Dynamic clustering for imbalance management through local supply and demand balancing

A.N.M.M. Haque, Tafique Hilal Tawab, H.P. Nguyen

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

The electrical power system has been facing a fundamental shift of paradigm with the integration of renewable energy sources (RES) and price responsive loads. These changes introduce higher uncertainties and pose implications for both network and market actors. While the network operators face frequent operational challenges in terms of voltage limit violations and network congestions, the market parties need deal with a higher risk of imbalance. In this paper, a dynamic clustering method has been proposed to procure flexibility from the smallscale residential prosumers in order to minimize the imbalance cost. An agent-based coordination mechanism has been adopted to implement a demand response program based on local supply and demand balancing. A bottom-up simulation analysis was performed incorporating 600 residential prosumers. Simulation results indicate that a dynamic and adaptive clustering scheme can efficiently minimize the imabalance cost resulting from wind power forecast errors while maintaining the comfort constraints of the prosumers.
Original languageEnglish
Title of host publication2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)
EditorsQuan Hao, Anurag Sharma
PublisherIEEE Computer Society
Pages459-464
Number of pages6
ISBN (Electronic)978-1-5386-4291-7
DOIs
Publication statusPublished - 18 Sep 2018
Event2018 International Conference on Innovative Smart Grid Technologies, ISGT Asia 2018 - Singapore, Singapore
Duration: 22 May 201825 May 2018
http://sites.ieee.org/isgt-asia-2018/

Conference

Conference2018 International Conference on Innovative Smart Grid Technologies, ISGT Asia 2018
Abbreviated titleISGTAsia2018
CountrySingapore
CitySingapore
Period22/05/1825/05/18
Internet address

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Keywords

  • Microgrids
  • supply and demand
  • Clustering algorithms
  • power markets
  • flexibility
  • imbalance market
  • dynamic clustering
  • Demand response

Cite this

Haque, A. N. M. M., Hilal Tawab, T., & Nguyen, H. P. (2018). Dynamic clustering for imbalance management through local supply and demand balancing. In Q. Hao, & A. Sharma (Eds.), 2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia) (pp. 459-464). IEEE Computer Society. https://doi.org/10.1109/ISGT-Asia.2018.8467952