A simulative framework for a multi-regional assessment of local energy markets – A case of large-scale electric vehicle deployment in Germany

Cramer, Wilhelm; Schumann, Klemens; Andres, Michael; Vertgewall, Chris Martin; Monti, Antonello; Schreck, Sebastian; Metzger, Michael; Jessenberger, Stefan; Klaus, Joachim; Brunner, Christoph; Heringer, Florian; Alvarado, Axel; Armstorfer, Andreas; Beg, Nauman

doi:10.1016/j.apenergy.2021.117249

Cited by 14 publications

(14 citation statements)

References 21 publications

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“…Energy demand has been derived bottom-up and includes electrical and thermal demand, as used in [18,53,54]. First, a building database is created storing information about each modeled building in the area of investigation.…”

Section: Bottom-up Regionalization Of Demand Datamentioning

confidence: 99%

Analyzing Intersectoral Benefits of District Heating in an Integrated Generation and Transmission Expansion Planning Model

et al. 2022

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In the field of sector integration, the expansion of district heating (DH) is traditionally discussed with regard to the efficient integration of renewable energy sources (RES) and excess heat. But does DH exclusively benefit from other sectors or does it offer advantages in return? So far, studies have investigated DH only as a closed system or determined intersectoral benefits in a highly aggregated approach. We use and expand an integrated generation and transmission expansion planning model to analyze how the flexibility of DH benefits the energy system and the power transmission grid in particular. First of all, the results confirm former investigations that show DH can be used for efficient RES integration. Total annual system cost can be decreased by expanding DH, due to low investment cost and added flexibility, especially from large-scale heat storage. The high short-term efficiency of heat storage—in combination with electric heating technologie —can be exploited to shift heat demand temporally and, using multiple distributed units, locally to solve electric grid congestion. Although it is unclear whether these results can be replicated in the real world, due to the aggregation and detail of the model, further research in this direction is justified.

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Section: Bottom-up Regionalization Of Demand Datamentioning

confidence: 99%

Analyzing Intersectoral Benefits of District Heating in an Integrated Generation and Transmission Expansion Planning Model

et al. 2022

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“…System benefits of LEMs have been indicated in [12,13,14]. The authors of [12,13] claim that LEMs bear the potential to reduce grid expansion given proper coordination of flexibility through LEMs.…”

Section: State Of the Art On System Impact Of Lemsmentioning

confidence: 99%

“…Additionally, they review that the current regulatory regime in Germany is preventing prosumer participation in LEMs, thus reducing development and activation of distributed flexibility. [14] has shown quantitatively that through LEMs, the peak load of local areas and the areas' electricity exchange with the wholesale system is reduced, thus bearing potential benefits of reduced transmission system usage. However, no pan-European simulation of wholesale markets and grid calculations have been carried out in these studies.…”

Section: State Of the Art On System Impact Of Lemsmentioning

confidence: 99%

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How will local energy markets influence the pan-European day-ahead market and transmission systems? A case study for local markets in France and Germany

et al. 2022

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“…While the modelling of synthetic time series (load and generation) and charging profiles is continuously discussed in research, the geo-referencing of electricity demands is still a challenge due to limited data availability. Previous studies such as [2][3][4][5][6] which tackle this topic use socioeconomic data, geospatial data, digital orthophotographs (DOP), or measurement data. Socioeconomic data contains information on the population and building structure of a region.…”

Section: Introductionmentioning

confidence: 99%

Modelling residential supply tasks based on digital orthophotography using machine learning

et al. 2022

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In order to achieve the climate targets, electrification of individual mobility is essential. However, grid integration of electrical vehicles poses challenges for the electrical distribution network due to high charging power and simultaneity. To investigate these challenges in research studies, the network-referenced supply task needs to be modeled. Previous research work utilizes data that is not always complete or sufficiently granular in space. This is why this paper presents a methodology which allows a holistic determination of residential supply tasks based on orthophotos. To do this, buildings are first identified from orthophotos, then residential building types are classified, and finally the electricity demand of each building is determined. In an exemplary case study, we validate the presented methodology and compare the results with another supply task methodology. The results show that the electricity demand deviates from the results of a reference method by an average 9%. Deviations result mainly from the parameterization of the selected residential building types. Thus, the presented methodology is able to model supply tasks similarly as other methods but more granular.

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A simulative framework for a multi-regional assessment of local energy markets – A case of large-scale electric vehicle deployment in Germany

Cited by 14 publications

References 21 publications

Analyzing Intersectoral Benefits of District Heating in an Integrated Generation and Transmission Expansion Planning Model

Analyzing Intersectoral Benefits of District Heating in an Integrated Generation and Transmission Expansion Planning Model

How will local energy markets influence the pan-European day-ahead market and transmission systems? A case study for local markets in France and Germany

Modelling residential supply tasks based on digital orthophotography using machine learning

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