Competitiveness Metrics for Electricity System Technologies

Mai, Trieu; Mowers, Matthew; Newman, Alexandra M.

doi:10.2172/1765599

Cited by 14 publications

(6 citation statements)

References 30 publications

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“…By placing all grid services on an equivalent monetary basis, these new metrics provide a more effective economic comparison across different electricity system technologies. Examples include cost-benefit ratio, system return on investment, and system profit margin (Mai et al, 2021). As more and more costs are reflected in market pricing, the costs will be seen as a lower system value for wind energy-provided the market design is cost-reflective and transparent.…”

Section: Estimating the Value Of Wind Energymentioning

confidence: 99%

Design and Operation of Energy Systems with Large Amounts of Variable Generation: IEA Wind TCP Task 25 (Final Summary Report)

Holttinen¹,

Kiviluoma²,

Helistö³

et al. 2021

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Section: Estimating the Value Of Wind Energymentioning

confidence: 99%

Design and Operation of Energy Systems with Large Amounts of Variable Generation: IEA Wind TCP Task 25 (Final Summary Report)

Holttinen¹,

Kiviluoma²,

Helistö³

et al. 2021

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“…The strong dependence of market value on the policy regime (and on the rest of the system composition) means that market value should be used with a keen awareness of its limitations. Just as the LCOE metric does not provide a complete picture of the cost performance of technologies [46], market value should be used in concert with other metrics when comparing technologies.…”

Section: Policy Implicationsmentioning

confidence: 99%

Decreasing market value of variable renewables can be avoided by policy action

Brown,

Reichenberg

2020

Preprint

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Although recent studies have shown that electricity systems with shares of wind and solar above 80% can be affordable, economists have raised concerns about market integration. Correlated generation from variable renewable sources depresses market prices, which can cause wind and solar to cannibalize their own revenues and prevent them from covering their costs from the market. This cannibalization appears to set limits on the integration of wind and solar, and thus contradict studies that show that high shares are cost effective. Here we show from theory and with numerical examples how policies interact with prices, revenue and costs for renewable electricity systems. The decline in average revenue seen in some recent literature is due to an implicit policy assumption that technologies are forced into the system, whether it be with subsidies or quotas. If instead the driving policy is a carbon dioxide cap or tax, wind and solar shares can rise without cannibalising their own market revenue, even at penetrations of wind and solar above 80%. Policy is thus the primary factor driving lower market values; the variability of wind and solar is only a secondary factor that accelerates the decline if they are subsidised. The strong dependence of market value on the policy regime means that market value needs to be used with caution as a measure of market integration. Keywords: market value of variable renewables, renewable energy policy, CO 2 tax, feed-in-tariff, merit order effect, large-scale integration of renewable power generation Highlights• Decreasing market value (MV) with wind and solar share is a result of policy choices • In long-term equilibria, wind and solar subsidies reduce MV, but CO 2 prices do not • Models with rising CO 2 prices see rising wind and solar (VRE) with no reduction in MV • Falling MV in models with VRE subsidy do not necessarily indicate integration problems • These results are confirmed using economic theory and in a power system model

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“…The interaction of these considerations is visually presented in Figure 1, where the green curve represents LCOE as a function of capacity and is a combination of the orange and blue curves, which show the total plant cost and wake losses respectively. There is much justified discussion about better metrics beyond LCOE to evaluate wind farm performance (Mai et al, 2021b). For the present study, we decided to use LCOE as our evaluation metric due to the wide historical and present use of LCOE in wind plant design and the complexity of including cost models or projections for modeling profit or other more complex financial metrics.…”

Section: An Optimization Approach To Explicitly Site Wind Turbinesmentioning

confidence: 99%

Estimating National-Scale Wind Potential Using Spatially Explicit Turbine Layout Optimization

Lopez,

Stanley,

Roberts

et al. 2023

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National renewable energy potential assessments play a broad and critical role in analysis of the clean energy transition by providing foundational estimates of developable clean resources.Common to all past wind potential assessments is an assumption that wraps the complexity of wind plant layout (i.e., the arrangement of turbines) into a single metric known as capacity density, or rated power capacity per unit of land area. Quite often, a singular capacity density or rotor diameter-driven capacity density is used in wind potential assessments across broad geographies despite the complexities of local drivers.

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Competitiveness Metrics for Electricity System Technologies

Abstract: Department of Energy (DOE) reports produced after 1991 and a growing number of pre-1991 documents are available free via www.OSTI.gov.

Cited by 14 publications

References 30 publications

Design and Operation of Energy Systems with Large Amounts of Variable Generation: IEA Wind TCP Task 25 (Final Summary Report)

Design and Operation of Energy Systems with Large Amounts of Variable Generation: IEA Wind TCP Task 25 (Final Summary Report)

Decreasing market value of variable renewables can be avoided by policy action

Estimating National-Scale Wind Potential Using Spatially Explicit Turbine Layout Optimization

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