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Surrogate models fo...
Surrogate models for rural energy planning : Application to Bolivian lowlands isolated communities
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- Balderrama, Sergio (författare)
- Univ Liege, Integrated & Sustainable Energy Syst, Liege, Belgium.;San Simon Univ, Ctr Univ Invest Energia, Cochabamba, Bolivia.
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- Lombardi, Francesco (författare)
- Politecn Milan, Dept Energy, Milan, Italy.;Delft Univ Technol, Dept Engn Syst & Serv, Delft, Netherlands.
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- Stevanato, Nicolo (författare)
- Politecn Milan, Dept Energy, Milan, Italy.;FEEM Fdn Eni Enrico Mattei, Milan, Italy.
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- Pena Balderrama, J. Gabriela, 1990- (författare)
- KTH,Energiteknik
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- Colombo, Emanuela (författare)
- Politecn Milan, Dept Energy, Milan, Italy.
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- Quoilin, Sylvain (författare)
- Univ Liege, Integrated & Sustainable Energy Syst, Liege, Belgium.
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Univ Liege, Integrated & Sustainable Energy Syst, Liege, Belgium;San Simon Univ, Ctr Univ Invest Energia, Cochabamba, Bolivia. Politecn Milan, Dept Energy, Milan, Italy.;Delft Univ Technol, Dept Engn Syst & Serv, Delft, Netherlands. (creator_code:org_t)
- Elsevier BV, 2021
- 2021
- Engelska.
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Ingår i: Energy. - : Elsevier BV. - 0360-5442 .- 1873-6785. ; 232
- Relaterad länk:
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https://lirias.kuleu...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Thanks to their modularity and their capacity to adapt to different contexts, hybrid microgrids are a promising solution to decrease greenhouse gas emissions worldwide. To properly assess their impact in different settings at country or cross-country level, microgrids must be designed for each particular situation, which leads to computationally intractable problems. To tackle this issue, a methodology is proposed to create surrogate models using machine learning techniques and a database of microgrids. The selected regression model is based on Gaussian Processes and allows to drastically decrease the computation time relative to the optimal deployment of the technology. The results indicate that the proposed methodology can accurately predict key optimization variables for the design of the microgrid system. The regression models are especially well suited to estimate the net present cost and the levelized cost of electricity (R-2 = 0.99 and 0.98). Their accuracy is lower when predicting internal system variables such as installed capacities of PV and batteries (R-2 = 0.92 and 0.86). A least-cost path towards 100% electrification coverage for the Bolivian lowlands mid-size communities is finally computed, demonstrating the usability and computational efficiency of the proposed framework.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Energiteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Energy Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Naturresursteknik -- Energisystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Environmental Engineering -- Energy Systems (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
Nyckelord
- Microgrids
- Energy planning
- Isolated energy systems
- Ruralelectrification
- Open energy modelling
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- art (ämneskategori)
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