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Development of a DS...
Development of a DSO Support Tool for Congestion Forecast
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- Srivastava, Ankur, 1989 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Steen, David, 1983 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Le, Anh Tuan, 1974 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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visa fler...
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- Carlson, Ola, 1955 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Bouloumpasis, Ioannis, 1987 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Tran, Quoc Tuan (författare)
- Le Commissariat à l’Énergie Atomique et aux Énergies Alternatives (CEA),The French Alternative Energies and Atomic Energy Commission (CEA)
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- Lemius, Lucile (författare)
- Atos Worldgrid SAS
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visa färre...
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(creator_code:org_t)
- 2021-08-17
- 2021
- Engelska.
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Ingår i: IET Generation, Transmission and Distribution. - : Institution of Engineering and Technology (IET). - 1751-8687 .- 1751-8695. ; 15:23, s. 3345-3359
- Relaterad länk:
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https://research.cha... (primary) (free)
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https://onlinelibrar...
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https://research.cha...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- This paper presents a novel DSO support tool with visualisation capability for forecasting network congestion in distribution systems with a high level of renewables. To incorporate the uncertainties in the distribution systems, the probabilistic power flow framework has been utilised. An advanced photovoltaic production forecast based on sky images and a load forecast using an artificial neural network is used as the input to the tool. In addition, advanced load models and operating modes of photovoltaic inverters have been incorporated into the tool. The tool has been applied in case studies to perform congestion forecasts for two real distribution systems to validate its usability and scalability. The results from case studies demonstrated that the tool performs satisfactorily for both small and large networks and is able to visualise the cumulative probabilities of nodes voltage deviation and network components (branches and transformers) congestion for a variety of forecast horizons as desired by the DSO. The results have also shown that explicit inclusion of load-voltage dependency models would improve the accuracy of the congestion forecast. For demonstrating the applicability of the tool, it has been integrated into an existing distribution management system via the IoT platform of a DMS vendor, Atos Worldgrid.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
Publikations- och innehållstyp
- art (ämneskategori)
- ref (ämneskategori)
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Srivastava, Anku ...
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Steen, David, 19 ...
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Le, Anh Tuan, 19 ...
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Carlson, Ola, 19 ...
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Bouloumpasis, Io ...
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Tran, Quoc Tuan
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visa fler...
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Lemius, Lucile
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visa färre...
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