Capturing Chronology and Extreme Values of Representative Days for Planning of Transmission Lines and Long-Term Energy Storage Systems

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The growing penetration of renewable energy sources (RESs) is inevitable to reach net zero emissions. In this regard, optimal planning and operation of power systems are becoming more critical due to the need for modeling the short-term variability of RES output power and load demand. Considering hourly time steps of one or more years to model the operational details in a long-term expansion planning scheme can lead to a practically unsolvable model. Therefore, a clustering-based hybrid time series aggregation algorithm is proposed in this paper to capture both extreme values and temporal dynamics of input data by some extracted representatives. The proposed method is examined in a complex co-planning model for transmission lines, wind power plants (WPPs), short-term battery and long-term pumped hydroelectric energy storage systems. The effectiveness of proposed mixed-integer linear programming (MILP) model is evaluated using a modified 6-bus Garver test system. The simulation results confirm the proposed model efficacy, especially in modeling long-term energy storage systems.
Original languageEnglish
Title of host publicationProceedings of the 2023 IEEE Belgrade PowerTech
Place of PublicationPiscataway
Number of pages6
ISBN (Electronic)978-1-6654-8778-8
ISBN (Print)978-1-6654-8779-5
Publication statusPublished - 2023
Event2023 IEEE Belgrade PowerTech - Belgrade, Serbia
Duration: 25 Jun 202329 Jun 2023

Publication series

Name2023 IEEE Belgrade PowerTech, PowerTech 2023


Conference2023 IEEE Belgrade PowerTech

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Energy Storage System
  • Representative Time Period
  • Transmission Expansion Planning
  • Time Series Aggregation
  • Wind Power Plant


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