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Assessment of Aggregators’ Operation and Value Sharing in Flexibility Market

Younesi, Ehsan | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57817 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Abbaspour Tehranifard, Ali; Fotuhi Firuzabad, Mahmud
  7. Abstract:
  8. Sharing the values resulting from the purchase and sale of energy in large coalitions in smart grid systems is accompanied by computational complexity and high calculation time. In order to reduce this time, this research presents novel clustering approaches to simplify the process of value sharing among players. These approaches have been employed in two methods: Shapley values and worst-case minimization (Nucleolus). In this method, players are clustered based on their roles and assets, and the K-means algorithm is also used for the second clustering method. By doing so, the constraints and the number of possible coalitions are reduced, and consequently, the calculation time in both methods is significantly decreased. Moreover, the impact of flexible loads on the manner of profit sharing in aggregators in the day-ahead and intraday markets has also been examined. An 18-member community was investigated as a case study, and the results clearly demonstrate a reduction in computation time for both methods. Furthermore, we have examined how flexible loads affect the two profit-sharing methods, whose correctness and performance have been confirmed
  9. Keywords:
  10. Cooperative Game Theory ; Clustering ; Value Sharing ; Coalition Reduction ; Worst-Case Minimization Method ; Shapley Method

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