Dynamic optimization of long term primary electric distribution network investments based on planning metrics

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Tor O. B., CEBECI M. E., KOC M., Guven A. N.

JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, cilt.33, sa.1, ss.227-237, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 33 Sayı: 1
  • Basım Tarihi: 2018
  • Doi Numarası: 10.17341/gazimmfd.406795
  • Dergi Adı: JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.227-237
  • Anahtar Kelimeler: Dynamic investment optimization, electric distribution grids, mixed integer programming, planning metrics, POWER DISTRIBUTION, DISTRIBUTION-SYSTEMS
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

This paper presents methodologies of dynamic planning algorithms which are developed for optimizing long-term primary electric distribution network investments taking into account some planning metrics. First, an algorithm which calculates a representative primary network model of distribution grids whose primary and secondary networks are intricate is developed. It is aimed to facilitate assessment of primary distribution network investment requirements and thereby defining grid investment candidates effectively by this reduced network representation. Then, a planning algorithm, which considers the representative network model and candidate investments as inputs, is developed based on a mixed integer programming (MIP) technique. Some planning metrics are defined in order to assess optimum investment solutions technically and economically, which are determined by this planning algorithm among the candidate investments along the planning horizon (e.g., 10 year). It is aimed to assess rationality of the investments through these planning metrics. DIgSILENT PowerFactory (PF) software is utilized in technical analysis to assess impacts of candidate grid investments on technical constraints. The algorithms and planning metrics developed in the study are tested satisfactorily on pilot regions of Akdeniz Electric Distribution Company in Turkey.