An interactive multi-criteria decision-making framework between a renewable power plant planner and the independent system operator


Soltaniyan S., Salehizadeh M. R., TAŞCIKARAOĞLU A., ERDİNÇ O., Catalao J. P. S.

SUSTAINABLE ENERGY GRIDS & NETWORKS, cilt.26, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 26
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.segan.2021.100447
  • Dergi Adı: SUSTAINABLE ENERGY GRIDS & NETWORKS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Providing efficient support mechanisms for renewable energy promotion has drawn much attention from researchers in the recent years. The connection of a new renewable power plant to the transmission system has impacts on different electricity market indices since the other strategic generation units change their behaviour in the new multi-agent environment. In this paper, as the main contribution to the previous literature, a combination of multi-criteria decision-making approach and multi-agent modelling technique is developed to obtain the maximum possible profits for an intended renewable generation plan and also direct the investment to be located in a way to improve electricity market indices besides supporting renewable energy promotion. Fuzzy Q-learning electricity market modelling approach in combination with the technique for order preference by similarity (TOPSIS) is used as a new decision support system for promotion of renewable energy for the first time in the literature. The proposed interactive multi-criteria decision-making framework between the independent system operator (ISO) and the renewable power plant planner provides a win win situation that improve market indices while help the renewable power plant planning. The effectiveness of the proposed method is examined on the IEEE 30-bus test system and the results are discussed. (c) 2021 Elsevier Ltd. All rights reserved.