Add script that converts the catalyst_cites.bib to a CSV for reporting

devtools/convert_bib_file.py

@@ -0,0 +1,43 @@
+"""Script for converting a .bib file to a .csv file for Sloan Reports."""
+from pathlib import Path
+
+import bibtexparser
+import pandas as pd
+
+OUTPUT_TYPE = {
+    "article": "Journal Article",
+    "book": "Book",
+    "misc": "Miscellaneous",
+    "techreport": "Technical Report",
+}
+
+
+def convert_bib_to_csv():
+    """Convert a .bib file to a .csv file as specified by Sloan's reporting guidelines."""
+    with Path("docs/catalyst_cites.bib").open() as bibtex_file:
+        bib_database = bibtexparser.load(bibtex_file)
+    entires = []
+    for entry in bib_database.entries:
+        first_author = entry.get("author").split(" and")[0]
+        first_author_last_name = first_author.split(" ")[-1]
+        first_author_first_name = " ".join(first_author.split(" ")[:-1])
+        entires.append(
+            pd.Series(
+                {
+                    "Output Type": OUTPUT_TYPE.get(entry.get("ENTRYTYPE"), "Unknown"),
+                    "Author Last Name": first_author_last_name,
+                    "Author First Name": first_author_first_name,
+                    "Output Title": entry.get("title"),
+                    "Output Publication": entry.get("journal"),
+                    "Publication Year": entry.get("year"),
+                    "Weblink or DOI": entry.get("doi"),
+                }
+            )
+        )
+    df = pd.concat(entires, axis=1).T
+    df["Grant Number"] = "G-2021-14184"
+    df.to_csv("devtools/catalyst_cites.csv", index=False)
+
+
+if __name__ == "__main__":
+    convert_bib_to_csv()

docs/catalyst_cites.bib

@@ -100,12 +100,12 @@ @misc{OSClimate
 }
 
 @techreport{PutGasOnStandby,
-  author      = {Sims, Jonathan and
-                 Hillenbrand von der Neyen, Catharina and
-                 D‘souza, Durand and
-                 Chau, Lily and
-                 González-Jiménez, Nicolás and
-                 Sani, Lorenzo},
+  author      = {Jonathan Sims and
+                 Catharina Hillenbrand von der Neyen and
+                 Durand D‘souza and
+                 Lily Chau and
+                 Nicolás González-Jiménez and
+                 Lorenzo Sani},
   abstract    = {Unabated gas plants’ future role in the power system should be predominantly limited
                  to backup reserve to allow for flexible low carbon forms of supply to fully emerge.
                  Events in 2021 have brought the extreme levels of price and supply volatility
@@ -175,7 +175,7 @@ @article{BISTLINE2020114941
   doi      = {https://doi.org/10.1016/j.apenergy.2020.114941},
   url      = {https://www.sciencedirect.com/science/article/pii/S0306261920304530},
   urldate  = {2021-11-01},
-  author   = {Bistline, John E.T. and Merrick, James H.},
+  author   = {John E.T. Bistline and James H. Merrick},
   abstract = {Energy systems models are used to perform energy and environmental policy
               analysis, inform company strategy, and understand implications of technological
               change. Although open-source models can promote transparency and reproducibility, data
@@ -194,7 +194,7 @@ @article{BISTLINE2020114941
 }
 
 @article{doi:10.1146/annurev-environ-020220-061831,
-author = {Donti, Priya L. and Kolter, J. Zico},
+author = {Priya L. Donti and J. Zico Kolter},
 title = {Machine Learning for Sustainable Energy Systems},
 journal = {Annual Review of Environment and Resources},
 volume = {46},
@@ -214,3 +214,113 @@ @article{doi:10.1146/annurev-environ-020220-061831
             we identify gaps in this literature, propose future research directions, and
             discuss important considerations for deployment.}
 }
+
+@misc{zheng2024optimal,
+      title={Optimal transmission expansion minimally reduces decarbonization costs of {U}.{S}. electricity},
+      author={Rangrang Zheng and Greg Schivley and Patricia Hidalgo-Gonzalez and Matthias Fripp and Michael J. Roberts},
+      year={2024},
+      eprint={2402.14189},
+      archivePrefix={arXiv},
+      primaryClass={econ.GN},
+      url={https://doi.org/10.48550/arXiv.2402.14189},
+      doi={10.48550/arXiv.2402.14189},
+      abstract={Solar and wind power are cost-competitive with fossil fuels, yet their
+      intermittent nature presents challenges. Significant temporal and geographic
+      differences in land, wind, and solar resources suggest that long-distance
+      transmission could be particularly beneficial. Using a detailed, open-source
+      model, we analyze optimal transmission expansion jointly with storage, generation,
+      and hourly operations across the three primary interconnects in the United States.
+      Transmission expansion offers far more benefits in a high-renewable system than in
+      a system with mostly conventional generation. Yet while an optimal nationwide plan
+      would have more than triple current interregional transmission, transmission
+      decreases the cost of a 100% clean system by only 4% compared to a plan that
+      relies solely on current transmission. Expanding capacity only within existing
+      interconnects can achieve most of these savings. Adjustments to energy storage and
+      generation mix can leverage the current interregional transmission infrastructure
+      to build a clean power system at a reasonable cost.}
+}
+
+@article{10.1257/jep.37.4.155,
+      Author = {Lucas W. Davis and Catherine Hausman and Nancy L. Rose},
+      Title = {Transmission Impossible? Prospects for Decarbonizing the {U}.{S}. Grid},
+      Journal = {Journal of Economic Perspectives},
+      Volume = {37},
+      Number = {4},
+      Year = {2023},
+      Month = {December},
+      Pages = {155-80},
+      DOI = {10.1257/jep.37.4.155},
+      URL = {https://www.aeaweb.org/articles?id=10.1257/jep.37.4.155},
+      abstract = {Encouraged by the declining cost of grid-scale renewables, recent
+      analyses conclude that the United States could reach net zero carbon dioxide
+      emissions by 2050 at relatively low cost using currently available technologies.
+      While the cost of renewable generation has declined dramatically, integrating
+      these renewables would require a large expansion in transmission to deliver that
+      power. Already there is growing evidence that the United States has insufficient
+      transmission capacity, and current levels of annual investment are well below what
+      would be required for a renewables-dominated system. We describe a variety of
+      challenges that make it difficult to build new transmission and potential policy
+      responses to mitigate them, as well as possible substitutes for some new
+      transmission capacity.}
+}
+
+@article{Miller_2023,
+doi = {10.1088/1748-9326/acc119},
+url = {https://dx.doi.org/10.1088/1748-9326/acc119},
+year = {2023},
+month = {apr},
+publisher = {IOP Publishing},
+volume = {18},
+number = {4},
+pages = {044020},
+author = {Gregory J. Miller and Gailin Pease and Wenbo Shi and Alan Jenn},
+title = {Evaluating the hourly emissions intensity of the {U}.{S}. electricity system},
+journal = {Environmental Research Letters},
+abstract = {High-quality data for the greenhouse gas and air pollution emissions
+            associated with electricity generation and consumption are increasingly
+            important to enable effective and targeted action to decarbonize the
+            electric grid and to inform research in a range of academic disciplines
+            including environmental economics, lifecycle assessment, and environmental
+            health. To inform the broadest range of use cases, such data should ideally
+            have a high temporal and spatial resolution, be available in as close to
+            real-time as possible, represent the complete power sector, use the
+            highest-quality measured data, have complete historical coverage, and
+            represent both generated and consumed emissions. To date, no published
+            datasets have achieved all of these characteristics. This work is the first
+            to publish a comprehensive, plant-level dataset of hourly-resolution
+            generation, fuel consumption, and direct CO2, NOx, and SO2 emissions for the
+            entire U.S. power sector. This data is published as part of the public and
+            open-source Open Grid Emissions Initiative, which also includes hourly,
+            consumption-based emissions intensities for every grid balancing area in the
+            country.  Using insights generated by this new dataset, this paper also
+            interrogates how several of the assumptions implicit in the use of existing
+            power sector emissions datasets may under-count or misrepresent the climate
+            and health impacts of air emissions from the U.S. power sector. We envision
+            the Initiative becoming a central repository of, and hub of activity for
+            addressing open research questions related to power sector emissions data,
+            and the go-to source for high-quality, high-resolution data for future
+            research on grid emissions.}
+}
+
+@book{o2021quantifying,
+  title={Quantifying Operational Resilience Benefits of the Smart Grid},
+  author={Cheyney O'Fallon and Avi Gopstein},
+  year={2021},
+  doi={10.6028/NIST.TN.2137},
+  url={https://doi.org/10.6028/NIST.TN.2137},
+  publisher={Department of Commerce. National Institute of Standards and Technology},
+  abstract={Automated systems for network protection, outage management, and restoration
+            enable electric utilities to maintain service continuity through network
+            reconfiguration. We evalu- ate the impact of interoperability investments on
+            distribution system resilience during Hur- ricane Irma through a reduced
+            form analysis of sustained customer outages. The expected number of
+            interruption hours during that hurricane was relatively lower for regions of
+            the Florida distribution grid that invested more in interoperability
+            enhancements, all else being equal. We use advanced metering infrastructure
+            penetration as a proxy and leading indica- tor of investment in
+            interoperability enhancements. Employing only publicly available data
+            resources, we conservatively estimate that Florida counties that made these
+            investments re- alized nearly $1.7 billion of operational resilience
+            benefits in the form of avoided customer interruption costs during Hurricane
+            Irma.}
+}

docs/further_reading.bib

@@ -249,3 +249,32 @@ @article{doi:10.1021/acs.est.9b04522
             operation.  Finally, we provide a cleaned data set with heat rate curves and
             describe how to use it in general modeling activities and analysis.}
 }
+
+@article{HIRTH2020100433,
+title = {Open data for electricity modeling: Legal aspects},
+journal = {Energy Strategy Reviews},
+volume = {27},
+pages = {100433},
+year = {2020},
+issn = {2211-467X},
+doi = {https://doi.org/10.1016/j.esr.2019.100433},
+url = {https://www.sciencedirect.com/science/article/pii/S2211467X19301269},
+author = {Lion Hirth},
+keywords = {Open data, Electricity system analysis,  database right, Copyright},
+abstract = {Power system modeling is data intensive. In Europe, electricity system data
+            is often available from sources such as statistical offices or system
+            operators.  However, it is often unclear if these data can be legally used
+            for modeling, and in particular if such use infringes intellectual property
+            rights. This article reviews the legal status of power system data, both as
+            a guide for data users and for data publishers. It is based on
+            interpretation of the law, a review of the secondary literature, an analysis
+            of the licenses used by major data distributors, expert interviews, and a
+            series of workshops. A core finding is that in many cases the legality of
+            current practices is doubtful: in fact, it seems likely that modelers
+            infringe intellectual property rights quite regularly. This is true for
+            industry analysis but also academic researchers. A straightforward solution
+            is open data – the idea that data can be freely used, modified, and shared
+            by anyone for any purpose. To be open, it is not sufficient for data to be
+            accessible free of cost, it must also come with an open data license, the
+            most common types of which are also reviewed in this paper.}
+}

docs/release_notes.rst

@@ -11,7 +11,9 @@ Data Cleaning
 
 * When ``generator_operating_date`` values are too inconsistent to be harvested
   successfully, we now take the max date within a year and attempt to harvest again, to
-  rescue records lost because of inconsistent month reporting in EIA 860 and 860M.
+  rescue records lost because of inconsistent month reporting in EIA 860 and 860M. See
+  :issue:`3340` and PR :pr:`3419`. This change also fixed a bug that was preventing
+  other columns harvested with a special process from being saved.
 
 .. _release-v2024.2.6: