A priority decision making-based bidding strategy for interactive aggregators

Tianguang Lu, Wei Jen Lee, Qian Ai, Songtao Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This paper proposes an interactive bidding strategy for smart distribution networks with clustered aggregators to effectively coordinate the energy and profit of each entity. In the proposed bi-level bidding model, there are two levels, where the upper level stands for the distribution operator (DO) to secure the operation quality and bid with energy aggregators (EAs), and the lower level represents each EA to bid for interactive energies with the DO and other EAs. An innovative interactive bidding mechanism is developed to take advantages of renewable generation and energy storage system (ESS). The priority-based decision making is applied to the lower level to elaborately map the bidding mechanism and lead each EA's market interaction. The proposed model is solved by a customized hierarchical genetic algorithm (HGA). Case studies on a practical distribution grid in China and the IEEE 33-bus test feeder demonstrate the effectiveness of the proposed methodology.

Original languageEnglish (US)
Title of host publication2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781509048946
DOIs
StatePublished - Nov 8 2017
Event2017 IEEE Industry Applications Society Annual Meeting, IAS 2017 - Cincinnati, United States
Duration: Oct 1 2017Oct 5 2017

Publication series

Name2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
Volume2017-January

Other

Other2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
CountryUnited States
CityCincinnati
Period10/1/1710/5/17

Keywords

  • Aggregators
  • Decision making
  • Hierarchical genetic algorithm
  • Power market
  • Renewable integration

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