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Effect of Short-ter...
Effect of Short-term and High-resolution Load Forecasting Errors on Microgrid Operation Costs
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- Antoniadou-Plytaria, Kyriaki, 1989 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Eriksson, Ludvig (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Johansson, Jakob (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Johnsson, Richard (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Kötz, Lasse (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Lamm, Johan (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Lundblad, Ellinor (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Steen, David, 1983 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Le, Anh Tuan, 1974 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Carlson, Ola, 1955 (author)
- Chalmers tekniska högskola,Chalmers University of Technology
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(creator_code:org_t)
- ISBN 9781665480321
- 2022
- 2022
- English.
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In: IEEE PES Innovative Smart Grid Technologies Conference Europe. - 9781665480321 ; 2022-October
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https://doi.org/10.1...
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Abstract
Subject headings
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- The aim of this paper is to evaluate the effect of the load forecasting errors to the operation costs of a grid-connected microgrid. To this end, a microgrid energy scheduling optimization model was tested with deterministic and stochastic formulations under two solution approaches i.e., day-ahead and rolling horizon optimization. In total, twelve simulation test cases were designed receiving as input the forecasts provided by one of the three implemented machine learning models: linear regression, artificial neural network with backpropagation, and long short-term memory. Simulation results of the weekly operation of a real residential building (HSB Living Lab) showed no significant differences among the costs of the test cases for a daily mean absolute percentage forecast error of about 12%. These results suggest that operators of similar microgrid systems could use simplifying approaches, such as day-ahead deterministic optimization, and forecasts of similar, non-negligible accuracy without substantially affecting the microgrid's total cost as compared to the ideal case of perfect forecast. Improving the accuracy would mainly reduce the microgrid's peak power cost as shown by its 20.2% increase in comparison to the ideal case.
Subject headings
- NATURVETENSKAP -- Matematik -- Beräkningsmatematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Computational Mathematics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
- 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)
Keyword
- microgrid
- machine learning
- battery
- stochastic optimization
- load forecasting
- energy management
Publication and Content Type
- kon (subject category)
- ref (subject category)
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Antoniadou-Plyta ...
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Eriksson, Ludvig
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Johansson, Jakob
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Johnsson, Richar ...
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Kötz, Lasse
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Lamm, Johan
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show more...
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Lundblad, Ellino ...
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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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- About the subject
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Mathematics
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and Computational Ma ...
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- ENGINEERING AND TECHNOLOGY
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ENGINEERING AND ...
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and Electrical Engin ...
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and Computer Systems
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- ENGINEERING AND TECHNOLOGY
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ENGINEERING AND ...
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and Electrical Engin ...
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and Other Electrical ...
- Articles in the publication
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IEEE PES Innovat ...
- By the university
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Chalmers University of Technology