Network Reconfiguration Framework for CO2 Emission Reduction and Line Loss Minimization in Distribution Networks Using Swarm Optimization Algorithms

被引:1
作者
Lin, Wei-Chen [1 ]
Hsiao, Chao-Hsien [1 ]
Huang, Wei-Tzer [1 ]
Yao, Kai-Chao [1 ]
Lee, Yih-Der [2 ]
Jian, Jheng-Lun [2 ]
Hsieh, Yuan [1 ]
机构
[1] Natl Changhua Univ Educ, Dept Ind Educ & Technol, Bao Shan Campus,2 Shi Da Rd, Changhua 500, Taiwan
[2] Natl Atom Res Inst, Taoyuan 325, Taiwan
关键词
CO2; emissions; line loss; active distribution network; network reconfiguration; swarm optimization algorithms; OpenDSS; DISTRIBUTION-SYSTEM; RESTORATION; ENHANCEMENT;
D O I
10.3390/su16041493
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper presents the development of a generic active distribution network (ADN) operation simulation framework that incorporates selected swarm optimization algorithms (SOAs) for the purpose of reducing CO2 emissions and line loss minimization through network reconfiguration (NR). The framework has been implemented in the ADN of Taipower. Network data, provided by the Distribution Mapping Management System and Distribution Dispatch Control Center (DDCC) of Taipower, were converted into an OpenDSS script to create ADN models. The SOA is integrated into the framework and utilized to determine the statuses of both four-way and two-way switches in the planning and operating stages, in accordance with the proposed multi-objective function and operational constraints. The weightings for these decisions can be customized by distribution operators to meet their specific requirements. In this paper, the weighting for line loss reduction is set to one for minimizing CO2 emissions. The numerical results demonstrate that the proposed ADN framework can recommend a feeder switching scheme to distribution operators, aiming to balance feeder loading and minimize the neutral line current. Finally, this approach leads to reduced line losses and minimizes CO2 emissions. In contrast to relying solely on historical operational experience, this generic ADN reconfiguration framework offers a systematic approach that can significantly contribute to reducing CO2 emissions and enhancing the operational efficiency of ADNs.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] Internet-of-Vehicles Network for CO2 Emission Estimation and Reinforcement Learning-Based Emission Reduction
    Devi, Archana Sulekha
    Britto, Milagres Mary John
    Fang, Zian
    Gopan, Renjith
    Jassal, Pawan Singh
    Qazzaz, Mohammed M. H.
    Rajbhandari, Sujan
    Al-Sallami, Farah Mahdi
    IEEE ACCESS, 2024, 12 : 110681 - 110690
  • [33] Electrical Distribution System Power Loss Reduction and Voltage Profile Enhancement by Network Reconfiguration Using PSO
    Shetty, Vinay J.
    Ankaliki, S. G.
    2019 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENERGY SYSTEMS (ICEES 2019), 2019,
  • [34] CO2 emission reduction in the steel industry by using emission trading programs
    Wang, Chuan
    Larsson, Mikael
    Yan, Jinyue
    Dahl, Jan
    INTERNATIONAL JOURNAL OF GREEN ENERGY, 2007, 4 (05) : 505 - 518
  • [35] Loss-minimized Distribution System Reconfiguration by Using Improved Multi-agent Based Particle Swarm Optimization
    Yang, Hong-Tzer
    Tzeng, Yi-Te
    Tsai, Men-Shen
    2010 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2010,
  • [36] On-line network reconfiguration for enhancement of voltage stability in distribution systems using artificial neural networks
    Kashem, MA
    Ganapathy, V
    Jasmon, GB
    ELECTRIC POWER COMPONENTS AND SYSTEMS, 2001, 29 (04) : 361 - 373
  • [37] Optimization of radial unbalanced distribution networks in the presence of distribution generation units by network reconfiguration using harmony search algorithm
    Roosta, Alireza
    Eskandari, Hamid-Reza
    Khooban, Mohammad-Hassan
    NEURAL COMPUTING & APPLICATIONS, 2019, 31 (11) : 7095 - 7109
  • [38] Optimization of radial unbalanced distribution networks in the presence of distribution generation units by network reconfiguration using harmony search algorithm
    Alireza Roosta
    Hamid-Reza Eskandari
    Mohammad-Hassan Khooban
    Neural Computing and Applications, 2019, 31 : 7095 - 7109
  • [39] Energy Loss Reduction and Load Balancing through Network Reconfiguration in Practical LV Distribution Feeder using GAMS
    Muruganantham, B.
    Selvam, M. Muthamizh
    Gnanadass, R.
    Padhy, N. P.
    2017 7TH INTERNATIONAL CONFERENCE ON POWER SYSTEMS (ICPS), 2017, : 509 - 513
  • [40] Optimal Allocation of Tie Switch in Distribution Systems for Energy Loss Reduction Using Particle Swarm Optimization
    Karaaom, Chatuphat
    Jirapong, Peerapol
    Thararak, Panida
    Tantrapon, Keerachat
    2020 8TH INTERNATIONAL ELECTRICAL ENGINEERING CONGRESS (IEECON), 2020,