IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v233-234y2019ip71-85.html
   My bibliography  Save this article

Optimal active and reactive power allocation in distribution networks using a novel heuristic approach

Author

Listed:
  • Bayat, A.
  • Bagheri, A.

Abstract

A wide range of solution methodologies has been presented in the literature for the siting and sizing of active and reactive power sources in radial distribution systems. The solution techniques are mainly classified into mathematical programming algorithms, heuristics, meta-heuristic methods, and the analytical approaches. This paper proposes a novel heuristic method for optimal allocation of distributed generation (DG) and capacitor banks. The conducted approach is easy for implementation and does not suffer from the complicacy of the other methods. Based on some mathematical calculations, two main formulations are derived. Then, the resulting formulations are employed to site and size capacitor bank and DG unit in the 33-bus distribution network to verify its performance by comparing the obtained results with those of global search method. Afterward, the proposed method is used to allocate a specified number of DGs and capacitors in the 33 and 69-bus systems. Finally, the conducted approach is employed to allocate multiple DGs and capacitors, and also multiple DGs with optimal power factor in the 119-bus distribution network. The recently presented methodologies including particle swarm optimization (PSO), improved analytical (IA), hybrid analytical-PSO, Teaching Learning Based Optimization (TLBO), Quasi-Oppositional Teaching Learning based optimization (QOTLBO), Comprehensive Teaching Learning-Based Optimization (CTLBO), and LSF-BFOA algorithms are used for investigating the efficiency of the developed method. The simulation results demonstrate that the presented heuristic approach is robust in finding the optimal results, very fast and easy to implement, applicable to large distribution systems and it give better results than the algorithms presented so far.

Suggested Citation

  • Bayat, A. & Bagheri, A., 2019. "Optimal active and reactive power allocation in distribution networks using a novel heuristic approach," Applied Energy, Elsevier, vol. 233, pages 71-85.
    • Handle: RePEc:eee:appene:v:233-234:y:2019:i::p:71-85
    DOI: 10.1016/j.apenergy.2018.10.030
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918315800
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2018.10.030?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kanwar, Neeraj & Gupta, Nikhil & Niazi, K.R. & Swarnkar, Anil & Bansal, R.C., 2017. "Simultaneous allocation of distributed energy resource using improved particle swarm optimization," Applied Energy, Elsevier, vol. 185(P2), pages 1684-1693.
    2. Aman, M.M. & Jasmon, G.B. & Bakar, A.H.A. & Mokhlis, H. & Karimi, M., 2014. "Optimum shunt capacitor placement in distribution system—A review and comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 429-439.
    3. Sultana, U. & Khairuddin, Azhar B. & Mokhtar, A.S. & Zareen, N. & Sultana, Beenish, 2016. "Grey wolf optimizer based placement and sizing of multiple distributed generation in the distribution system," Energy, Elsevier, vol. 111(C), pages 525-536.
    4. Li, Yang & Feng, Bo & Li, Guoqing & Qi, Junjian & Zhao, Dongbo & Mu, Yunfei, 2018. "Optimal distributed generation planning in active distribution networks considering integration of energy storage," Applied Energy, Elsevier, vol. 210(C), pages 1073-1081.
    5. Quadri, Imran Ahmad & Bhowmick, S. & Joshi, D., 2018. "A comprehensive technique for optimal allocation of distributed energy resources in radial distribution systems," Applied Energy, Elsevier, vol. 211(C), pages 1245-1260.
    6. Zhang, Shenxi & Cheng, Haozhong & Wang, Dan & Zhang, Libo & Li, Furong & Yao, Liangzhong, 2018. "Distributed generation planning in active distribution network considering demand side management and network reconfiguration," Applied Energy, Elsevier, vol. 228(C), pages 1921-1936.
    7. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "An optimal investment planning framework for multiple distributed generation units in industrial distribution systems," Applied Energy, Elsevier, vol. 124(C), pages 62-72.
    8. Pesaran H.A, Mahmoud & Huy, Phung Dang & Ramachandaramurthy, Vigna K., 2017. "A review of the optimal allocation of distributed generation: Objectives, constraints, methods, and algorithms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 293-312.
    9. Sultana, Beenish & Mustafa, M.W. & Sultana, U. & Bhatti, Abdul Rauf, 2016. "Review on reliability improvement and power loss reduction in distribution system via network reconfiguration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 297-310.
    10. Gitizadeh, Mohsen & Vahed, Ali Azizi & Aghaei, Jamshid, 2013. "Multistage distribution system expansion planning considering distributed generation using hybrid evolutionary algorithms," Applied Energy, Elsevier, vol. 101(C), pages 655-666.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Azeredo, Lucas F.S. & Yahyaoui, Imene & Fiorotti, Rodrigo & Fardin, Jussara F. & Garcia-Pereira, Hilel & Rocha, Helder R.O., 2023. "Study of reducing losses, short-circuit currents and harmonics by allocation of distributed generation, capacitor banks and fault current limiters in distribution grids," Applied Energy, Elsevier, vol. 350(C).
    2. Diego José da Silva & Edmarcio Antonio Belati & Eduardo Werley Silva dos Angelos, 2020. "FPAES: A Hybrid Approach for the Optimal Placement and Sizing of Reactive Compensation in Distribution Grids," Energies, MDPI, vol. 13(23), pages 1-18, December.
    3. David Steveen Guzmán-Romero & Brandon Cortés-Caicedo & Oscar Danilo Montoya, 2023. "Development of a MATLAB-GAMS Framework for Solving the Problem Regarding the Optimal Location and Sizing of PV Sources in Distribution Networks," Resources, MDPI, vol. 12(3), pages 1-19, March.
    4. Peng Cheng & Zhiyu Xu & Ruiye Li & Chao Shi, 2022. "A Hybrid Taguchi Particle Swarm Optimization Algorithm for Reactive Power Optimization of Deep-Water Semi-Submersible Platforms with New Energy Sources," Energies, MDPI, vol. 15(13), pages 1-16, June.
    5. Mohamed A. Elseify & Salah Kamel & Hussein Abdel-Mawgoud & Ehab E. Elattar, 2022. "A Novel Approach Based on Honey Badger Algorithm for Optimal Allocation of Multiple DG and Capacitor in Radial Distribution Networks Considering Power Loss Sensitivity," Mathematics, MDPI, vol. 10(12), pages 1-26, June.
    6. Anaya, Karim L. & Pollitt, Michael G., 2020. "Reactive power procurement: A review of current trends," Applied Energy, Elsevier, vol. 270(C).
    7. Tzu-Chia Chen & José Ricardo Nuñez Alvarez & Ngakan Ketut Acwin Dwijendra & Zainab Jawad Kadhim & Reza Alayi & Ravinder Kumar & Seepana PraveenKumar & Vladimir Ivanovich Velkin, 2023. "Modeling and Optimization of Combined Heating, Power, and Gas Production System Based on Renewable Energies," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    8. Ali Selim & Salah Kamel & Amal A. Mohamed & Ehab E. Elattar, 2021. "Optimal Allocation of Multiple Types of Distributed Generations in Radial Distribution Systems Using a Hybrid Technique," Sustainability, MDPI, vol. 13(12), pages 1-31, June.
    9. Chandrasekaran Venkatesan & Raju Kannadasan & Mohammed H. Alsharif & Mun-Kyeom Kim & Jamel Nebhen, 2021. "A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems," Sustainability, MDPI, vol. 13(6), pages 1-34, March.
    10. Thuan Thanh Nguyen & Bach Hoang Dinh & Thai Dinh Pham & Thang Trung Nguyen, 2020. "Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints," Sustainability, MDPI, vol. 12(18), pages 1-30, September.
    11. Jiang, Tao & Dong, Xinru & Zhang, Rufeng & Li, Xue, 2023. "Strategic active and reactive power scheduling of integrated community energy systems in day-ahead distribution electricity market," Applied Energy, Elsevier, vol. 336(C).
    12. Syed Ali Abbas Kazmi & Hafiz Waleed Ahmad & Dong Ryeol Shin, 2019. "A New Improved Voltage Stability Assessment Index-centered Integrated Planning Approach for Multiple Asset Placement in Mesh Distribution Systems," Energies, MDPI, vol. 12(16), pages 1-41, August.
    13. Ayat Ali Saleh & Tomonobu Senjyu & Salem Alkhalaf & Majed A. Alotaibi & Ashraf M. Hemeida, 2020. "Water Cycle Algorithm for Probabilistic Planning of Renewable Energy Resource, Considering Different Load Models," Energies, MDPI, vol. 13(21), pages 1-24, November.
    14. Kumar, Abhishek & Meena, Nand K. & Singh, Arvind R. & Deng, Yan & He, Xiangning & Bansal, R.C. & Kumar, Praveen, 2019. "Strategic integration of battery energy storage systems with the provision of distributed ancillary services in active distribution systems," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    15. Jerzy Andruszkiewicz & Józef Lorenc & Agnieszka Weychan, 2023. "Determination of the Optimal Level of Reactive Power Compensation That Minimizes the Costs of Losses in Distribution Networks," Energies, MDPI, vol. 17(1), pages 1-24, December.
    16. Pesaran H.A., Mahmoud & Nazari-Heris, Morteza & Mohammadi-Ivatloo, Behnam & Seyedi, Heresh, 2020. "A hybrid genetic particle swarm optimization for distributed generation allocation in power distribution networks," Energy, Elsevier, vol. 209(C).
    17. Syed Ali Abbas Kazmi & Usama Ameer Khan & Hafiz Waleed Ahmad & Sajid Ali & Dong Ryeol Shin, 2020. "A Techno-Economic Centric Integrated Decision-Making Planning Approach for Optimal Assets Placement in Meshed Distribution Network Across the Load Growth," Energies, MDPI, vol. 13(6), pages 1-71, March.
    18. Pereira, Luan D.L. & Yahyaoui, Imene & Fiorotti, Rodrigo & de Menezes, Luíza S. & Fardin, Jussara F. & Rocha, Helder R.O. & Tadeo, Fernando, 2022. "Optimal allocation of distributed generation and capacitor banks using probabilistic generation models with correlations," Applied Energy, Elsevier, vol. 307(C).
    19. Xiaosheng Peng & Kai Cheng & Jianxun Lang & Zuowei Zhang & Tao Cai & Shanxu Duan, 2021. "Short-Term Wind Power Prediction for Wind Farm Clusters Based on SFFS Feature Selection and BLSTM Deep Learning," Energies, MDPI, vol. 14(7), pages 1-18, March.
    20. Devabalaji Kaliaperumal Rukmani & Yuvaraj Thangaraj & Umashankar Subramaniam & Sitharthan Ramachandran & Rajvikram Madurai Elavarasan & Narottam Das & Luis Baringo & Mohamed Imran Abdul Rasheed, 2020. "A New Approach to Optimal Location and Sizing of DSTATCOM in Radial Distribution Networks Using Bio-Inspired Cuckoo Search Algorithm," Energies, MDPI, vol. 13(18), pages 1-21, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mahesh Kumar & Amir Mahmood Soomro & Waqar Uddin & Laveet Kumar, 2022. "Optimal Multi-Objective Placement and Sizing of Distributed Generation in Distribution System: A Comprehensive Review," Energies, MDPI, vol. 15(21), pages 1-48, October.
    2. Zhang, Shenxi & Cheng, Haozhong & Li, Ke & Tai, Nengling & Wang, Dan & Li, Furong, 2018. "Multi-objective distributed generation planning in distribution network considering correlations among uncertainties," Applied Energy, Elsevier, vol. 226(C), pages 743-755.
    3. Singh, Pushpendra & Meena, Nand K. & Yang, Jin & Vega-Fuentes, Eduardo & Bishnoi, Shree Krishna, 2020. "Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks," Applied Energy, Elsevier, vol. 278(C).
    4. Li, Yang & Feng, Bo & Wang, Bin & Sun, Shuchao, 2022. "Joint planning of distributed generations and energy storage in active distribution networks: A Bi-Level programming approach," Energy, Elsevier, vol. 245(C).
    5. Mohammadhafez Bazrafshan & Likhitha Yalamanchili & Nikolaos Gatsis & Juan Gomez, 2019. "Stochastic Planning of Distributed PV Generation," Energies, MDPI, vol. 12(3), pages 1-20, January.
    6. Mohamed A. Elseify & Salah Kamel & Hussein Abdel-Mawgoud & Ehab E. Elattar, 2022. "A Novel Approach Based on Honey Badger Algorithm for Optimal Allocation of Multiple DG and Capacitor in Radial Distribution Networks Considering Power Loss Sensitivity," Mathematics, MDPI, vol. 10(12), pages 1-26, June.
    7. Jiao, P.H. & Chen, J.J. & Cai, X. & Wang, L.L. & Zhao, Y.L. & Zhang, X.H. & Chen, W.G., 2021. "Joint active and reactive for allocation of renewable energy and energy storage under uncertain coupling," Applied Energy, Elsevier, vol. 302(C).
    8. Shahid Nawaz Khan & Syed Ali Abbas Kazmi & Abdullah Altamimi & Zafar A. Khan & Mohammed A. Alghassab, 2022. "Smart Distribution Mechanisms—Part I: From the Perspectives of Planning," Sustainability, MDPI, vol. 14(23), pages 1-109, December.
    9. Li, Yinxiao & Wang, Yi & Chen, Qixin, 2020. "Study on the impacts of meteorological factors on distributed photovoltaic accommodation considering dynamic line parameters," Applied Energy, Elsevier, vol. 259(C).
    10. Sultana, U. & Khairuddin, Azhar B. & Sultana, Beenish & Rasheed, Nadia & Qazi, Sajid Hussain & Malik, Nimra Riaz, 2018. "Placement and sizing of multiple distributed generation and battery swapping stations using grasshopper optimizer algorithm," Energy, Elsevier, vol. 165(PA), pages 408-421.
    11. José Adriano da Costa & David Alves Castelo Branco & Max Chianca Pimentel Filho & Manoel Firmino de Medeiros Júnior & Neilton Fidelis da Silva, 2019. "Optimal Sizing of Photovoltaic Generation in Radial Distribution Systems Using Lagrange Multipliers," Energies, MDPI, vol. 12(9), pages 1-19, May.
    12. Ma, Zherui & Dong, Fuxiang & Wang, Jiangjiang & Zhou, Yuan & Feng, Yingsong, 2023. "Optimal design of a novel hybrid renewable energy CCHP system considering long and short-term benefits," Renewable Energy, Elsevier, vol. 206(C), pages 72-85.
    13. Li, Yang & Yang, Zhen & Li, Guoqing & Mu, Yunfei & Zhao, Dongbo & Chen, Chen & Shen, Bo, 2018. "Optimal scheduling of isolated microgrid with an electric vehicle battery swapping station in multi-stakeholder scenarios: A bi-level programming approach via real-time pricing," Applied Energy, Elsevier, vol. 232(C), pages 54-68.
    14. Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
    15. Fu, Xueqian & Chen, Haoyong & Cai, Runqing & Yang, Ping, 2015. "Optimal allocation and adaptive VAR control of PV-DG in distribution networks," Applied Energy, Elsevier, vol. 137(C), pages 173-182.
    16. Mandhir Kumar Verma & Vivekananda Mukherjee & Vinod Kumar Yadav & Santosh Ghosh, 2020. "Constraints for effective distribution network expansion planning: an ample review," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 531-546, June.
    17. Zambrano-Asanza, S. & Quiros-Tortos, J. & Franco, John F., 2021. "Optimal site selection for photovoltaic power plants using a GIS-based multi-criteria decision making and spatial overlay with electric load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    18. Neshat, Mehdi & Mirjalili, Seyedali & Sergiienko, Nataliia Y. & Esmaeilzadeh, Soheil & Amini, Erfan & Heydari, Azim & Garcia, Davide Astiaso, 2022. "Layout optimisation of offshore wave energy converters using a novel multi-swarm cooperative algorithm with backtracking strategy: A case study from coasts of Australia," Energy, Elsevier, vol. 239(PE).
    19. Wu, Raphael & Sansavini, Giovanni, 2021. "Energy trilemma in active distribution network design: Balancing affordability, sustainability and security in optimization-based decision-making," Applied Energy, Elsevier, vol. 304(C).
    20. Yang, Dongfeng & Jiang, Chao & Cai, Guowei & Yang, Deyou & Liu, Xiaojun, 2020. "Interval method based optimal planning of multi-energy microgrid with uncertain renewable generation and demand," Applied Energy, Elsevier, vol. 277(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:233-234:y:2019:i::p:71-85. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.