Transportation Research Part D: Transport and Environment, 2018
Users may download and print one copy of any publication from the public portal for the purpose... more Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Long-term energy systems models have been used extensively in energy planning and climate policy ... more Long-term energy systems models have been used extensively in energy planning and climate policy analysis. However, specifically in energy systems optimization models, heterogeneity of consumer preferences for competing energy technologies (e.g., vehicles), has not been adequately represented, leading to behaviorally unrealistic modeling results. This can lead to policy analysis results that are viewed by stakeholders as clearly deficient. This paper shows how heterogeneous consumer behavioral effects can be introduced into these models in the form of perceived disutility costs, to more realistically capture consumer choice in making technology purchase decisions. We developed a novel methodology that incorporates the theory of a classic consumer choice model into a commonly used long-term energy systems modeling framework using a case study of light-duty vehicles. A diverse set of consumer segments (thirty-six) is created to represent observable, identifiable differences in factors such as annual driving distances and attitude towards risks of new technology. Non-monetary or "disutility" costs associated with these factors are introduced to capture the differences in preferences across consumer segments for various technologies. We also create clones within each consumer segment to capture randomly distributed unobservable differences in preferences. We provide and review results for a specific example that includes external factors such as recharging/refueling station availability, battery size of electric vehicles, recharging time and perceived technology risks. Although the example is for light-duty vehicles in the US using a specific modeling system, this approach can be implemented more broadly to model the adoption of consumer technologies in other sectors or regions in similar energy systems modeling frameworks.
Users may download and print one copy of any publication from the public portal for the purpose... more Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
We model the California Energy System to 2050 under policy and technology scenarios. The model op... more We model the California Energy System to 2050 under policy and technology scenarios. The model optimizes technology and resource investments to meet emissions targets. Deep emissions cuts (474%) are achieved across all reduction scenarios. Carbon capture enables negative emission biofuels and allows more petroleum use. Greenhouse gas mitigation cost is small compared with total economic activity.
We address the poor representation of travel behaviour in energy systems models. Modal choice mod... more We address the poor representation of travel behaviour in energy systems models. Modal choice modelled in TIMES energy system using novel TTB methodology. Case studies for California and Ireland are presented. In a mitigation/optimization scenario there is a shift to public transport usage.
2050 "target" = 80% reduction by 2050 2. Lack of existing models 3. Build on previous UCD resea... more 2050 "target" = 80% reduction by 2050 2. Lack of existing models 3. Build on previous UCD research e.g., 80in50 studies; alternative fuels infrastructure development Novel Research Questions-Improved Timeslice Resolution • Demand timeslices Applied to electricity demands in residential, commercial, industrial, agricultural, and transport • Supply timeslices (availabilities) Applied to fossil, nuclear, and renewable power plants Availability factor (capacity factor) is limited within each timeslice (i.e., max % of installed capacity is available) Historical plant timeslice data comes from a dispatch model for California, EDGE-CA (McCarthy and Yang, 2009
Transportation Research Part D: Transport and Environment, 2018
Users may download and print one copy of any publication from the public portal for the purpose... more Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
Long-term energy systems models have been used extensively in energy planning and climate policy ... more Long-term energy systems models have been used extensively in energy planning and climate policy analysis. However, specifically in energy systems optimization models, heterogeneity of consumer preferences for competing energy technologies (e.g., vehicles), has not been adequately represented, leading to behaviorally unrealistic modeling results. This can lead to policy analysis results that are viewed by stakeholders as clearly deficient. This paper shows how heterogeneous consumer behavioral effects can be introduced into these models in the form of perceived disutility costs, to more realistically capture consumer choice in making technology purchase decisions. We developed a novel methodology that incorporates the theory of a classic consumer choice model into a commonly used long-term energy systems modeling framework using a case study of light-duty vehicles. A diverse set of consumer segments (thirty-six) is created to represent observable, identifiable differences in factors such as annual driving distances and attitude towards risks of new technology. Non-monetary or "disutility" costs associated with these factors are introduced to capture the differences in preferences across consumer segments for various technologies. We also create clones within each consumer segment to capture randomly distributed unobservable differences in preferences. We provide and review results for a specific example that includes external factors such as recharging/refueling station availability, battery size of electric vehicles, recharging time and perceived technology risks. Although the example is for light-duty vehicles in the US using a specific modeling system, this approach can be implemented more broadly to model the adoption of consumer technologies in other sectors or regions in similar energy systems modeling frameworks.
Users may download and print one copy of any publication from the public portal for the purpose... more Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
We model the California Energy System to 2050 under policy and technology scenarios. The model op... more We model the California Energy System to 2050 under policy and technology scenarios. The model optimizes technology and resource investments to meet emissions targets. Deep emissions cuts (474%) are achieved across all reduction scenarios. Carbon capture enables negative emission biofuels and allows more petroleum use. Greenhouse gas mitigation cost is small compared with total economic activity.
We address the poor representation of travel behaviour in energy systems models. Modal choice mod... more We address the poor representation of travel behaviour in energy systems models. Modal choice modelled in TIMES energy system using novel TTB methodology. Case studies for California and Ireland are presented. In a mitigation/optimization scenario there is a shift to public transport usage.
2050 "target" = 80% reduction by 2050 2. Lack of existing models 3. Build on previous UCD resea... more 2050 "target" = 80% reduction by 2050 2. Lack of existing models 3. Build on previous UCD research e.g., 80in50 studies; alternative fuels infrastructure development Novel Research Questions-Improved Timeslice Resolution • Demand timeslices Applied to electricity demands in residential, commercial, industrial, agricultural, and transport • Supply timeslices (availabilities) Applied to fossil, nuclear, and renewable power plants Availability factor (capacity factor) is limited within each timeslice (i.e., max % of installed capacity is available) Historical plant timeslice data comes from a dispatch model for California, EDGE-CA (McCarthy and Yang, 2009
Uploads
Papers by kalai ramea