Clustering Interval Load with Weather to Create Scenarios of Behind-the-Meter Solar Penetration Article Swipe
Allison Campbell
,
Soumya Kundu
,
Andrew P. Reiman
,
Orestis Vasios
,
Ian Beil
,
Andy Eiden
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2403.05009
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2403.05009
Forecasting load at the feeder level has become increasingly challenging with the penetration of behind-the-meter solar, as this self-generation (also called total generation) is only visible to the utility as aggregated net-load. This work proposes a methodology for creation of scenarios of solar penetration at the feeder level for use by forecasters to test the robustness of their algorithm to progressively higher penetrations of solar. The algorithm draws on publicly available observations of weather \emph{condition} (e.g., rainy/cloudy/fair) for use as proxies to sky clearness. These observations are used to mask and weight the interval deviations of similar native usage profiles from which average interval usage is calculated and subsequently added to interval net generation to reconstruct interval total generation. This approach improves the estimate of annual energy generation by 23\%; where the net generation signal currently only reflects 52\% of total annual generation, now 75\% is captured via the proposed algorithm. This proposed methodology is data driven and extensible to service territories which lack information on irradiance measurements and geo-coordinates.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2403.05009
- https://arxiv.org/pdf/2403.05009
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392678010
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4392678010Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2403.05009Digital Object Identifier
- Title
-
Clustering Interval Load with Weather to Create Scenarios of Behind-the-Meter Solar PenetrationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-03-08Full publication date if available
- Authors
-
Allison Campbell, Soumya Kundu, Andrew P. Reiman, Orestis Vasios, Ian Beil, Andy EidenList of authors in order
- Landing page
-
https://arxiv.org/abs/2403.05009Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2403.05009Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2403.05009Direct OA link when available
- Concepts
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Cluster analysis, Metre, Penetration (warfare), Interval (graph theory), Environmental science, Meteorology, Computer science, Remote sensing, Real-time computing, Engineering, Operations research, Physics, Geography, Mathematics, Artificial intelligence, Astronomy, CombinatoricsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.publicly | 69 |
| abstract_inverted_index.reflects | 137 |
| abstract_inverted_index.algorithm | 58, 66 |
| abstract_inverted_index.available | 70 |
| abstract_inverted_index.currently | 135 |
| abstract_inverted_index.net-load. | 31 |
| abstract_inverted_index.scenarios | 40 |
| abstract_inverted_index.aggregated | 30 |
| abstract_inverted_index.algorithm. | 150 |
| abstract_inverted_index.calculated | 106 |
| abstract_inverted_index.clearness. | 83 |
| abstract_inverted_index.deviations | 94 |
| abstract_inverted_index.extensible | 158 |
| abstract_inverted_index.generation | 113, 127, 133 |
| abstract_inverted_index.irradiance | 166 |
| abstract_inverted_index.robustness | 55 |
| abstract_inverted_index.Forecasting | 0 |
| abstract_inverted_index.challenging | 9 |
| abstract_inverted_index.forecasters | 51 |
| abstract_inverted_index.generation) | 22 |
| abstract_inverted_index.generation, | 142 |
| abstract_inverted_index.generation. | 118 |
| abstract_inverted_index.information | 164 |
| abstract_inverted_index.methodology | 36, 153 |
| abstract_inverted_index.penetration | 12, 43 |
| abstract_inverted_index.reconstruct | 115 |
| abstract_inverted_index.territories | 161 |
| abstract_inverted_index.increasingly | 8 |
| abstract_inverted_index.measurements | 167 |
| abstract_inverted_index.observations | 71, 85 |
| abstract_inverted_index.penetrations | 62 |
| abstract_inverted_index.subsequently | 108 |
| abstract_inverted_index.progressively | 60 |
| abstract_inverted_index.self-generation | 18 |
| abstract_inverted_index.\emph{condition} | 74 |
| abstract_inverted_index.behind-the-meter | 14 |
| abstract_inverted_index.geo-coordinates. | 169 |
| abstract_inverted_index.rainy/cloudy/fair) | 76 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile |