Load duration curve: A tool for technico-economic analysis of energy solutions

Poulin, Alain; Dostie, M.; Fournier, Michaël; Sansregret, Simon

doi:10.1016/j.enbuild.2007.01.020

Cited by 50 publications

(28 citation statements)

References 2 publications

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“…Modelling future demand is a significant problem in itself: many studies which project future power demand neglect the possible changes to consumption patterns and simply scale existing profiles [41]. Past work has either projected future demand from single sectors or consumers [42e44], or has been limited to predicting individual features such as load duration curves [45,46] or peak load [16,47]. State-of-the art methods to generate more realistic future load profiles either apply trend extrapolation [48,49], model specific appliances and sectors [50e52], or focus on extreme events and the relationship between demand and temperature [53e55].…”

Section: Introductionmentioning

confidence: 99%

The increasing impact of weather on electricity supply and demand

Staffell

Pfenninger

2018

Energy

242

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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Section: Introductionmentioning

confidence: 99%

The increasing impact of weather on electricity supply and demand

Staffell

Pfenninger

2018

Energy

242

109

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“…4. A simplest powers distribution with the same energetic effects is given by the load duration curve (LDC) similar to a load curve but the demand data is ordered in descending order of magnitude, rather than chronologically [18]. To facilitate the numerical analysis, the continuous function is approximated by a step function.…”

Section: Minimize the Hydrogen Consumption During A Cyclementioning

confidence: 99%

“…To minimize the hydrogen consumption, during a cycle, the bilevel optimization procedure described in (18) and (19) has been used with the limits of the nozzle opening s min , s max and of the current density J min , J max from Table 2. The optimization procedure has been applied for two different scenarios: Scenario 1 takes into consideration that FC produces a net power corresponding to a load duration curve (Fig.…”

Section: Minimize the Hydrogen Consumption Over A Load Duration Curvementioning

confidence: 99%

Strategies for optimizing the opening of the outlet air circuit’s nozzle to improve the efficiency of the PEMFC generator

2011

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“…In reference (Poulin et al, 2007), the authors discuss in their study that by considering the relationship between the electric power demand and time, the accuracy and relevance of energy solution analysis for a customer could be greatly improved. Through Monte Carlo simulations, the algorithm for generation of realistic synthetic load duration curve can be implemented.…”

Section: Introductionmentioning

confidence: 99%

Long-term load forecasting for the Kingdom of Bahrain using Monte Carlo method

Qader

Qamber

2010

Journal of the Association of Arab Universities for Basic and A

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The present study applies Monte Carlo method to electric power network of the Kingdom of Bahrain over a period of five years taking into consideration the maximum electrical loads. The basic variables of the Monte Carlo method are presented and discussed from the standard deviation and reserve points of view. The maximum loads and simulation results were compared on a weekly and yearly basis. A comparison of the minimum mean square error has been calculated and plotted. The results show similarity between the forecasted data and simulation results.

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Load duration curve: A tool for technico-economic analysis of energy solutions

Cited by 50 publications

References 2 publications

The increasing impact of weather on electricity supply and demand

The increasing impact of weather on electricity supply and demand

Strategies for optimizing the opening of the outlet air circuit’s nozzle to improve the efficiency of the PEMFC generator

Long-term load forecasting for the Kingdom of Bahrain using Monte Carlo method

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