Quantifying the flexibility of residential electricity demand in 2050: a bottom-up approach

Stiphout, Arne van; Engels, Jonas; Guldentops, Dries

doi:10.1109/ptc.2015.7232411

Cited by 11 publications

(13 citation statements)

References 9 publications

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“…The scanning absorptometer measurement, performed with a KM500win Automatic Scanning Absorptometer instrument from KRK Kumagai (Japan), provides quantitative information about the liquid absorption as a function of time on time scales of 10 ms up to 10 s. 12,17 During an SA measurement, liquid is supplied from a scanning head which moves along a spiral path on the paper. In Fig.…”

Section: Scanning Absorptometer (Sa)mentioning

confidence: 99%

“…The wetting parameter here is a calculated contact angle, computed from the measured liquid penetration using the Lucas-Washburn equation. [17][18][19] For liquid penetration ultrasonic measurement is available in different congurations. All of them indicate the liquid penetration into paper and the wetting behaviour using ultrasound intensity.…”

Section: Introductionmentioning

confidence: 99%

“…The potential of the SA for characterising the direct liquid uptake has been studied and shows good results for measuring penetration. 6,12,17 Liquid penetration of single droplets has been investigated in this study using the contact angle instrument. The change in drop volume over time is calculated from an image sequence taken by the CA instrument.…”

Section: Introductionmentioning

confidence: 99%

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Short timescale wetting and penetration on porous sheets measured with ultrasound, direct absorption and contact angle

Krainer

Hirn

2018

RSC Adv.

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In this study the short timescale penetration and spreading of liquids on porous sheets is investigated. Three measurement techniques are evaluated: ultrasonic liquid penetration measurement (ULP), contact angle measurement (CA) and scanning absorptiometry (SA). With each of these techniques liquid penetration as well as surface wetting can be measured. A quantitative comparison between the methods is carried out. For our studies we are using model liquids with tuneable surface tension, viscosity and surface energy which are the governing parameters for pore flow according to the Lucas-Washburn equation.Scanning absorptiometry turns out to be an adequate tool for direct measurement for liquid penetration.Ultrasonic liquid penetration showed a stable correlation (R 2 ¼ 0.70) to SA and thus also gives a suitable indication on the liquid penetration behaviour. Absorption of individual microliter drops measured in the CA instrument showed different results than the other two measurements. For characterisation of the wetting behaviour the measurement techniques gave substantially different results. We thus conclude that ULP and SA do not capture the wetting behaviour of liquids on paper in the same way as conventional contact angle measurement, it is unclear if their results are meaningful. Finally we are proposing two parameters indicating a combination of liquid penetration and wetting, the slope of the contact angle over time dq/dt and a contact angle calculated from SA. These two parameters are moderately correlated, supporting the idea that they are indeed capturing a combination of liquid penetration and wetting. While our investigations are restricted to paper, we believe that the methods investigated here are generally applicable to study liquid absorption in thin porous media like microfluidic paper based analytical devices, thin porous storage media, membranes and the like. Our findings are highlighting the importance to have a match in timescale (time for penetration and wetting) and size scale (liquid amount supplied) between the testing method and the actual use case of the material, when analyzing wetting and penetration on porous materials.

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Section: Scanning Absorptometer (Sa)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Short timescale wetting and penetration on porous sheets measured with ultrasound, direct absorption and contact angle

Krainer

Hirn

2018

RSC Adv.

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“…A number of approaches has been researched previously with various levels of lower level information. The available flexible capacity of a residential VPP was estimated using lower level device specifications (white box technique) to enable efficient and reliable aggregator services [6]. This technique was applied to a distributed control system with a low error of 5% for homogeneous and heterogeneous clusters.…”

Section: Related Workmentioning

confidence: 99%

Performance Assessment of Black Box Capacity Forecasting for Multi-Market Trade Application

2017

Self Cite

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Abstract:With the growth of renewable generated electricity in the energy mix, large energy storage and flexible demand, particularly aggregated demand response is becoming a front runner as a new participant in the wholesale energy markets. One of the biggest barriers for the integration of aggregator services into market participation is knowledge of the current and future flexible capacity. To calculate the available flexibility, the current aggregator pilot and simulation implementations use lower level measurements and device specifications. This type of implementation is not scalable due to computational constraints, as well as it could conflict with end user privacy rights. Black box machine learning approaches have been proven to accurately estimate the available capacity of a cluster of heating devices using only aggregated data. This study will investigate the accuracy of this approach when applied to a heterogeneous virtual power plant (VPP). Firstly, a sensitivity analysis of the machine learning model is performed when varying the underlying device makeup of the VPP. Further, the forecasted flexible capacity of a heterogeneous residential VPP was applied to a trade strategy, which maintains a day ahead schedule, as well as offers flexibility to the imbalance market. This performance is then compared when using the same strategy with no capacity forecasting, as well as perfect knowledge. It was shown that at most, the highest average error, regardless of the VPP makeup, was still less than 9%. Further, when applying the forecasted capacity to a trading strategy, 89% of the optimal performance can be met. This resulted in a reduction of monthly costs by approximately 20%.

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“…The DR-based methods are often tailored to the underlying DR scheme (i.e., price-based or incentive-based DR) and their main objective is to model the responsiveness of customers to price signals or incentive programs. In pricebased DR schemes, an elasticity matrix models customer flexibility as changes in aggregated demand in response to price changes [11,12,13,14]. However, an elasticity matrix can only measure the aggregated flexibility potential and not the appliance specific flexibility.…”

Section: State Of the Art In Residential Flexibility Assessmentmentioning

confidence: 99%

Modeling and analysis of residential flexibility: Timing of white good usage

et al. 2016

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Challenges that smart grids aim to address include the increasing fraction of supply by renewable energy sources, as well as plain rise of demand, e.g., by increased electrification of transportation. Part of the solution to these challenges lies in exploiting the opportunity to steer residential electricity consumption (e.g., for flattening the peak load or balancing the supply and demand in presence of the renewable energy production). To optimally exploit this opportunity, it is crucial to have insights on how flexible the residential demand is. Load flexibility is characterized by the amount of power, time of availability and duration of deferrable consumption. Residential flexibility however, is challenging to exploit due to the variation in types of customer loads and differences in appliance usage habits from one household to the other. Existing analyses of individual customer flexibility behavior in terms of timing are often based on inferences from surveys or customer load patterns (e.g., as observed through smart meter data): there is a high level of uncertainty about customer habits in offering the flexibility. Even though some of these studies rely on real world data, only few of them have quantitative data on actual flexible appliance usage, and none of them characterizes individual user behavior. In this paper, we address this gap and contribute with: (1) a new quantitative specification of flexibility, (2) two systematic methodologies for modeling individual customer behavior, (3) evaluation of the proposed models in terms of how accurately the data they generate corresponds with real world customer behavior, and (4) a basic analysis of factors influencing the flexibility behavior based on statistical tests. Experimental results for (2)-(4) are based on a unique dataset from a real-life field trial.

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Quantifying the flexibility of residential electricity demand in 2050: a bottom-up approach

Cited by 11 publications

References 9 publications

Short timescale wetting and penetration on porous sheets measured with ultrasound, direct absorption and contact angle

Short timescale wetting and penetration on porous sheets measured with ultrasound, direct absorption and contact angle

Performance Assessment of Black Box Capacity Forecasting for Multi-Market Trade Application

Modeling and analysis of residential flexibility: Timing of white good usage

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