Minimization of Power Losses through Optimal Battery Placement in a Distributed Network with High Penetration of Photovoltaics

被引:45
作者
Alzahrani, Ahmed [1 ]
Alharthi, Hussain [1 ]
Khalid, Muhammad [1 ,2 ]
机构
[1] King Fahd Univ Petr & Minerals, Elect Engn Dept, Dhahran 31261, Saudi Arabia
[2] KA CARE Energy Res & Innovat Ctr, Dhahran 31261, Saudi Arabia
关键词
battery energy storage system; distribution network; renewable energy sources; ENERGY-STORAGE SYSTEMS; OPTIMAL ESS ALLOCATION; OPERATION;
D O I
10.3390/en13010140
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
The problems associated with the deployment of intermittent, unpredictable and uncontrollable solar photovoltaics (PV) can be feasibly solved with battery energy storage systems (BESS), particularly in terms of optimizing the available capacity, increasing reliability and reducing system losses. Consequently, the degree of importance of BESS increases in proportion to the level of PV penetration. Nevertheless, the respective high cost of BESS imposes a huge concern and the need to establish a techno-economic solution. In this paper, we investigate the system losses and power quality issues associated with the high deployment of PV in a grid network and hence formulate BESS capacity optimization and placement methodology based on a genetic algorithm. The concept of the proposed methodology has been tested and validated on a standard IEEE 33 bus system. A brief stepwise analysis is presented to demonstrate the effectiveness and robustness of the proposed methodology in reducing the incremental system losses experienced with increased PV penetration. Furthermore, based on the proposed optimization objectives, a comparative study has also been performed to quantify the impact and effectiveness of aggregated and distributed placement of BESS. The results obtained exhibit a substantial reduction in system losses, particularly in the case of distributed BESS placement.
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页数:16
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共 40 条
  • [21] Optimal Planning of Multiple Distributed Generating Units and Storage in Active Distribution Networks
    Khalid, Muhammad
    Akram, Umer
    Shafiq, Saifullah
    [J]. IEEE ACCESS, 2018, 6 : 55234 - 55244
  • [22] Operation and sizing of energy storage for wind power plants in a market system
    Korpaas, M
    Holen, AT
    Hildrum, R
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2003, 25 (08) : 599 - 606
  • [23] Electrical Energy Forecasting and Optimal Allocation of ESS in a Hybrid Wind-Diesel Power System
    Lan, Hai
    Yin, He
    Wen, Shuli
    Hong, Ying-Yi
    Yu, David C.
    Zhang, Lijun
    [J]. APPLIED SCIENCES-BASEL, 2017, 7 (02):
  • [24] Optimal allocation of a hybrid energy storage system considering its dynamic operation characteristics for wind power applications in active distribution networks
    Lei, Jiazhi
    Gong, Qingwu
    [J]. INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2018, 42 (13) : 4184 - 4196
  • [25] Optimal siting and sizing of renewable energy sources, storage devices, and reactive support devices to obtain a sustainable electrical distribution systems
    Melgar Dominguez O.D.
    Pourakbari Kasmaei M.
    Lavorato M.
    Mantovani J.R.S.
    [J]. Energy Systems, 2018, 9 (03) : 529 - 550
  • [26] MI ZQ, 2018, ENERGIES, V11, DOI DOI 10.3390/en11051242
  • [27] A Supervisory Load-Leveling Approach to Improve the Voltage Profile in Distribution Network
    Mokhtari, Ghassem
    Nourbakhsh, Ghavameddin
    Ledwich, Gerard
    Ghosh, Arindam
    [J]. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2015, 6 (01) : 245 - 252
  • [28] Load leveling reduces T&D line losses
    Nourai, Ali
    Kogan, V. I.
    Schafer, Chris M.
    [J]. IEEE TRANSACTIONS ON POWER DELIVERY, 2008, 23 (04) : 2168 - 2173
  • [29] Unit Commitment With Ideal and Generic Energy Storage Units
    Pozo, David
    Contreras, Javier
    Sauma, Enzo E.
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2014, 29 (06) : 2974 - 2984
  • [30] Optimal planning and operation of energy storage systems in radial networks for wind power integration with reserve support
    Qin, Mingwen
    Chan, Kevin Wing
    Chung, Chi Yung
    Luo, Xiao
    Wu, Ting
    [J]. IET GENERATION TRANSMISSION & DISTRIBUTION, 2016, 10 (08) : 2019 - 2025