The sensitivity of power system expansion models

Schyska, Bruno U.; Kies, Alexander; Schlott, Markus; Bremen, Lueder von; Medjroubi, Wided

doi:10.1016/j.joule.2021.07.017

Cited by 30 publications

(12 citation statements)

References 44 publications

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“…Several potential strategies exist to include climate-related uncertainty in energy system models. Sensitivity analysis [34,104], advanced sampling procedures [53][54][55], and robust decision-making [105][106][107] can capture climaterelated uncertainty without modifying energy system model formulations. Advanced sampling aims to minimise the number of energy system model runs by reducing the ensemble size while still capturing its variability.…”

Section: Add Climate-related Uncertainty Analysis To Default Energy S...mentioning

confidence: 99%

Overcoming the disconnect between energy system and climate modeling

Craig

Wohland

Stoop

et al. 2022

Joule

Self Cite

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Section: Add Climate-related Uncertainty Analysis To Default Energy S...mentioning

confidence: 99%

Overcoming the disconnect between energy system and climate modeling

Craig

Wohland

Stoop

et al. 2022

Joule

Self Cite

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“…Schyska et al [101] introduce a different approach: the misallocation metric (Eq. ( 4)), MisallocationMetric i,j .…”

Section: Lcoe Deviationmentioning

confidence: 99%

“…In Ref. [101], the authors use the system LCoE as the objective function and for this reason it is categorized as a cost deviation indicator. The innovative feature is that for the use of this indicator it is not necessary to define a reference model.…”

Section: Lcoe Deviationmentioning

confidence: 99%

Comparison methods of energy system frameworks, models and scenario results

Prina

Nastasi

Groppi

et al. 2022

Renewable and Sustainable Energy Reviews

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“…Sensitivity methods enable the analysis of the impact of input variables on the variation of a system output. The applications of sensitivity techniques in power systems research have been applied to different problems such as generator ranking [25], load classification [26], voltage stability assessment [27], [28], [29], transient response prediction [30], small-disturbance stability [31], power system stabilizer design and frequency support from storage devices and system dynamics [32], [33], or uncertainties in power system models [34], [35]. However, very little work has been done regarding the sensitivity of power quality disturbances to uncertain parameters.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of Voltage Sags Estimation to Uncertainties

Zambrano

Hernàndez²,

Caro³

et al. 2023

IEEE Access

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Voltage sags are power quality disturbances mainly caused by faults with a highly random nature. For this reason, the severity and frequency of occurrence of voltage sags is typically analyzed by means of probabilistic methods, such as Monte Carlo simulations, where different probability distributions are selected to model the uncertain inputs (e.g., fault impedance, fault location, fault rate, etc.). The selection and parameterization of the appropriate probability functions involves many difficulties to ensure that they represent the distribution of input variables in a realistic way and so, many different approaches can be found in literature. This paper studies the sensitivity of voltage sags severity to the uncertainty in the input models in order to focus modeling effort on the input variables that are more critical and effectively have an influence on voltage sags levels, whereas non-influential parameters can be neglected or modeled by means of simplified hypothesis. The method proposed is based on Design of Experiments and Analysis of Variance (ANOVA) and is able to discriminate with a statistic confidence level whether the uncertainty in the input significantly affects voltage sags severity indices or not. The effect of uncertainty on voltage sags indices SARFI90 and SARFI70 has been evaluated in realistic scenarios for IEEE test networks of 24 and 118 buses and in the power system of Ecuador with 357 nodes. General trends have been also established that help to understand the effect of the modeling of input parameters on the estimated number of sags.INDEX TERMS Analysis of variance, design of experiments, sensitivity analysis, power quality, uncertainty, voltage sag.

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The sensitivity of power system expansion models

Cited by 30 publications

References 44 publications

Overcoming the disconnect between energy system and climate modeling

Overcoming the disconnect between energy system and climate modeling

Comparison methods of energy system frameworks, models and scenario results

Sensitivity of Voltage Sags Estimation to Uncertainties

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