Dynamic Pricing for Improving Bi-Directional Interactions with Reduced Power Imbalance

Yongjun Sun*, Pei Huang

*Corresponding author for this work

    Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 12 - Chapter in an edited book (Author)peer-review

    1 Citation (Scopus)

    Abstract

    Active supply–demand interactions in a smart grid are essential for reducing grid power imbalance which is important for the security and efficiency of power supply. A key element to the success of such interactions is the proper pricing strategy. The latest game-theory-based dynamic pricing methods require information exchanges not only between the supply and demand sides, but also among individual buildings, since they make decisions for one building’s demand response based on/influenced by operations of the others. However, in practical applications in which a number of buildings are considered, the latter information exchanges are extremely difficult due to the concerns of privacy, communication complexity and high computation load. Therefore, this chapter proposed a genetic algorithm-based dynamic pricing method for improving bi-directional interactions with reduced power imbalance, which does not require information exchanges among individual buildings. In this chapter, at the demand side, targeting at minimizing daily electricity cost, a non-linear programming-based demand response control is performed in individual buildings at a dynamic price given by the grid operator genetic algorithm optimizer. Targeting at reducing grid power imbalance, the genetic algorithm optimizer is used by the grid operator to search for a better dynamic price based on the aggregated demand response results. Such interaction will continue until the grid power imbalance cannot be further reduced. The impacts of demand elasticity are also investigated on performance improvements. The proposed pricing method can be used in practical applications to improve dynamic pricing of a smart grid for reduced grid power imbalance and thus increased operation efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
    Original languageEnglish
    Title of host publicationFuture Urban Energy System for Buildings
    Subtitle of host publicationThe Pathway Towards Flexibility, Resilience and Optimization
    EditorsXingxing Zhang, Pei Huang, Yongjun Sun
    PublisherSpringer Singapore
    Pages425-444
    Edition1
    ISBN (Electronic)978-981-99-1222-3
    ISBN (Print)978-981-99-1221-6, 978-981-99-1224-7
    DOIs
    Publication statusPublished - 2023

    Publication series

    NameSustainable Development Goals Series
    VolumePart F2770
    ISSN (Print)2523-3084
    ISSN (Electronic)2523-3092

    Research Keywords

    • Bi-Directional interactions
    • Demand response
    • Dynamic pricing
    • Power imbalance
    • Smart grid

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