Hyppää sisältöön
    • Suomeksi
    • In English
  • Suomeksi
  • In English
  • Kirjaudu
Näytä aineisto 
  •   Etusivu
  • OSUVA
  • Artikkelit
  • Näytä aineisto
  •   Etusivu
  • OSUVA
  • Artikkelit
  • Näytä aineisto
JavaScript is disabled for your browser. Some features of this site may not work without it.

Optimal scheduling of an active distribution system considering distributed energy resources, demand response aggregators and electrical energy storage

Zakernezhad, Hamid; Setayesh Nazar, Mehrdad; Shafie-khah, Miadreza; Catalao, Joao P.S. (2022-05-15)

 
Katso/Avaa
Artikkeli (7.533Mb)
Lataukset: 

URI
https://doi.org/10.1016/j.apenergy.2022.118865

Zakernezhad, Hamid
Setayesh Nazar, Mehrdad
Shafie-khah, Miadreza
Catalao, Joao P.S.
Elsevier
15.05.2022
doi:10.1016/j.apenergy.2022.118865
Näytä kaikki kuvailutiedot
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2023020826377

Kuvaus

vertaisarvioitu
© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Tiivistelmä
This paper presents a two-level optimization model for the optimal scheduling of an active distribution system in day-ahead and real-time market horizons. The distribution system operator transacts energy and ancillary services with the electricity market, plug-in hybrid electric vehicle parking lot aggregators, and demand response aggregators. Further, the active distribution system can utilize a switching procedure for its zonal tie-line switches to mitigate the effects of contingencies. The main contribution of this paper is that the proposed framework simultaneously models the arbitrage strategy of the active distribution system, electric vehicle parking lot aggregators, and demand response aggregators in the day-ahead and real-time markets. This paper's solution methodology is another contribution that utilizes robust and lexicographic ordering optimization methods. At the first stage of the first level, the optimal bidding strategies of plug-in hybrid electric vehicle parking lot aggregators and demand response aggregators are explored. Then, at the second stage of the first level, the day-ahead optimization process finds the optimal scheduling of distributed energy resources and switching of electrical switches. Finally, at the second level, the real-time optimization problem optimizes the scheduling of system resources. Different case studies were carried out to assess the effectiveness of the algorithm. The proposed algorithm increases the system's day-ahead and real-time revenues by about 52.09% and 47.04% concerning the case without the proposed method, respectively.
Kokoelmat
  • Artikkelit [3159]
https://osuva.uwasa.fi
Ota yhteyttä | Tietosuoja | Saavutettavuusseloste
 

 

Tämä kokoelma

TekijäNimekeAsiasanaYksikkö / TiedekuntaOppiaineJulkaisuaikaKokoelmat

Omat tiedot

Kirjaudu sisäänRekisteröidy
https://osuva.uwasa.fi
Ota yhteyttä | Tietosuoja | Saavutettavuusseloste