Demand Response and Dynamic Line Ratings for Optimum Power Network Reliability and Ageing

被引:33
|
作者
Khoo, Wei Chieh [1 ]
Teh, Jiashen [1 ]
Lai, Ching-Ming [2 ]
机构
[1] Univ Sains Malaysia USM, Sch Elect & Elect Engn, Nibong Tebal 14300, Malaysia
[2] Natl Chung Hsing Univ NCHU, Dept Elect Engn, Taichung 402, Taiwan
来源
IEEE ACCESS | 2020年 / 8卷
关键词
Aging; Reliability; Conductors; Optimization; Load modeling; Load management; Temperature distribution; Demand response; dynamic line rating; resilience; reliability; optimisation; ageing; overhead lines; flexibility; Monte Carlo; SYSTEM; REPLACEMENT; UNCERTAINTY; MODELS; CABLE;
D O I
10.1109/ACCESS.2020.3026049
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This study proposes a methodology to optimise the use of average demand loss of each load bus to enhance line ratings and modify load curves, by minimising demand loss and network ageing due to elevated conductor temperatures. The considered lines are connected to load buses, operated with dynamic line rating technology and have actual conductor physical properties. The simulation of line failures considers line loadings, whose values are based on utilizations of the average demand loss of load buses where the lines are connected, and the remaining service life of the conductor. Demand response in the form of peak-shaving and valley-filling is used to modify load demand curves, with the allowable peak load reduced based on utilizations of the remaining average demand loss. The average demand loss values are determined in the preliminary screening module of the proposed method. Various trade-offs between ageing and reliability of the network are solved based on the two-objective non-sorting genetic algorithm and fuzzy decision-making method in the execution module of the proposed method. Results have shown that the proposed method is cost-effective in that it strategically increase line ageing slightly to enhance system reliability, by as much as 71.9%, based on the equal emphasis of network ageing and reliability, when compared with the scenario that only prioritizes the protection of network ageing. Line ageing is also 68.2% lower on average across the entire spectrum of rating exceedance (1% to 25%) compared to the scenario that only prioritizes enhancement of network reliability.
引用
收藏
页码:175319 / 175328
页数:10
相关论文
共 50 条
  • [21] Contribution of emergency demand response programs in power system reliability
    Aghaei, Jamshid
    Alizadeh, Mohammad-Iman
    Siano, Pierluigi
    Heidari, Alireza
    ENERGY, 2016, 103 : 688 - 696
  • [22] A dynamic model for multi-objective feeder reconfiguration in distribution network considering demand response program
    Lotfi, Hossein
    Shojaei, Ali Asghar
    ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS, 2023, 14 (04): : 1051 - 1080
  • [23] The Effect of Time-Based Demand Response Program on LDC and Reliability of Power System
    Samadi, Mahdi
    Javidi, Mohammad Hossein
    Ghazizadeh, Mohammad Sadegh
    2013 21ST IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE), 2013,
  • [24] Reliability Impact of Dynamic Thermal Rating System in Wind Power Integrated Network
    Teh, Jiashen
    Cotton, Ian
    IEEE TRANSACTIONS ON RELIABILITY, 2016, 65 (02) : 1081 - 1089
  • [25] Reliability evaluation incorporating Demand Response and Time varying thermal Ratings of OHLs
    Abogaleela, Mohamed
    Kopsidas, Konstantinos
    2018 TWENTIETH INTERNATIONAL MIDDLE EAST POWER SYSTEMS CONFERENCE (MEPCON), 2018, : 1069 - 1074
  • [26] Emergency demand response program modeling on power system reliability evaluation
    Aazami R.
    Daniar S.
    Talaeizadeh V.
    International Journal of Electrical Engineering, 2016, 23 (04): : 151 - 158
  • [27] Historical Data Analysis for Extending Dynamic Line Ratings Across Power Transmission Systems
    Viafora, Nicola
    Moller, Jakob G.
    Olsen, Rasmus A.
    Kristensen, Anders S.
    Holboll, Joachim
    2018 IEEE INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS), 2018,
  • [28] Double Q Planning Method for Substation Considering Power Demand of 5G Network and Reliability
    Ma X.
    Feng X.
    Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, 2023, 38 (11): : 2962 - 2976
  • [29] Power quality and reliability enhancement in distribution systems via optimum network reconfiguration by using quantum firefly algorithm
    Shareef, H.
    Ibrahim, A. A.
    Salman, N.
    Mohamed, A.
    Ai, W. Ling
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 58 : 160 - 169
  • [30] Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids
    Garcia, Edwin
    Aguila, Alexander
    Ortiz, Leony
    Ruiz, Milton
    ENERGIES, 2024, 17 (05)