Gaussian Mixture Based Uncertainty Modeling to Optimize Energy Management of Heterogeneous Building Neighborhoods:A Case Study of a Dutch University Medical Campus
To realize the goals of energy transition, becoming energy-neutral at the neighborhood level by sharing energy among clusters of heterogeneous buildings with local distributed energy resources (DERs), will play a vital role. However, uncertainties related to demand and renewable sources pose a major operational challenge to schedule the DERs. In this paper, a scenario-based mixed-integer linear programming (MILP) model is proposed for an energy management system (EMS) of a local energy community. The proposed EMS executes a stochastic day-ahead scheduling operation of multi-energy systems (MES... Mehr ...
Verfasser: |
Shafiullah, D.S.
Vergara, Pedro P.
Haque, A.N.M.M.
Nguyen, P.H.
Pemen, A.J.M. |
Dokumenttyp: |
Artikel |
Erscheinungsdatum: |
2020 |
Reihe/Periodikum: |
Shafiullah , D S , Vergara , P P , Haque , A N M M , Nguyen , P H & Pemen , A J M 2020 , ' Gaussian Mixture Based Uncertainty Modeling to Optimize Energy Management of Heterogeneous Building Neighborhoods : A Case Study of a Dutch University Medical Campus ' , Energy and Buildings , vol. 224 , 110150 . https://doi.org/10.1016/j.enbuild.2020.110150 |
Schlagwörter: |
day-ahead scheduling
/ energy hub
/ energy management system
/ Gaussian mixture model
/ multi-energy systems
/ Stochastic optimization
/ Uncertainty
/ /dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy
/ name=SDG 7 - Affordable and Clean Energy |
Sprache: |
Englisch |
Permalink: |
https://search.fid-benelux.de/Record/base-27449703 |
Datenquelle: |
BASE;
Originalkatalog |
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Link(s) :
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https://research.tue.nl/en/publications/de843493-3c56-47ae-a564-1de571037c34 |