Comparing concentrating solar and nuclear power as baseload providers using the example of South Africa

Pfenninger, Stefan; Keirstead, James

doi:10.1016/j.energy.2015.04.077

Cited by 41 publications

(24 citation statements)

References 56 publications

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“…5 British Electricity Trading and Transmission Arrangements. 6 Modern Era Retrospective-Analysis for Research and Applications. 7 Hadley Centre Central England Temperature.…”

Section: Modelling Demandmentioning

confidence: 99%

“…This provides hope, as moving electricity generation to renewables, followed by electrification of other key sectors (notably heat and transport) is widely thought to be the most feasible way to rapidly reduce energy sector emissions [4,5]. While other options such as nuclear, carbon capture and storage (CCS) and biofuels were expected to play significant role, they are either no longer cost-competitive [3,6], or have failed to become market-ready [7]. However, wind and solar power are dependent on weather and thus variable (or intermittent), fluctuating at timescales ranging from minutes to hours to multiple days [8], as well as across years and decades [9,10].…”

Section: Introductionmentioning

confidence: 99%

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The increasing impact of weather on electricity supply and demand

Staffell

Pfenninger

2018

Energy

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256

109

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a b s t r a c tWind and solar power have experienced rapid cost declines and are being deployed at scale. However, their output variability remains a key problem for managing electricity systems, and the implications of multi-day to multi-year variability are still poorly understood. As other energy-using sectors are electrified, the shape and variability of electricity demand will also change. We develop an open framework for quantifying the impacts of weather on electricity supply and demand using the Renewables.ninja and DESSTINEE models. We demonstrate this using a case study of Britain using National Grid's Two Degrees scenario forwards to 2030.We find the British electricity system is rapidly moving into unprecedented territory, with peak demand rising above 70 GW due to electric heating, and intermittent renewable output exceeding demand as early as 2021. Hourly ramp-rates widen by 50% and year-to-year variability increases by 80%, showing why future power system studies must consider multiple years of data, and the influence of weather on both supply and demand. Our framework is globally applicable, and allows detailed scenarios of hourly electricity supply and demand to be explored using only limited input data such as annual quantities from government scenarios or broader energy systems models.

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“…5 British Electricity Trading and Transmission Arrangements. 6 Modern Era Retrospective-Analysis for Research and Applications. 7 Hadley Centre Central England Temperature.…”

Section: Modelling Demandmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The increasing impact of weather on electricity supply and demand

Staffell

Pfenninger

2018

Energy

Self Cite

256

109

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“…Five-yearly average construction durations for Asian reactors that began commercial operation between 1980 and 2010 were sourced from the IAEA (2013) [48]. Also included are estimates pertaining to reactors currently under construction or that recently began commercial operation [20,31].…”

Section: Construction Durationmentioning

confidence: 99%

“…However, wind and photovoltaics are technically different to conventional power generation technologies, having variable availability, and being non-synchronous [17]. This has prompted renewed consideration of conventional nuclear generation as an important low emissions technology for expanded deployment [7], even in jurisdictions where wind and photovoltaics are abundantly available, such as South Africa [20] and Australia [21]. This has prompted renewed consideration of conventional nuclear generation as an important low emissions technology for expanded deployment [7], even in jurisdictions where wind and photovoltaics are abundantly available, such as South Africa [20] and Australia [21].…”

Section: Introductionmentioning

confidence: 99%

“…Integrating large quantities of these technologies will therefore necessitate changes to power system operation and planning [18,19]. This has prompted renewed consideration of conventional nuclear generation as an important low emissions technology for expanded deployment [7], even in jurisdictions where wind and photovoltaics are abundantly available, such as South Africa [20] and Australia [21].…”

Section: Introductionmentioning

confidence: 99%

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Quantifying key uncertainties in the costs of nuclear power

Riesz

Sotiriadis

Vithayasrichareon

et al. 2016

Int. J. Energy Res.

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Summary In power system portfolio decisions, cost risk (uncertainty over cost) should be an important consideration, in addition to central estimates of cost. This study quantifies the uncertainty in each of the cost components for nuclear power, and combines them using a Monte Carlo analysis, allowing a direct assessment of cost risk for this technology. This can be used as an input to sophisticated portfolio optimisation modelling tools that take cost risk into account. Levelised cost of energy (LCOE) estimates are also provided here to allow an indicative comparison of the scale of cost risk, compared with other technologies. The most important contributors to cost risk for nuclear power generation are identified to be overnight capital cost (OCC) estimates, the degree of cost escalation over the construction and pre‐construction periods and the duration of those periods. In the absence of cost escalation, the mean LCOE of nuclear power is found to be AU$145/MWh in jurisdictions excluding Asia (or AU$130/MWh if Asian plant costs are included in the distributions), with a standard deviation of AU$62/MWh. However, when cost escalation over construction and pre‐construction periods is included at rates observed during nuclear build programs in France and the USA, the mean LCOE increases to AU$515/MWh, with a standard deviation of AU$2646/MWh. These results indicate that nuclear power costs have an 80% probability of exceeding AU$170/MWh, and a 50% probability of exceeding AU$278/MWh, based upon Monte Carlo analysis. This suggests that for OECD jurisdictions without an established nuclear industry (such as Australia), nuclear power may be comparable in cost with ‘dispatchable’, synchronous renewable alternatives such as concentrating solar thermal. Furthermore, the considerable cost risk associated with nuclear power is a significant disadvantage. Copyright © 2016 John Wiley & Sons, Ltd.

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