Optimization of Near-Zero Energy Buildings Cluster with Top-Down Control

Pei Huang*, Yongjun Sun

*Corresponding author for this work

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

    Abstract

    Nearly zero energy buildings (NZEBs) are considered as a promising solution to the mitigation of the energy problems. A proper control of the energy system operation of the nZEB cluster is essential for improving load matching, reducing grid interaction and reducing energy bills. Existing studies have developed many demand response control methods to adjust the operation of energy systems to improve performances. Most of these studies focus on optimizing performances at individual-nZEB-level while neglecting collaborations (e.g., energy sharing and battery sharing) between nZEBs. Only a few studies consider the collaborations and optimize the system operation at nZEB-cluster-level, yet they cannot take full advantage of nZEB collaborations as optimization is conducted in a bottom-up manner lacking global coordination. This chapter, therefore, proposes a top-down control method of nZEBs for optimizing performances at the cluster level. The top-down control method first considers the nZEB cluster as ‘one’ and optimizes its energy system operation using the genetic algorithm (GA), and then it coordinates the operation of every single nZEB inside the cluster using non-linear programming (NLP). The top-down control enables collaborations among nZEBs by coordinating single nZEB’s operations. Such collaborations can bring significant performance improvements in different aspects. For instance, in aspect of economic cost, the collaborations can reduce the high-priced energy imports from the grid by sharing the surplus renewable energy with nZEBs which have insufficient energy generations. The proposed top-down control has been compared with a traditional non-collaborative control. The study results show that the top-down control is effective in improving performances at cluster level. © 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
    Place of PublicationSingapore
    PublisherSpringer 
    Pages465-486
    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

    • Economic cost
    • Grid interaction
    • Load matching
    • Near-Zero energy building cluster
    • Top-Down control

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