Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Update conda lockfile for week of 2024-10-28 #3932

Merged
merged 5 commits into from
Oct 28, 2024
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension


Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion .pre-commit-config.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@ repos:
# Formatters: hooks that re-write Python & documentation files
####################################################################################
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.7.0
rev: v0.7.1
hooks:
- id: ruff
args: [--fix, --exit-non-zero-on-fix]
Expand Down
17 changes: 17 additions & 0 deletions docs/catalyst_pubs.bib
Original file line number Diff line number Diff line change
Expand Up @@ -139,3 +139,20 @@ @misc{Ferc1DB
url = {https://doi.org/10.5281/zenodo.3677547},
urldate = {2021-11-01}
}

@proceedings{lamb_2024_13948332,
title = {{The Public Utility Data Liberation Project: Providing Open Data for a Clean Energy Transition}},
author = {Lamb, Katherine and
Belfer, Ella and
Selvans, Zane and
Norman, Bennett and
Gosnell, Christina and
Xia, Dazhong and
Sharpe, Austen and
Schira, Zach},
year = {2024},
publisher = {Zenodo},
month = oct,
doi = {10.5281/zenodo.13948332},
url = {https://doi.org/10.5281/zenodo.13948332}
}
96 changes: 96 additions & 0 deletions docs/further_reading.bib
Original file line number Diff line number Diff line change
Expand Up @@ -354,3 +354,99 @@ @book{doi:https://doi.org/10.1002/0470036427
The author explains how a whole power system is managed and coordinated, analyzed
mathematically, and kept stable and reliable.}
}

@misc{brown_2019_3368397,
author = {Brown, Patrick R. and O'Sullivan, Francis M.},
title = {{Shaping photovoltaic array output to align with changing wholesale electricity price profiles}},
month = sep,
year = 2019,
publisher = {Zenodo},
version = {1.0.0},
doi = {10.5281/zenodo.3368397},
url = {https://doi.org/10.5281/zenodo.3368397}
}

@misc{brown_2019_3562896,
author = {Brown, Patrick R.},
title = {{Spatial and temporal variation in the value of solar power across United States electricity markets}},
month = dec,
year = 2019,
publisher = {Zenodo},
version = {1.0.0},
doi = {10.5281/zenodo.3562896},
url = {https://doi.org/10.5281/zenodo.3562896}
}

@article{BROWN2019113734,
title = {Shaping photovoltaic array output to align with changing wholesale electricity price profiles},
journal = {Applied Energy},
volume = {256},
pages = {113734},
year = {2019},
issn = {0306-2619},
doi = {https://doi.org/10.1016/j.apenergy.2019.113734},
url = {https://www.sciencedirect.com/science/article/pii/S0306261919314217},
author = {Patrick R. Brown and Francis M. O’Sullivan},
keywords = {Solar energy, Photovoltaics, Locational marginal pricing, Electricity markets, Curtailment},
abstract = {Large-scale deployment of solar photovoltaics (PV) contributes to the
occurrence of depressed—and sometimes negative—electricity prices during daylight
hours as PV displaces higher-cost generators in the merit-order dispatch stack.
These changes in electricity price provide an opportunity to increase the wholesale
energy revenue of PV generators through temporal shaping of PV output. Here, we
explore the impact of three output-shaping strategies on PV wholesale energy revenue
and capacity factor: utilization of 1-axis tracking, curtailment during
negative-price hours, and modification of fixed-tilt array orientation.
Utility-scale PV arrays are modeled at more than 10,000 pricing nodes across six
United States electricity markets over the 2010–2017 time period. Large changes in
revenue-optimized output profiles are observed for the California system, where
solar capacity penetration has increased from ∼2% of peak load in 2010 to ∼28% of
peak load in 2017, and the wholesale revenue benefits of temporal output shaping are
increasing with time. On the California real-time market in 2017, compared to
capacity-factor-optimized fixed-tilt arrays with must-run operation, curtailment
increases revenues by 9%, curtailment in conjunction with fixed-tilt orientation
optimization increases revenues by 20%, 1-axis tracking without curtailment
increases revenues by 32%, and 1-axis tracking with curtailment increases revenues
by 42% for the median node. Median optimal fixed-tilt azimuths for PV on the
real-time market in California have increased from 192° in 2010 to 235° (i.e. 55°
west of south) in 2017. Among the markets and years studied, the California market
in 2017 demonstrates the largest potential benefit from temporal output shaping.
These results highlight mechanisms for mitigating some of the decline in PV
wholesale value at high solar penetrations, and illustrate the importance of
adapting PV installation and dispatch strategies to changing power system
conditions.}
}

@article{BROWN2020109594,
title = {Spatial and temporal variation in the value of solar power across United States electricity markets},
journal = {Renewable and Sustainable Energy Reviews},
volume = {121},
pages = {109594},
year = {2020},
issn = {1364-0321},
doi = {https://doi.org/10.1016/j.rser.2019.109594},
url = {https://www.sciencedirect.com/science/article/pii/S1364032119308020},
author = {Patrick R. Brown and Francis M. O'Sullivan},
keywords = {Solar energy, Photovoltaics, Value of solar, Locational marginal price, Distributed energy resources, Merit order effect, Air pollution, Capacity value, Resource adequacy},
abstract = {The cost of utility-scale photovoltaics (PV) has declined rapidly over the
past decade. Yet increased renewable electricity generation, decreased natural gas
prices, and deployment of emissions-control technology across the United States have
led to concurrent changes in electricity prices and power system emissions rates,
each of which influence the value of PV electricity. An ongoing assessment of the
economic competitiveness of PV is therefore necessary as PV cost and value continue
to evolve. Here, we use historical nodal electricity prices, capacity market prices,
marginal power system emissions rates of CO2 and air pollutants, and weather data to
model the energy, capacity, health, and climate value of PV electricity at over
10 000 locations across six U.S. Independent System Operators (ISOs) from 2010 to
2017. On the energy and capacity markets, transmission congestion in some locations
and years results in PV revenues that are more than double the median across the
relevant ISO. While the marginal public health benefits from avoided SO2, NOx, and
PM2.5 emissions have declined over time in most ISOs, monetizing the health benefits
of PV generation in 2017 would increase median PV energy revenues by 70% in MISO and
NYISO and 100% in PJM. Given 2017 PV costs, electricity prices, and grid conditions,
PV breaks even at 30% of modeled locations on the basis of energy, capacity, and
health benefits, at 75% of modeled locations with the addition of a 50 $/ton CO2
price, and at 100% of modeled locations with a 100 $/ton CO2 price. These results
suggest that PV cost decline has outpaced value decline over the past decade, such
that in 2017 the net benefits of utility-scale PV outweigh the cost at the majority
of modeled locations.}
}
Loading
Loading