Evidence map›Paper›PMID 33551539›Full record

ArticleApplied energy2021

Quantitative assessment of U.S. bulk power systems and market operations during the COVID-19 pandemic.

Guangchun Ruan, Jiahan Wu, Haiwang Zhong, Qing Xia, Le Xie

Abstract read
In one paragraph

Article in Applied energy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Data-driven operation of the resilient electric grid: A case of COVID-19.Journal of engineering (Stevenage, England) · 2021
    Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Guangchun RuanDepartment of Electrical Engineering, the State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment, Tsinghua University, Beijing 100084, China.
Jiahan WuDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.
Haiwang ZhongDepartment of Electrical Engineering, the State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment, Tsinghua University, Beijing 100084, China.
Qing XiaDepartment of Electrical Engineering, the State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment, Tsinghua University, Beijing 100084, China.
Le XieDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Starting in early 2020, the novel coronavirus disease (COVID-19) severely attached the U.S., causing substantial changes in the operations of bulk power systems and electricity markets. In this paper, we develop a data-driven analysis to substantiate the pandemic's impacts from the perspectives of power system security, electric power generation, electric power demand and electricity prices. Our results suggest that both electric power demand and electricity prices have discernibly dropped during the COVID-19 pandemic. Geographically diverse impacts are observed and quantified, while the bulk power systems and markets in the northeast region are most severely affected. All the data sources, assessment criteria, and analysis codes reported in this paper are available on a GitHub repository.

Indexed as

COVID-19 pandemicData-driven analysisElectricity marketImpact analysisPower system

Identifiers

PMID33551539
PMCPMC7846474

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.