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Interfacing applications for uncertainty reduction in smart energy systems utilizing distributed intelligence

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  • Nguyen, Phuong H.
  • Blaauwbroek, Niels
  • Nguyen, Cuong
  • Zhang, Xu
  • Flueck, Alexander
  • Wang, Xiaoyu

Abstract

Under the transition towards sustainable smart energy systems (SES), utilization of distributed intelligence has been gradually proposed along with the expansion of Information and Communication Technology (ICT) infrastructure and advanced control services. Distributed intelligence (DI)-based control and management solutions proved a perfect complement to the existing control structures to handle the SES’ uncertainty which is getting quite complex with different system layers and involved stakeholders. Advanced modelling and simulation techniques are crucial here to realize and enable the applications of DI to enhance grid reliability while optimize market operation. However, several challenges arise while modelling DI applications and integrating them in the simulation platform due to the complexity of the multi-disciplinary smart grids. As an activity of IEEE Task Force on Interfacing Techniques for Simulation Tools, this paper mainly reviews the interface issues between modelling and simulation of physical, ICT, and application layers, as well as business processes of the whole smart energy systems. By means of a conceptual framework for SES development, this paper aims to position most of DI-based control applications in specific research domain and elaborate on their interface with the whole SES context.

Suggested Citation

  • Nguyen, Phuong H. & Blaauwbroek, Niels & Nguyen, Cuong & Zhang, Xu & Flueck, Alexander & Wang, Xiaoyu, 2017. "Interfacing applications for uncertainty reduction in smart energy systems utilizing distributed intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1312-1320.
    • Handle: RePEc:eee:rensus:v:80:y:2017:i:c:p:1312-1320
    DOI: 10.1016/j.rser.2017.05.180
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    References listed on IDEAS

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    Cited by:

    1. Niels Blaauwbroek & Phuong Nguyen & Han Slootweg, 2018. "Data-Driven Risk Analysis for Probabilistic Three-Phase Grid-Supportive Demand Side Management," Energies, MDPI, vol. 11(10), pages 1-18, September.

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