Solar and wind grid system value in the United States: The effect of transmission congestion, generation profiles, and curtailment

Millstein, Dev; Wiser, Ryan; Mills, Andrew; Bolinger, Mark; Seel, Joachim; Jeong, Seongeun

doi:10.1016/j.joule.2021.05.009

Cited by 73 publications

(31 citation statements)

References 80 publications

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“…It is the latter set of records that we compare to reanalysis‐based generation estimates. These generation records have been used in prior publications and provide some of the only hourly, plant‐level generation records that are publicly available in the United States 5,23 . Minimal data cleaning was conducted to remove sites with incomplete records and to truncate capacity factors at nominal power capacity (i.e., CF ≤ 1).…”

Section: Methodsmentioning

confidence: 99%

Limitations of reanalysis data for wind power applications

Davidson

Millstein

2022

Wind Energy

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Wind energy resource estimates commonly depend on simulated wind speed profiles generated by reanalysis or weather models due to the lack of long time series measurements with sufficient coverage at relevant heights (roughly 90 m above ground).However, modeled data, including reanalyses, can be noisy and display a wide range of biases and errors, variously attributed to terrain effects, poor coverage of assimilated inputs, and model resolution. Wind generation records, if available at high temporal and geographical resolution, can provide a proxy for wind measurements and allow for evaluation of reanalyses and weather model wind time series. We use a 7-year-long data set of hourly, plant-level generation records from over 100 wind plants across Texas to evaluate two commonly used reanalysis data sets (MERRA2 and ERA5). Additionally, we use 1-year of records (2019) to evaluate an operational, high-resolution regional weather modeling product (HRRR v3). We find that across the region, and across all modeling products, the modeled representation of wind generation (i.e., wind speeds at hub heights passed through a power curve) has relatively small mean errors when aggregated daily, but that accuracy and hourly correlation have a strong diurnal sensitivity. Accuracy and correlation systematically decline through the evening and markedly improve after sunrise. These diurnal patterns persist even in the highest resolution model tested (HRRR v3). We hypothesize the nighttime decline in accuracy is mostly due to poorly represented boundary layer conditions, perhaps related to model representation of stability, while other uncertainties (such as wake effects) play a secondary role.

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Section: Methodsmentioning

confidence: 99%

Limitations of reanalysis data for wind power applications

Davidson

Millstein

2022

Wind Energy

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“…Maintaining strong pressure for cost reduction may be especially important given the many institutional challenges that can slow deployment ( Cherp et al., 2021 ) and the increasing recognition that the grid-system value of wind and solar tends to decline as penetrations increase ( Das et al., 2020 ; Sivaram and Kann, 2016 ). So far, wind and solar cost reductions have kept pace with value declines, but future technology advancement will dictate whether these trends continue ( Millstein et al., 2021 ).…”

Section: Discussionmentioning

confidence: 99%

Levelized cost-based learning analysis of utility-scale wind and solar in the United States

2022

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“…For this system, we consider free lossless electricity transmission to give the greatest possible advantage to variable wind and solar resources relative to competing technologies. Because we do not include the constraints of grid infrastructure (Millstein et al, 2021), generation and curtailment values are likely to be underestimates. In fact, our simulations are not intended to guide siting decisions for real-world applications, but rather to quantify the importance of long-term planning and the potential advantage of considering the wind and solar resource spatiotemporal variability, complementarity, and correlation with residual demand.…”

Section: Limitations Of the Studymentioning

confidence: 99%