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

* Bump gdal to v3.9.3 and relock dependencies. * Update conda-lock.yml and rendered conda environment files. * Update ruff pre-commit hook and add pubs to bibliography Added Patrick Brown's Zenodo locational marginal pricing (LMP) datasets on Zenodo to the "further reading" in our bibliography since I keep going back to try and find them and it's a pain every time. * Re-lock dependencies with GDAL 3.9.3 --------- Co-authored-by: Zane Selvans <[email protected]> Co-authored-by: zaneselvans <[email protected]>
catalyst-cooperative · Oct 28, 2024 · 28f6249 · 28f6249
1 parent 85e6a94
commit 28f6249
Show file tree

Hide file tree

Showing 8 changed files with 941 additions and 775 deletions.
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -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]

diff --git a/docs/catalyst_pubs.bib b/docs/catalyst_pubs.bib
@@ -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}
+}
diff --git a/docs/further_reading.bib b/docs/further_reading.bib
@@ -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.}
+}