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

Journal Article · · Journal of Open Source Software
DOI:https://doi.org/10.21105/joss.03601· OSTI ID:1844599

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 expansion plans modeled to represent alternate future conditions meeting a set of scenario assumptions are traditionally compared against historical trends which may not be consistent with current and future conditions. We present the `cerf` Python package (a.k.a., the Capacity Expansion Regional Feasibility model) which helps evaluate the feasibility and structure of future, scenario-driven electricity capacity expansion plans by siting power plants in areas that have been deemed the least cost option while considering dynamic future conditions. We can use `cerf` to gain insight to research topics such as: 1) under what conditions future projected electricity expansion plans from models such as GCAM-USA are possible to achieve, 2) where and which on-the-ground barriers to siting (e.g., protected areas, cooling water availability) may influence our ability to achieve certain expansions, and 3) how electricity infrastructure build-outs and value may evolve into the future when considering locational marginal pricing (LMP) based on the supply and demand of electricity from a grid operations model.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
1844599
Report Number(s):
PNNL-SA-164611
Journal Information:
Journal of Open Source Software, Journal Name: Journal of Open Source Software Journal Issue: 65 Vol. 6; ISSN 2475-9066
Publisher:
Open Source Initiative - NumFOCUSCopyright Statement
Country of Publication:
United States
Language:
English

References (12)

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U.S. electricity infrastructure of the future: Generation and transmission pathways through 2050 journal February 2020
Representing power sector detail and flexibility in a multi-sector model journal November 2019
Comparing future patterns of energy system change in 2 °C scenarios with historically observed rates of change journal November 2015
A review of the potential impacts of climate change on bulk power system planning and operations in the United States journal December 2018
Diffusion of low-carbon technologies and the feasibility of long-term climate targets journal January 2015
Resilience of the Eastern African electricity sector to climate driven changes in hydropower generation journal January 2019
Impacts of long-term temperature change and variability on electricity investments journal March 2021
A global analysis of the progress and failure of electric utilities to adapt their portfolios of power-generation assets to the energy transition journal August 2020
Data Structures for Statistical Computing in Python conference January 2010
GCAM v5.1: representing the linkages between energy, water, land, climate, and economic systems journal January 2019
CERF – A Geospatial Model for Assessing Future Energy Production Technology Expansion Feasibility journal January 2018

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