IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v174y2016icp69-79.html
   My bibliography  Save this article

Smart grid adaptive energy conservation and optimization engine utilizing Particle Swarm Optimization and Fuzzification

Author

Listed:
  • Manbachi, Moein
  • Farhangi, Hassan
  • Palizban, Ali
  • Arzanpour, Siamak

Abstract

This paper aims to present a novel smart grid adaptive energy conservation and optimization engine for smart distribution networks. The optimization engine presented in this paper tries to minimize distribution network loss, improve voltage profile of the system and minimize the operating cost of reactive power injection by switchable shunt Capacitor Banks using Advanced Metering Infrastructure data. Moreover, it performs Conservation Voltage Reduction (CVR) and minimizes transformer loss. To accurately weight the optimization engine objective function sub-parts, Fuzzification technique is employed in this paper. Particle Swarm Optimization (PSO) is applied as Volt-VAR Optimization (VVO) algorithm. Substantial benefits of the proposed energy conservation and optimization engine include but not limited to: adequate accuracy and speed, comprehensive objective function, capability of using AMI data as inputs, and ability to determine weighting factors according to the cost of each objective sub-part. To precisely test the applicability of proposed engine, 33-node distribution feeder is used as case study. The result analysis shows that the proposed approach could lead distribution grids to achieve higher levels of optimization and efficiency compared with conventional techniques.

Suggested Citation

  • Manbachi, Moein & Farhangi, Hassan & Palizban, Ali & Arzanpour, Siamak, 2016. "Smart grid adaptive energy conservation and optimization engine utilizing Particle Swarm Optimization and Fuzzification," Applied Energy, Elsevier, vol. 174(C), pages 69-79.
    • Handle: RePEc:eee:appene:v:174:y:2016:i:c:p:69-79
    DOI: 10.1016/j.apenergy.2016.04.083
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626191630544X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2016.04.083?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. Venkatesan, Naveen & Solanki, Jignesh & Solanki, Sarika Khushalani, 2012. "Residential Demand Response model and impact on voltage profile and losses of an electric distribution network," Applied Energy, Elsevier, vol. 96(C), pages 84-91.
    2. Zakariazadeh, Alireza & Homaee, Omid & Jadid, Shahram & Siano, Pierluigi, 2014. "A new approach for real time voltage control using demand response in an automated distribution system," Applied Energy, Elsevier, vol. 117(C), pages 157-166.
    3. Niknam, Taher & Firouzi, Bahman Bahmani & Ostadi, Amir, 2010. "A new fuzzy adaptive particle swarm optimization for daily Volt/Var control in distribution networks considering distributed generators," Applied Energy, Elsevier, vol. 87(6), pages 1919-1928, June.
    4. Hung, Duong Quoc & Mithulananthan, N., 2014. "Loss reduction and loadability enhancement with DG: A dual-index analytical approach," Applied Energy, Elsevier, vol. 115(C), pages 233-241.
    5. Niknam, Taher, 2011. "A new HBMO algorithm for multiobjective daily Volt/Var control in distribution systems considering Distributed Generators," Applied Energy, Elsevier, vol. 88(3), pages 778-788, March.
    6. Manbachi, M. & Sadu, A. & Farhangi, H. & Monti, A. & Palizban, A. & Ponci, F. & Arzanpour, S., 2016. "Impact of EV penetration on Volt–VAR Optimization of distribution networks using real-time co-simulation monitoring platform," Applied Energy, Elsevier, vol. 169(C), pages 28-39.
    7. Zhe Xiao & Tinghua Li & Ming Huang & Jihong Shi & Jingjing Yang & Jiang Yu & Wei Wu, 2010. "Hierarchical MAS Based Control Strategy for Microgrid," Energies, MDPI, vol. 3(9), pages 1-17, September.
    8. Martinez-Rojas, Marcela & Sumper, Andreas & Gomis-Bellmunt, Oriol & Sudrià-Andreu, Antoni, 2011. "Reactive power dispatch in wind farms using particle swarm optimization technique and feasible solutions search," Applied Energy, Elsevier, vol. 88(12), pages 4678-4686.
    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. Bendu, Harisankar & Deepak, B.B.V.L. & Murugan, S., 2017. "Multi-objective optimization of ethanol fuelled HCCI engine performance using hybrid GRNN–PSO," Applied Energy, Elsevier, vol. 187(C), pages 601-611.
    2. Zhang, Bin & E, Jiaqiang & Gong, Jinke & Yuan, Wenhua & Zuo, Wei & Li, Yu & Fu, Jun, 2016. "Multidisciplinary design optimization of the diesel particulate filter in the composite regeneration process," Applied Energy, Elsevier, vol. 181(C), pages 14-28.
    3. Saxena, Vishal & Kumar, Niraj & Saxena, Vinod Kumar, 2019. "Multi-objective optimization of modified nanofluid fuel blends at different TiO2 nanoparticle concentration in diesel engine: Experimental assessment and modeling," Applied Energy, Elsevier, vol. 248(C), pages 330-353.
    4. Chen, J.J. & Zhuang, Y.B. & Li, Y.Z. & Wang, P. & Zhao, Y.L. & Zhang, C.S., 2017. "Risk-aware short term hydro-wind-thermal scheduling using a probability interval optimization model," Applied Energy, Elsevier, vol. 189(C), pages 534-554.
    5. Al-Sumaiti, Ameena Saad & Salama, Magdy M.A. & El-Moursi, Mohamed, 2017. "Enabling electricity access in developing countries: A probabilistic weather driven house based approach," Applied Energy, Elsevier, vol. 191(C), pages 531-548.
    6. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Ding, Fei & Wu, Jianzhong, 2018. "A centralized-based method to determine the local voltage control strategies of distributed generator operation in active distribution networks," Applied Energy, Elsevier, vol. 228(C), pages 2024-2036.
    7. Rosato, Antonello & Panella, Massimo & Andreotti, Amedeo & Mohammed, Osama A. & Araneo, Rodolfo, 2021. "Two-stage dynamic management in energy communities using a decision system based on elastic net regularization," Applied Energy, Elsevier, vol. 291(C).
    8. Barbie, Eli & Rabinovici, Raul & Kuperman, Alon, 2020. "Analytic formulation and optimization of weighted total harmonic distortion in single-phase staircase modulated multilevel inverters," Energy, Elsevier, vol. 199(C).
    9. Firouzi, Afshin & Meshkani, Ali, 2021. "Risk-based optimization of the debt service schedule in renewable energy project finance," Utilities Policy, Elsevier, vol. 70(C).
    10. Pyeong-Ik Hwang & Seung-Il Moon & Seon-Ju Ahn, 2016. "A Conservation Voltage Reduction Scheme for a Distribution Systems with Intermittent Distributed Generators," Energies, MDPI, vol. 9(9), pages 1-18, August.
    11. Tang, Jia & Wang, Dan & Wang, Xuyang & Jia, Hongjie & Wang, Chengshan & Huang, Renle & Yang, Zhanyong & Fan, Menghua, 2017. "Study on day-ahead optimal economic operation of active distribution networks based on Kriging model assisted particle swarm optimization with constraint handling techniques," Applied Energy, Elsevier, vol. 204(C), pages 143-162.
    12. Fagundez, J.L.S. & Lanzanova, T.D.M. & Martins, M.E.S. & Salau, N.P.G., 2020. "Joint use of artificial neural networks and particle swarm optimization to determine optimal performance of an ethanol SI engine operating with negative valve overlap strategy," Energy, Elsevier, vol. 204(C).
    13. Dan Wang & Qing’e Hu & Jia Tang & Hongjie Jia & Yun Li & Shuang Gao & Menghua Fan, 2017. "A Kriging Model Based Optimization of Active Distribution Networks Considering Loss Reduction and Voltage Profile Improvement," Energies, MDPI, vol. 10(12), pages 1-19, December.

    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. Samimi, Abouzar & Nikzad, Mehdi & Siano, Pierluigi, 2017. "Scenario-based stochastic framework for coupled active and reactive power market in smart distribution systems with demand response programs," Renewable Energy, Elsevier, vol. 109(C), pages 22-40.
    2. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Ding, Fei & Wu, Jianzhong, 2018. "A centralized-based method to determine the local voltage control strategies of distributed generator operation in active distribution networks," Applied Energy, Elsevier, vol. 228(C), pages 2024-2036.
    3. 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.
    4. Biswas (Raha), Syamasree & Mandal, Kamal Krishna & Chakraborty, Niladri, 2016. "Pareto-efficient double auction power transactions for economic reactive power dispatch," Applied Energy, Elsevier, vol. 168(C), pages 610-627.
    5. Petinrin, J.O. & Shaabanb, Mohamed, 2016. "Impact of renewable generation on voltage control in distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 770-783.
    6. Tang, Jia & Wang, Dan & Wang, Xuyang & Jia, Hongjie & Wang, Chengshan & Huang, Renle & Yang, Zhanyong & Fan, Menghua, 2017. "Study on day-ahead optimal economic operation of active distribution networks based on Kriging model assisted particle swarm optimization with constraint handling techniques," Applied Energy, Elsevier, vol. 204(C), pages 143-162.
    7. Tengku Juhana Tengku Hashim & Azah Mohamed, 2017. "Optimal coordinated voltage control in active distribution networks using backtracking search algorithm," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-20, October.
    8. 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.
    9. Zare, Mohsen & Niknam, Taher, 2013. "A new multi-objective for environmental and economic management of Volt/Var Control considering renewable energy resources," Energy, Elsevier, vol. 55(C), pages 236-252.
    10. Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    11. Niels Blaauwbroek & Phuong Nguyen & Han Slootweg, 2018. "Data-Driven Risk Analysis for Probabilistic Three-Phase Grid-Supportive Demand Side Management," Energies, MDPI, vol. 11(10), pages 1-18, September.
    12. Dan Wang & Qing’e Hu & Jia Tang & Hongjie Jia & Yun Li & Shuang Gao & Menghua Fan, 2017. "A Kriging Model Based Optimization of Active Distribution Networks Considering Loss Reduction and Voltage Profile Improvement," Energies, MDPI, vol. 10(12), pages 1-19, December.
    13. Arghandeh, Reza & Woyak, Jeremy & Onen, Ahmet & Jung, Jaesung & Broadwater, Robert P., 2014. "Economic optimal operation of Community Energy Storage systems in competitive energy markets," Applied Energy, Elsevier, vol. 135(C), pages 71-80.
    14. Martinez-Rojas, Marcela & Sumper, Andreas & Gomis-Bellmunt, Oriol & Sudrià-Andreu, Antoni, 2011. "Reactive power dispatch in wind farms using particle swarm optimization technique and feasible solutions search," Applied Energy, Elsevier, vol. 88(12), pages 4678-4686.
    15. Xu, Fang Yuan & Zhang, Tao & Lai, Loi Lei & Zhou, Hao, 2015. "Shifting Boundary for price-based residential demand response and applications," Applied Energy, Elsevier, vol. 146(C), pages 353-370.
    16. Erdinc, Ozan, 2014. "Economic impacts of small-scale own generating and storage units, and electric vehicles under different demand response strategies for smart households," Applied Energy, Elsevier, vol. 126(C), pages 142-150.
    17. Mak, Davye & Choeum, Daranith & Choi, Dae-Hyun, 2020. "Sensitivity analysis of volt-VAR optimization to data changes in distribution networks with distributed energy resources," Applied Energy, Elsevier, vol. 261(C).
    18. Singh, Bharat & Kumar, Ashwani, 2023. "Optimal energy management and feasibility analysis of hybrid renewable energy sources with BESS and impact of electric vehicle load with demand response program," Energy, Elsevier, vol. 278(PA).
    19. Mohagheghi, Erfan & Gabash, Aouss & Alramlawi, Mansour & Li, Pu, 2018. "Real-time optimal power flow with reactive power dispatch of wind stations using a reconciliation algorithm," Renewable Energy, Elsevier, vol. 126(C), pages 509-523.
    20. Anilkumar, T.T. & Simon, Sishaj P. & Padhy, Narayana Prasad, 2017. "Residential electricity cost minimization model through open well-pico turbine pumped storage system," Applied Energy, Elsevier, vol. 195(C), pages 23-35.

    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:174:y:2016:i:c:p:69-79. 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.