Functional Architecture and Collaborative Configuration of Virtual Distribution Feeder for Seasonal Short-term Peak Load

被引:0
|
作者
Zhou, Niancheng [1 ]
Wang, Peng [1 ]
Chi, Yuan [1 ]
Guo, Yingfei [1 ]
Wang, Qianggang [1 ]
Luo, Yongjie [1 ]
机构
[1] State Key Laboratory of Power Transmission Equipment & System Security and New Technology (Chongqing University), Chongqing,400044, China
关键词
Energy storage;
D O I
10.7500/AEPS20230703005
中图分类号
学科分类号
摘要
The traditional line capacity expansion method suffers from the low overall utilization rate of lines and poor power support ability during a contingency when facing seasonal short-term peak loads. Therefore, with the function virtualization as the core concept, this paper studies the functional architecture of virtual distribution feeders that integrate traditional distribution feeders with energy storage components. By using paired energy storage components to construct a virtual power transmission channel, the virtual distribution feeders address seasonal short-term peak loads, delay the conventional line capacity expansion project, and provide emergency power support and auxiliary service functions during non-peak periods to improve the overall utilization rate of energy storage components. In order to further fulfill the flexible transmission and emergency power support potential of virtual distribution feeders, an optimal configuration model for line capacity expansion in distribution network is proposed to optimize the energy storage configuration for virtual distribution feeders while ensuring economy feasibility and meeting peak load demand. Case studies show that the virtual distribution feeders can effectively delay the traditional capacity expansion projects and cope with the seasonal short-term peak loads. For areas with relatively stable load growth, or long lines and short designed delay years for capacity expansion, the advantages of virtual distribution feeders are more noticeable. © 2024 Automation of Electric Power Systems Press. All rights reserved.
引用
收藏
页码:79 / 90
相关论文
共 50 条
  • [31] Piecewise Short-term Load Forecasting Based on Adaptive Seasonal Load Category and Important Point Segment
    Peng X.
    Pan K.
    Zhang D.
    Liu Y.
    Lin Z.
    Dianwang Jishu/Power System Technology, 2020, 44 (02): : 603 - 613
  • [32] Short-term hourly load forecasting using time-series modeling with peak load estimation capability
    Amjady, N
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2001, 16 (03) : 498 - 505
  • [33] Short-term hourly load forecasting using time-series modeling with peak load estimation capability
    Amjady, N
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2001, 16 (04) : 798 - 805
  • [34] IDENTIFICATION OF SEASONAL SHORT-TERM LOAD FORECASTING MODELS USING STATISTICAL DECISION FUNCTIONS
    HUBELE, NF
    CHENG, CS
    IEEE TRANSACTIONS ON POWER SYSTEMS, 1990, 5 (01) : 40 - 45
  • [35] SHORT-TERM PEAK LOAD FORECASTING USING PSO-ANN METHODS: THE CASE OF INDONESIA
    Abdullah, Ade Gafar
    Sopian, Willy Wigia
    Arasid, Wildan
    Nandiyanto, Asep Bayu Dani
    Danuwijaya, Ari Arifin
    Abdullah, Cep Ubad
    JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY, 2018, 13 (08) : 2395 - 2404
  • [36] Aggregated short-term load forecasting for heterogeneous buildings using machine learning with peak estimation
    Bellahsen, Amine
    Dagdougui, Hanane
    ENERGY AND BUILDINGS, 2021, 237
  • [37] Locally-Weighted Polynomial Neural Network for Daily Short-Term Peak Load Forecasting
    Yu, Jungwon
    Kim, Sungshin
    INTERNATIONAL JOURNAL OF FUZZY LOGIC AND INTELLIGENT SYSTEMS, 2016, 16 (03) : 163 - 172
  • [38] A functional-link-neural network for short-term electric load forecasting
    Dash, PK
    Liew, AC
    Satpathy, HP
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 1999, 7 (03) : 209 - 221
  • [39] Short-term load forecasting using system-type neural network architecture
    Kim, Byoung H.
    Velas, John P.
    Lee, Kwang Y.
    2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10, 2006, : 2619 - +
  • [40] A Modeling Framework for Deriving the Structural and Functional Architecture of a Short-Term Memory Microcircuit
    Fisher, Dimitry
    Olasagasti, Teas
    Tank, David W.
    Aksay, Emre R. F.
    Goldman, Mark S.
    NEURON, 2013, 79 (05) : 987 - 1000