Optimal Clean Energy Resource Allocation in Balanced and Unbalanced Operation of Sustainable Electrical Energy Distribution Networks

被引:0
|
作者
Kumar, Abhinav [1 ]
Kumar, Sanjay [1 ]
Sinha, Umesh Kumar [1 ]
Bohre, Aashish Kumar [2 ]
Saha, Akshay Kumar [3 ]
机构
[1] Natl Inst Technol Jamshedpur, Dept Elect, Jamshedpur 831014, India
[2] Natl Inst Technol, Dept Elect Egg, Durgapur 713209, India
[3] Univ KwaZulu Natal, Discipline Elect Elect & Comp Engn, ZA-4041 Durban, South Africa
关键词
distributed clean energy resources; active power loss index; reactive power loss index; voltage index; balanced and unbalanced distribution systems; soft computing techniques; LOAD FLOW SOLUTION; LEARNING-BASED OPTIMIZATION; DISTRIBUTION-SYSTEMS; VOLTAGE REGULATION; OPTIMAL PLACEMENT; GENERATION; DG; RECONFIGURATION; ALGORITHM; COUNTRIES;
D O I
10.3390/en17184572
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Electric power is crucial for economic growth and the overall development of any country. The efficient planning of distribution system is necessary because all the consumers mainly rely on the distribution network to access the power. This paper focuses on addressing distribution system challenges and meeting consumers' fundamental needs, such as achieving an improved voltage profile and minimizing costs within an environmentally sustainable framework. This work addressed the gap in the existing research by analysing the performance of both balanced and unbalanced systems within the same framework, specifically using the IEEE 33-bus and IEEE 118-bus test systems. Unlike prior studies that focused solely on either balanced or unbalanced systems, this work redistributed balanced loads into three-phase unequal unbalanced loads to create a more challenging unbalanced distribution network. The primary objective is to compare the effects of balanced and unbalanced loads on system the performances and to identify strategies for mitigating unbalanced load issues in each phase. Six optimization methods (PSO, TLBO, JAYA, SCA, RAO, and HBO) were employed to minimize losses, voltage variations, and other multi-objective function factors. Additionally, the study compared the cost of energy loss (CEL), emission factors, costs associated with distributed clean energy resources (DCER), and active and reactive power losses. Phase angle distortions due to unbalanced loads were also analysed. The results showed that among the optimization techniques tested (PSO, TLBO, JAYA, SCA, RAO, and HBO), the HBO method proved to be the most effective for the optimal allocation of distributed clean energy resources, yielding the lowest PFMO values and favourable outcomes across the technical, economic, and environmental parameters.
引用
收藏
页数:52
相关论文
共 50 条
  • [41] Optimal allocation of energy storage systems for voltage control in LV distribution networks
    Giannitrapani, Antonio
    Paoletti, Simone
    Vicino, Antonio
    Zarrilli, Donato
    2017 IEEE MANCHESTER POWERTECH, 2017,
  • [42] Optimal Energy Efficient Resource Allocation for Wireless Powered Hybrid Multiple Access Networks
    Zhang G.-C.
    Zeng Z.-C.
    Cui M.
    Wu Q.-Q.
    Lin F.
    Liu Y.-J.
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2020, 48 (04): : 697 - 705
  • [43] Optimal Placement and Capacity Allocation of Distributed Energy Storage Devices in Distribution Networks
    Li, Wei
    Lu, Chao
    Pan, Xin
    Song, Jie
    2017 13TH IEEE CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), 2017, : 1403 - 1407
  • [44] Energy Efficient Resource Allocation in Wireless Energy Harvesting Sensor Networks
    Azarhava, Hosein
    Niya, Javad Musevi
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2020, 9 (07) : 1000 - 1003
  • [45] Energy-Aware Optimal Resource Allocation in MR-MC Wireless Networks
    Liu, Lu
    Cao, Xianghui
    Cheng, Yu
    2013 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2013, : 4865 - 4870
  • [46] Optimal Allocation of Energy Storage Systems for Voltage Control in LV Distribution Networks
    Giannitrapani, Antonio
    Paoletti, Simone
    Vicino, Antonio
    Zarrilli, Donato
    IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (06) : 2859 - 2870
  • [47] Optimal resource allocation method for energy harvesting based underlay Cognitive Radio networks
    Liao, Jianbin
    Yu, Hongliang
    Jiang, Weibin
    Lin, Ruiquan
    Wang, Jun
    PLOS ONE, 2023, 18 (01):
  • [48] Smart Operation of Unbalanced Distribution Systems with PVs and Energy Storage
    Sharma, Isha
    Bozchalui, Mohammad Chehreghani
    Sharma, Ratnesh
    2013 IEEE INTERNATIONAL CONFERENCE ON SMART ENERGY GRID ENGINEERING (SEGE), 2013,
  • [49] Optimal Renewable Energy Resource Based Distributed Generation Allocation in a Radial Distribution System
    Sambaiah, Kola Sampangi
    Jayabarathi, T.
    SOFT COMPUTING FOR PROBLEM SOLVING, SOCPROS 2018, VOL 1, 2020, 1048 : 295 - 310
  • [50] Optimal allocation of energy storage system and its benefit analysis for unbalanced distribution network with wind generation
    Nayak, Manas Ranjan
    Behura, Diptimayee
    Kasturi, Kumari
    JOURNAL OF COMPUTATIONAL SCIENCE, 2021, 51