A Cost-Effective Disturbance Governance Framework for Low-Inertia Autonomous Microgrids

Payam Ghaebi Panah, Rahmat Allah Hooshmand*, Mehdi Gholipour, Carlos A. Macana, Josep M. Guerrero, Juan C. Vasquez

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

2 Citations (Scopus)

Abstract

Islanded microgrids with high shares of RES are more exposed to frequency disturbances. The largest generator is typically in charge of frequency regulation. This study tries to upgrade this monopoly to a competitive market. A novel framework is proposed to invite prosumers of any kind/size to participate in a local ancillary service market. A multi-criteria decision-maker is developed to select the proper service from the pool of bids. Flexibility Flags and Prosumer Deviation Index are introduced to quantify the behaviors of individuals and the stability of autonomous microgrids. Furthermore, an innovative reward/punishment framework is suggested for the billing of subscribers. In this method, the extra cost of the activated reserved power is solely compensated by disturbance makers rather than the conventional way of blindly charging all subscribers for frequency regulation. An urban microgrid including electric vehicles, micro combined heat/power generator, thermostatic loads, and kinetic energy storage is considered for the performance assessment. The results indicate that electric vehicles and flexible loads are privileged. Also, the bill of the planned loads for the regulation service falls from 46–48% down to 3–6% under the proposed framework while the cost of frequency regulation drops by 59% when the unnecessary reserved power is modified.
Original languageEnglish
Article number101640
JournalSustainable Energy Technologies and Assessments
Volume48
ISSN2213-1388
DOIs
Publication statusPublished - Dec 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Ltd

Keywords

  • Demand-side management
  • Flexibility services
  • Multi-criteria decision making
  • Thermal demand response
  • Vehicle to grid

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