Impact of wind and solar variability on the resource adequacy for North American bulk power system

Abdel-Karim, Noha; Calderon, David; Lauby, M. G.; Coleman, Thomas F.; Moura, John

doi:10.1109/pmaps.2016.7764176

Cited by 6 publications

(5 citation statements)

References 6 publications

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“…Many studies have quantified the value of solar with increasing penetration levels (e.g., Lamont 2008;Mills and Wiser 2013;MIT 2015;Denholm et al 2016), and, in select regions, these model-driven estimates have been complemented by empirical observations based on actual market outcomes with growing solar generation, including the U.S. (Brown and O'Sullivan 2020;Bolinger, Seel, Robson, et al 2021) and Germany (Hirth 2013). Related to the grid services provided by solar, entities responsible for the reliable operation of the grid are interested in better understanding the contribution of solar to reliability (Abdel-Karim et al 2016). The impacts of solar on the dispatch of other generators and on wholesale prices, meanwhile, have been modeled with growing shares of solar (Mills and Wiser 2013;Lew et al 2013;Deetjen et al 2016;Brinkman et al 2016;Bloom et al 2016;Bistline 2017).…”

Section: Introductionmentioning

confidence: 99%

Solar-to-Grid: Trends in System Impacts, Reliability, and Market Value in the United States with Data Through 2020

Mills

Seel

Millstein

et al. 2021

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Section: Introductionmentioning

confidence: 99%

Solar-to-Grid: Trends in System Impacts, Reliability, and Market Value in the United States with Data Through 2020

Mills

Seel

Millstein

et al. 2021

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“…Probably the most elementary SA method is represented by the so-called "Tornado diagram" [69], which is based on OAT designs and is often preferred for its simplicity of calculation, as well as for its capability to display SA results in an effective and immediate way [70][71][72].…”

Section: Tornado Diagrammentioning

confidence: 99%

Sensitivity Analysis and Power Systems: Can We Bridge the Gap? A Review and a Guide to Getting Started

2021

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Power systems are increasingly affected by various sources of uncertainty at all levels. The investigation of their effects thus becomes a critical challenge for their design and operation. Sensitivity Analysis (SA) can be instrumental for understanding the origins of system uncertainty, hence allowing for a robust and informed decision-making process under uncertainty. The SA value as a support tool for model-based inference is acknowledged; however, its potential is not fully realized yet within the power system community. This is due to an improper use of long-established SA practices, which sometimes prevent an in-depth model sensitivity investigation, as well as to partial communication between the SA community and the final users, ultimately hindering non-specialists’ awareness of the existence of effective strategies to tackle their own research questions. This paper aims at bridging the gap between SA and power systems via a threefold contribution: (i) a bibliometric study of the state-of-the-art SA to identify common practices in the power system modeling community; (ii) a getting started overview of the most widespread SA methods to support the SA user in the selection of the fittest SA method for a given power system application; (iii) a user-oriented general workflow to illustrate the implementation of SA best practices via a simple technical example.

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“…Many studies have quantified the value of solar with increasing penetration levels (e.g., Lamont 2008;Mills and Wiser 2013;MIT 2015;Denholm et al 2016), and, in select regions, these model-driven estimates have been complemented by empirical observations based on actual market outcomes with growing solar generation, including the U.S. (Bolinger, Seel, and Robson 2019;Brown and O'Sullivan 2020) and Germany (Hirth 2013). Related to the grid services provided by solar, entities responsible for the reliable operation of the grid are interested in better understanding the contribution of solar to reliability (Abdel-Karim et al 2016). The impacts of solar on the dispatch of other generators and on wholesale prices, meanwhile, have been modeled with growing shares of solar (Mills and Wiser 2013;Lew et al 2013;Deetjen et al 2016;Brinkman et al 2016;Bloom et al 2016;Bistline 2017).…”

Section: Introductionmentioning

confidence: 99%

Solar-to-Grid: Trends in System Impacts, Reliability, and Market Value in the United States with Data Through 2019

Mills

Seel

Millstein

et al. 2021

View full text Add to dashboard Cite

Impact of wind and solar variability on the resource adequacy for North American bulk power system

Cited by 6 publications

References 6 publications

Solar-to-Grid: Trends in System Impacts, Reliability, and Market Value in the United States with Data Through 2020

Solar-to-Grid: Trends in System Impacts, Reliability, and Market Value in the United States with Data Through 2020

Sensitivity Analysis and Power Systems: Can We Bridge the Gap? A Review and a Guide to Getting Started

Solar-to-Grid: Trends in System Impacts, Reliability, and Market Value in the United States with Data Through 2019

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