Representing power sector detail and flexibility in a multi-sector model

Wise, Marshall; Patel, Pralit; Khan, Zarrar; Kim, Son H.; Hejazi, Mohamad; Iyer, Gokul

doi:10.1016/j.esr.2019.100411

Title: Representing power sector detail and flexibility in a multi-sector model

Full Record
Other Related Research

Abstract

Electricity demand is expected to grow rapidly in the coming decades. Although capacity investment requires time horizons over years and decades, planners need to also consider shorter-term conditions of high stress such as sudden changes in fuel prices and demand to maintain reliability of power supply during all times. Consequently, long-term models used to inform planning therefore need to account for the impacts of sub-annual load variation along with the co-evolution of the power sector with other sectors of the economy. We incorporate sub-annual investment and operation dynamics in the power sector module of a long-term multisector model with state-level detail in the U.S. (GCAM-USA) to better reflect operational flexibility in the power sector in response to various stressors. For example, we demonstrate the ability of dispatchable technologies (e.g. coal and gas) to increase generation in response to increasing demands for electricity without increasing capacity at the same rate. We also demonstrate that the impacts of an important stressor, namely, natural gas price variation on power-sector investment and operation are heterogeneous across states and depend on the character of state-level fuel mixes. Our study highlights the value of representing sub-annual detail in a long-term model with multi-sectoral dynamics to bettermore »« less

Authors:

Wise, Marshall; Patel, Pralit; Khan, Zarrar; Kim, Son H.; Hejazi, Mohamad;

Publication Date:: Fri Nov 01 00:00:00 EDT 2019

Research Org.:: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Org.:: USDOE Office of Science (SC)

OSTI Identifier:: 1566278

Alternate Identifier(s):: OSTI ID: 1580114

Report Number(s):: PNNL-SA-138629
Journal ID: ISSN 2211-467X; S2211467X1930104X; 100411; PII: S2211467X1930104X

Grant/Contract Number:: AC05-76RL01830

Resource Type:: Published Article

Journal Name:: Energy Strategy Reviews

Additional Journal Information:: Journal Name: Energy Strategy Reviews Journal Volume: 26 Journal Issue: C; Journal ID: ISSN 2211-467X

Publisher:: Elsevier

Country of Publication:: Netherlands

Language:: English

Subject:: 29 ENERGY PLANNING, POLICY, AND ECONOMY; Electric sector; Power sector; Investment; Dispatch; Capacity expansion

Citation Formats


                    Wise, Marshall, Patel, Pralit, Khan, Zarrar, Kim, Son H., Hejazi, Mohamad, and Iyer, Gokul. Representing power sector detail and flexibility in a multi-sector model.  Netherlands: N. p., 2019. 
Web.  doi:10.1016/j.esr.2019.100411.

Copy to clipboard


                    Wise, Marshall, Patel, Pralit, Khan, Zarrar, Kim, Son H., Hejazi, Mohamad, & Iyer, Gokul. Representing power sector detail and flexibility in a multi-sector model.  Netherlands.  https://doi.org/10.1016/j.esr.2019.100411

Copy to clipboard


                    Wise, Marshall, Patel, Pralit, Khan, Zarrar, Kim, Son H., Hejazi, Mohamad, and Iyer, Gokul. Fri .  
"Representing power sector detail and flexibility in a multi-sector model".  Netherlands.  https://doi.org/10.1016/j.esr.2019.100411.

Copy to clipboard


                    
@article{osti_1566278,

  title        = {Representing power sector detail and flexibility in a multi-sector model},

  author       = {Wise, Marshall and Patel, Pralit and Khan, Zarrar and Kim, Son H. and Hejazi, Mohamad and Iyer, Gokul},

  abstractNote = {Electricity demand is expected to grow rapidly in the coming decades. Although capacity investment requires time horizons over years and decades, planners need to also consider shorter-term conditions of high stress such as sudden changes in fuel prices and demand to maintain reliability of power supply during all times. Consequently, long-term models used to inform planning therefore need to account for the impacts of sub-annual load variation along with the co-evolution of the power sector with other sectors of the economy. We incorporate sub-annual investment and operation dynamics in the power sector module of a long-term multisector model with state-level detail in the U.S. (GCAM-USA) to better reflect operational flexibility in the power sector in response to various stressors. For example, we demonstrate the ability of dispatchable technologies (e.g. coal and gas) to increase generation in response to increasing demands for electricity without increasing capacity at the same rate. We also demonstrate that the impacts of an important stressor, namely, natural gas price variation on power-sector investment and operation are heterogeneous across states and depend on the character of state-level fuel mixes. Our study highlights the value of representing sub-annual detail in a long-term model with multi-sectoral dynamics to better capture real-world decision-making in the power sector.},

  doi          = {10.1016/j.esr.2019.100411},

  journal      = {Energy Strategy Reviews},

  number       = C,

  volume       = 26,

  place        = {Netherlands},

  year         = {Fri Nov 01 00:00:00 EDT 2019},

  month        = {Fri Nov 01 00:00:00 EDT 2019}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Publisher's Version of Record
https://doi.org/10.1016/j.esr.2019.100411

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 9 works

Citation information provided by
Web of Science

Save / Share:

Export Metadata

Save to My Library

Similar Records in DOE PAGES and OSTI.GOV collections:

Renewable Energy and Efficiency Technologies in Scenarios of U.S. Decarbonization in Two Types of Models: Comparison of GCAM Modeling and Sector-Specific Modeling

Technical Report Binsted, Matthew ; Suchyta, Harry ; Zhang, Ying ; ...

Energy system projections from quantitative models inform actions ranging from short-term and local decisions, such as those about technology and infrastructure deployment, and global and long-term negotiations and targets. Computational limits require model designers to balance coverage and resolution (i.e., breadth versus depth). Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses with less resolution than models that focus on a single sector's energy use. GCAM balances global supply and demand of all energy carriers projecting prices using internal calculations for energy sources and costs of greenhouse gas mitigation while capturing interlinkages betweenmore »« less
https://doi.org/10.2172/1903177

Full Text Available
Representing the Future Role of Hydropower and Pumped Storage Hydropower (PSH) in Electricity Planning Tools

Conference Cohen, Stuart M.

Existing tools for long-term electric sector planning struggle to represent hydropower's nuanced site-specific technical and operating characteristics, which depend on technical specifications as well as water management practices and regulations. As a result, long-term planning models and tools insufficiently characterize hydropower value and incentives, and they cannot fully represent the role hydropower can play in a future electricity system that could include a high penetration of variable wind and solar generation, battery storage, and other low-carbon technologies. This presentation demonstrates the culmination of a multi-year effort to enhance hydropower representations in electricity planning models at the National Renewable Energy Laboratorymore »« less
Full Text Available
Emissions reduction scenarios in the Argentinean Energy Sector

Journal Article Di Sbroiavacca, Nicolás ; Nadal, Gustavo ; Lallana, Francisco ; ... - Energy Economics

Here in this paper the LEAP, TIAM-ECN, and GCAM models were applied to evaluate the impact of a variety of climate change control policies (including carbon pricing and emission constraints relative to a base year) on primary energy consumption, final energy consumption, electricity sector development, and CO₂ emission savings of the energy sector in Argentina over the 2010-2050 period. The LEAP model results indicate that if Argentina fully implements the most feasible mitigation measures currently under consideration by official bodies and key academic institutions on energy supply and demand, such as the ProBiomass program, a cumulative incremental economic cost ofmore »« less
https://doi.org/10.1016/j.eneco.2015.03.021

Full Text Available
tell: a Python package to model future total electricity loads in the United States

Journal Article McGrath, Casey R. ; Burleyson, Casey D. ; Khan, Zarrar ; ... - Journal of Open Source Software

The purpose of the Total ELectricity Load (tell) model is to generate 21st century profiles of hourly electricity load (demand) across the Conterminous United States (CONUS). tell loads reflect the impact of climate and socioeconomic change at a spatial and temporal resolution adequate for input to an electricity grid operations model. tell uses machine learning to develop profiles that are driven by projections of climate/meteorology and population. tell also harmonizes its results with United States (U.S.) state-level, annual projections from a national- to global-scale energy-economy model. This model accounts for a wide range of other factors affecting electricity demand, includingmore »« less
https://doi.org/10.21105/joss.04472

Full Text Available
cerf: A Python package to evaluate the feasibility and costs of power plant siting for alternative futures

Journal Article Vernon, Christopher R. ; Rice, Jennie S. ; Zuljevic, Nino ; ... - Journal of Open Source Software

Long-term electric power sector planning and capacity expansion is a key area of interest to stakeholders across a wide range of organizations because it helps in making informed decisions about investments in infrastructure within the context of potential future vulnerabilities under various natural and human stressors. Future power plant siting costs will depend on a number of factors including the characteristics of the electricity capacity expansion and electricity demand (e.g., fuel mix of future electric power capacity, and the magnitude and geographic distribution of electricity demand growth) as well as the geographic location of power plants. Electricity technology capacity expansionmore »« less
https://doi.org/10.21105/joss.03601

Full Text Available

Similar Records