Review and clustering of optimal energy management problem studies for industrial microgrids

BEKTAŞ Z., Kayakutlu G.

INTERNATIONAL JOURNAL OF ENERGY RESEARCH, cilt.45, sa.1, ss.103-117, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 45 Sayı: 1
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1002/er.5652
  • Dergi Adı: INTERNATIONAL JOURNAL OF ENERGY RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), Communication Abstracts, Compendex, Environment Index, INSPEC, Metadex, Pollution Abstracts, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.103-117
  • Anahtar Kelimeler: clustering, industrial microgrids, optimal energy management, self-organizing maps
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

The optimal energy management problem of microgrids is an agenda item for the energy field. Especially industrial microgrids, whose energy demand is high and uninterruptible, need to be managed by a holistic view of optimization. Technical researches in this field are to be enriched with the literature review that looks through various angles. In the scope of this paper, the research literature is reviewed deeply and analyzed with the aim of presenting the gaps. Articles written in English, in the period of 2010 to 2019 have been revised thoroughly. By eliminating the search results, 105 relevant articles have been determined. Objective(s), criteria for analysis, processes included, power source(s), storage system, other system components and methodology of each article have been studied. The literature has been summarized, it has been seen that solar, wind, and diesel sources are used in about 82%, 55%, and 16% of articles, respectively. Then, they have been clustered using self-organizing maps. Nine clusters have been obtained which separate the articles clearly. Especially, three of them which have fewer data have been analyzed. Clustering results have been interpreted and utilized to show the research openings. Achievements of this study will lead the scientific research that will fill in the gaps.