Artikel

A MILP algorithm for the optimal sizing of an off-grid hybrid renewable energy system in South Tyrol

The exploitation of renewable energy sources through sustainable energy technologies are taking the field to decrease the pollutions' emissions into the Earth's environment. To offset the limitations of such resources, hybrid energy systems are becoming fundamental in grid-connected applications as well as in off-grid ones. However, the unsteady behavior of renewable sources, such as Sun and Wind, complicates the prediction of the energy production's trend. The main factors and components involved in the design of hybrid energy systems are: (i) type of generators, (ii) their optimal number, (iii) storage systems and (iv) optimal management strategies. All of them have to be considered simultaneously to develop the optimal solution aimed at either reducing the dependence from fossil fuels or granting the supply of energy. In this paper, a methodology based on the Mixed Integer Linear Programming (MILP) is presented and adopted to meet the electric demand of a mountain lodge located in a remote area in South-Tyrol (Italy). The methodology has been developed implementing an algorithm through the Matlab software. The algorithm is capable of evaluating the optimal size of a hybrid off-grid Solar-Wind system with battery storage in order to replace an Internal Combustion Engine (ICE) fueled by diesel.

Sprache
Englisch

Erschienen in
Journal: Energy Reports ; ISSN: 2352-4847 ; Volume: 6 ; Year: 2020 ; Issue: 1 ; Pages: 21-26 ; Amsterdam: Elsevier

Klassifikation
Wirtschaft
Thema
Hybrid off-grid energy system
Matlab
Mixed integer linear programming
Optimization algorithm
Renewable energy

Ereignis
Geistige Schöpfung
(wer)
Alberizzi, Jacopo C.
Rossi, Mosè
Renzi, Massimiliano
Ereignis
Veröffentlichung
(wer)
Elsevier
(wo)
Amsterdam
(wann)
2020

DOI
doi:10.1016/j.egyr.2019.08.012
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Alberizzi, Jacopo C.
  • Rossi, Mosè
  • Renzi, Massimiliano
  • Elsevier

Entstanden

  • 2020

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