit Bharvirkar

500/MWh. Participation rates (i.e., enrollment in voluntary DR programs or acceptance of default hourly pricing) have the greatest influence on DR impacts of all factors studied, yet are the least well understood. Elasticity refinements to reflect the impact of enabling technologies and response at high prices provide more accurate market potential estimates, particularly when arc elasticities (rather than substitution elasticities) are estimated.


Utilities Policy | 2006

Customer response to day-ahead market hourly pricing: Choices and performance

Nicole Hopper; Charles Goldman; Ranjit Bharvirkar; Bernie Neenan

ABSTRACT=Demand response (DR) is increasingly recognized asan essential ingredient to well-functioning electricity markets. DRmarket potential studies can answer questions about the amount of DRavailable in a given area, from which market segments. Several recent DRmarket potential studies have been conducted, most adapting techniquesused to estimate energy-efficiency (EE) potential. In this scoping study,we: reviewed and categorized seven recent DR market potential studies;recommended a methodology for estimating DR market potential for large,non-residential utility customers that uses price elasticities to accountfor behavior and prices; compiled participation rates and elasticityvalues from six DR options offered to large customers in recent years,and demonstrated our recommended methodology with large customer marketpotential scenarios at an illustrative Northeastern utility. We recommendan elasticity approach for large-customer DR options that rely oncusto!Demand response is increasingly recognized as an essential ingredient to well functioning electricity markets. This growing consensus was formalized in the Energy Policy Act of 2005 (EPACT), which established demand response as an official policy of the U.S. government, and directed states (and their electric utilities) to consider implementing demand response, with a particular focus on price-based mechanisms. The resulting deliberations, along with a variety of state and regional demand response initiatives, are raising important policy questions: for example, How much demand response is enough? How much is available? From what sources? At what cost? The purpose of this scoping study is to examine analytical techniques and data sources to support demand response market assessments that can, in turn, answer the second and third of these questions. We focus on demand response for large (>350 kW), commercial and industrial (C&I) customers, although many of the concepts could equally be applied to similar programs and tariffs for small commercial and residential customers.Demand response (DR) is increasingly recognized as an essential ingredient to well-functioning electricity markets. DR market potential studies can answer questions about the amount of DR available in a given area and from which market segments. Several recent DR market potential studies have been conducted, most adapting techniques used to estimate energy-efficiency (EE) potential. In this scoping study, we: reviewed and categorized seven recent DR market potential studies; recommended a methodology for estimating DR market potential for large, non-residential utility customers that uses price elasticities to account for behavior and prices; compiled participation rates and elasticity values from six DR options offered to large customers in recent years, and demonstrated our recommended methodology with large customer market potential scenarios at an illustrative Northeastern utility. We observe that EE and DR have several important differences that argue for an elasticity approach for large-customer DR options that rely on customer-initiated response to prices, rather than the engineering approaches typical of EE potential studies. Base-case estimates suggest that offering DR options to large, non-residential customers results in 1-3% reductions in their class peak demand in response to prices or incentive payments of


Archive | 2004

Does Real-Time Pricing Deliver Demand Response? A Case Study of Niagara Mohawk's Large Customer RTP Tariff

Chuck Goldman; Nicole Hopper; Osman Sezgen; Mithra Moezzi; Ranjit Bharvirkar; Bernie Neenan; Donna Pratt; Peter Cappers; Richard N. Boisvert; Neenan Associates

500/MWh. Participation rates (i.e., enrollment in voluntary DR programs or acceptance of default hourly pricing) have the greatest influence on DR impacts of all factors studied, yet are the least well understood. Elasticity refinements to reflect the impact of enabling technologies and response at high prices provide more accurate market potential estimates, particularly when arc elasticities (rather than substitution elasticities) are estimated.

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Nicole Hopper

Lawrence Berkeley National Laboratory

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Ranjit Bharvirkar

Lawrence Berkeley National Laboratory

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Charles Goldman

Lawrence Berkeley National Laboratory

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Peter Cappers

Lawrence Berkeley National Laboratory

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Galen Barbose

Lawrence Berkeley National Laboratory

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Osman Sezgen

Lawrence Berkeley National Laboratory

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Mithra Moezzi

Portland State University

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