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  • Open Access

    ARTICLE

    Two-Stage Scheduling Model for Flexible Resources in Active Distribution Networks Based on Probabilistic Risk Perception

    Yukai Li1,*, Ruixue Zhang1, Yongfeng Ni1, Hongkai Qiu1, Yuning Zhang2, Chunming Liu2

    Energy Engineering, Vol.122, No.2, pp. 681-707, 2025, DOI:10.32604/ee.2024.058981 - 31 January 2025

    Abstract Aiming at the problems of increasing uncertainty of low-carbon generation energy in active distribution network (ADN) and the difficulty of security assessment of distribution network, this paper proposes a two-phase scheduling model for flexible resources in ADN based on probabilistic risk perception. First, a full-cycle probabilistic trend sequence is constructed based on the source-load historical data, and in the day-ahead scheduling phase, the response interval of the flexibility resources on the load and storage side is optimized based on the probabilistic trend, with the probability of the security boundary as the security constraint, and with… More >

  • Open Access

    ARTICLE

    A Spark Scheduling Strategy for Heterogeneous Cluster

    Xuewen Zhang1, Zhonghao Li1, Gongshen Liu1,*, Jiajun Xu1, Tiankai Xie2, Jan Pan Nees1

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 405-417, 2018, DOI:10.3970/cmc.2018.02527

    Abstract As a main distributed computing system, Spark has been used to solve problems with more and more complex tasks. However, the native scheduling strategy of Spark assumes it works on a homogenized cluster, which is not so effective when it comes to heterogeneous cluster. The aim of this study is looking for a more effective strategy to schedule tasks and adding it to the source code of Spark. After investigating Spark scheduling principles and mechanisms, we developed a stratifying algorithm and a node scheduling algorithm is proposed in this paper to optimize the native scheduling More >

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