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Robust opportunisti...
Robust opportunistic optimal energy management of a mixed microgrid under asymmetrical uncertainties
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- Nammouchi, Amal (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
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- Aupke, Phil (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013)
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- D’Andreagiovanni, Fabio (author)
- , French National Centre for Scientific Research (CNRS), France; Sorbonne Universités, France
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- Ghazzai, Hakim (author)
- King Abdullah University of Science and Technology (KAUST), Saudi Arabia
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- Theocharis, Andreas (author)
- Karlstads universitet,Institutionen för ingenjörsvetenskap och fysik (from 2013)
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- Kassler, Andreas, 1968- (author)
- Karlstads universitet,Institutionen för matematik och datavetenskap (from 2013),Deggendorf Institute of Technology, Germany
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(creator_code:org_t)
- Elsevier, 2023
- 2023
- English.
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In: Sustainable Energy, Grids and Networks. - : Elsevier. - 2352-4677. ; 36
- Related links:
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https://doi.org/10.1...
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https://kau.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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Abstract
Subject headings
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- Energy management within microgrids under the presence of large number of renewables such as photovoltaics is complicated due to uncertainties involved. Randomness in energy production and consumption make both the prediction and optimality of exchanges challenging. In this paper, we evaluate the impact of uncertainties on optimality of different robust energy exchange strategies. To address the problem, we present AIROBE, a data-driven system that uses machine-learning-based predictions of energy supply and demand as input to calculate robust energy exchange schedules using a multiband robust optimization approach to protect from deviations. AIROBE allows the decision maker to tradeoff robustness with stability of the system and energy costs. Our evaluation shows, how AIROBE can deal effectively with asymmetric deviations and how better prediction methods can reduce both the operational cost while at the same time may lead to increased operational stability of the system.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Naturresursteknik -- Energisystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Environmental Engineering -- Energy Systems (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Energiteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Energy Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Keyword
- Decision making
- Economics
- Forecasting
- Machine learning
- Optimization
- Smart power grids
- System stability
- Energy exchanges
- Machine learning and AI
- Machine-learning
- Microgrid
- Optimality
- Renewable energies
- Robust energy
- Robust optimization
- Smart grid
- Uncertainty
- Energy management
- Computer Science
- Datavetenskap
Publication and Content Type
- ref (subject category)
- art (subject category)
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