IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v141y2017icp2288-2299.html
   My bibliography  Save this article

An efficient multi-objective model and algorithm for sizing a stand-alone hybrid renewable energy system

Author

Listed:
  • Wang, Rui
  • Li, Guozheng
  • Ming, Mengjun
  • Wu, Guohua
  • Wang, Ling

Abstract

Hybrid renewable energy system (HRES) has continuously been demonstrated effective in making use of renewable energies, e.g., solar, wind. This study proposes a novel multi-objective model and algorithm for optimizing the size of a typical stand-alone HRES that is composed of photovoltaic (PV) panels, wind turbines, battery banks and diesels. Notably, the proposed model considers minimization of annualized system cost (economy), loss of power supply probability (reliability) and greenhouse gas emission (environment), and enables a decision maker to optimize both the number and the type of PV panel, wind turbine, battery and diesel generator as well as the PV panel installation angle, the wind turbine installation height. To effectively solve the model, in particular, dealing with mixed types of decision variables including integer, real and categorical values, the non-dominated sorting algorithm II (NSGA-II) embedded with a re-ranking based genetic operators is proposed. Lastly, a case study is presented to demonstrate the effectiveness and efficiency of the proposed model and algorithm.

Suggested Citation

  • Wang, Rui & Li, Guozheng & Ming, Mengjun & Wu, Guohua & Wang, Ling, 2017. "An efficient multi-objective model and algorithm for sizing a stand-alone hybrid renewable energy system," Energy, Elsevier, vol. 141(C), pages 2288-2299.
  • Handle: RePEc:eee:energy:v:141:y:2017:i:c:p:2288-2299
    DOI: 10.1016/j.energy.2017.11.085
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217319436
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2017.11.085?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. Yang, Hongxing & Wei, Zhou & Chengzhi, Lou, 2009. "Optimal design and techno-economic analysis of a hybrid solar-wind power generation system," Applied Energy, Elsevier, vol. 86(2), pages 163-169, February.
    2. Ju, Liwei & Tan, Zhongfu & Li, Huanhuan & Tan, Qingkun & Yu, Xiaobao & Song, Xiaohua, 2016. "Multi-objective operation optimization and evaluation model for CCHP and renewable energy based hybrid energy system driven by distributed energy resources in China," Energy, Elsevier, vol. 111(C), pages 322-340.
    3. Jung, Jaesung & Villaran, Michael, 2017. "Optimal planning and design of hybrid renewable energy systems for microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 180-191.
    4. Siddaiah, Rajanna & Saini, R.P., 2016. "A review on planning, configurations, modeling and optimization techniques of hybrid renewable energy systems for off grid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 376-396.
    5. Sharafi, Masoud & ELMekkawy, Tarek Y., 2014. "Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach," Renewable Energy, Elsevier, vol. 68(C), pages 67-79.
    6. Bahramara, S. & Moghaddam, M. Parsa & Haghifam, M.R., 2016. "Optimal planning of hybrid renewable energy systems using HOMER: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 609-620.
    7. Maheri, Alireza, 2014. "Multi-objective design optimisation of standalone hybrid wind-PV-diesel systems under uncertainties," Renewable Energy, Elsevier, vol. 66(C), pages 650-661.
    8. Madhlopa, Amos & Sparks, Debbie & Keen, Samantha & Moorlach, Mascha & Krog, Pieter & Dlamini, Thuli, 2015. "Optimization of a PV–wind hybrid system under limited water resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 324-331.
    9. Mohammed, Y.S. & Mustafa, M.W. & Bashir, N., 2014. "Hybrid renewable energy systems for off-grid electric power: Review of substantial issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 527-539.
    10. Rui Wang & Maszatul M. Mansor & Robin C. Purshouse & Peter J. Fleming, 2015. "An analysis of parameter sensitivities of preference-inspired co-evolutionary algorithms," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(13), pages 2407-2420, October.
    11. Abedi, S. & Alimardani, A. & Gharehpetian, G.B. & Riahy, G.H. & Hosseinian, S.H., 2012. "A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1577-1587.
    12. Wang, Rui & Purshouse, Robin C. & Fleming, Peter J., 2015. "Preference-inspired co-evolutionary algorithms using weight vectors," European Journal of Operational Research, Elsevier, vol. 243(2), pages 423-441.
    13. Sharafi, Masoud & ElMekkawy, Tarek Y., 2015. "Stochastic optimization of hybrid renewable energy systems using sampling average method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1668-1679.
    14. Cozzolino, R. & Tribioli, L. & Bella, G., 2016. "Power management of a hybrid renewable system for artificial islands: A case study," Energy, Elsevier, vol. 106(C), pages 774-789.
    15. Maleki, Akbar & Pourfayaz, Fathollah & Rosen, Marc A., 2016. "A novel framework for optimal design of hybrid renewable energy-based autonomous energy systems: A case study for Namin, Iran," Energy, Elsevier, vol. 98(C), pages 168-180.
    16. Soroudi, Alireza & Amraee, Turaj, 2013. "Decision making under uncertainty in energy systems: State of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 376-384.
    17. Dufo-López, Rodolfo & Bernal-Agustín, José L. & Yusta-Loyo, José M. & Domínguez-Navarro, José A. & Ramírez-Rosado, Ignacio J. & Lujano, Juan & Aso, Ismael, 2011. "Multi-objective optimization minimizing cost and life cycle emissions of stand-alone PV–wind–diesel systems with batteries storage," Applied Energy, Elsevier, vol. 88(11), pages 4033-4041.
    18. Fadaee, M. & Radzi, M.A.M., 2012. "Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3364-3369.
    19. Wang, Rui & Purshouse, Robin C. & Giagkiozis, Ioannis & Fleming, Peter J., 2015. "The iPICEA-g: a new hybrid evolutionary multi-criteria decision making approach using the brushing technique," European Journal of Operational Research, Elsevier, vol. 243(2), pages 442-453.
    20. Sinha, Sunanda & Chandel, S.S., 2014. "Review of software tools for hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 192-205.
    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. Khaled Guerraiche & Latifa Dekhici & Eric Chatelet & Abdelkader Zeblah, 2023. "Techno-Economic Green Optimization of Electrical Microgrid Using Swarm Metaheuristics," Energies, MDPI, vol. 16(4), pages 1-19, February.
    2. Maheri, Alireza & Unsal, Ibrahim & Mahian, Omid, 2022. "Multiobjective optimisation of hybrid wind-PV-battery-fuel cell-electrolyser-diesel systems: An integrated configuration-size formulation approach," Energy, Elsevier, vol. 241(C).
    3. Hou, Hui & Xu, Tao & Wu, Xixiu & Wang, Huan & Tang, Aihong & Chen, Yangyang, 2020. "Optimal capacity configuration of the wind-photovoltaic-storage hybrid power system based on gravity energy storage system," Applied Energy, Elsevier, vol. 271(C).
    4. Houssem R. E. H. Bouchekara & Yusuf A. Sha’aban & Mohammad S. Shahriar & Saad M. Abdullah & Makbul A. Ramli, 2023. "Sizing of Hybrid PV/Battery/Wind/Diesel Microgrid System Using an Improved Decomposition Multi-Objective Evolutionary Algorithm Considering Uncertainties and Battery Degradation," Sustainability, MDPI, vol. 15(14), pages 1-38, July.
    5. Abdelkader, Abbassi & Rabeh, Abbassi & Mohamed Ali, Dami & Mohamed, Jemli, 2018. "Multi-objective genetic algorithm based sizing optimization of a stand-alone wind/PV power supply system with enhanced battery/supercapacitor hybrid energy storage," Energy, Elsevier, vol. 163(C), pages 351-363.
    6. Fares, Dalila & Fathi, Mohamed & Mekhilef, Saad, 2022. "Performance evaluation of metaheuristic techniques for optimal sizing of a stand-alone hybrid PV/wind/battery system," Applied Energy, Elsevier, vol. 305(C).
    7. He, Yi & Guo, Su & Zhou, Jianxu & Wu, Feng & Huang, Jing & Pei, Huanjin, 2021. "The many-objective optimal design of renewable energy cogeneration system," Energy, Elsevier, vol. 234(C).
    8. Huang, Zishuo & Yu, Hang & Chu, Xiangyang & Peng, Zhenwei, 2018. "A novel optimization model based on game tree for multi-energy conversion systems," Energy, Elsevier, vol. 150(C), pages 109-121.
    9. Wang, Rui & Xiong, Jian & He, Min-fan & Gao, Liang & Wang, Ling, 2020. "Multi-objective optimal design of hybrid renewable energy system under multiple scenarios," Renewable Energy, Elsevier, vol. 151(C), pages 226-237.
    10. Sadeghi, Delnia & Ahmadi, Seyed Ehsan & Amiri, Nima & Satinder, & Marzband, Mousa & Abusorrah, Abdullah & Rawa, Muhyaddin, 2022. "Designing, optimizing and comparing distributed generation technologies as a substitute system for reducing life cycle costs, CO2 emissions, and power losses in residential buildings," Energy, Elsevier, vol. 253(C).
    11. Xu, Xiao & Hu, Weihao & Cao, Di & Huang, Qi & Chen, Cong & Chen, Zhe, 2020. "Optimized sizing of a standalone PV-wind-hydropower station with pumped-storage installation hybrid energy system," Renewable Energy, Elsevier, vol. 147(P1), pages 1418-1431.
    12. Kong, Xue & Wang, Hongye & Li, Nan & Mu, Hailin, 2022. "Multi-objective optimal allocation and performance evaluation for energy storage in energy systems," Energy, Elsevier, vol. 253(C).
    13. Oviedo-Cepeda, J.C. & Serna-Suárez, Ivan & Osma-Pinto, German & Duarte, Cesar & Solano, Javier & Gabbar, Hossam A., 2020. "Design of tariff schemes as demand response mechanisms for stand-alone microgrids planning," Energy, Elsevier, vol. 211(C).
    14. Zeljković, Čedomir & Mršić, Predrag & Erceg, Bojan & Lekić, Đorđe & Kitić, Nemanja & Matić, Petar, 2022. "Optimal sizing of photovoltaic-wind-diesel-battery power supply for mobile telephony base stations," Energy, Elsevier, vol. 242(C).
    15. Frangopoulos, Christos A., 2018. "Recent developments and trends in optimization of energy systems," Energy, Elsevier, vol. 164(C), pages 1011-1020.
    16. Rahmat Khezri & Amin Mahmoudi & Hirohisa Aki & S. M. Muyeen, 2021. "Optimal Planning of Remote Area Electricity Supply Systems: Comprehensive Review, Recent Developments and Future Scopes," Energies, MDPI, vol. 14(18), pages 1-29, September.
    17. Qian Liu & Rui Wang & Yan Zhang & Guohua Wu & Jianmai Shi, 2018. "An Optimal and Distributed Demand Response Strategy for Energy Internet Management," Energies, MDPI, vol. 11(1), pages 1-16, January.

    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. Wang, Rui & Xiong, Jian & He, Min-fan & Gao, Liang & Wang, Ling, 2020. "Multi-objective optimal design of hybrid renewable energy system under multiple scenarios," Renewable Energy, Elsevier, vol. 151(C), pages 226-237.
    2. Anoune, Kamal & Bouya, Mohsine & Astito, Abdelali & Abdellah, Abdellatif Ben, 2018. "Sizing methods and optimization techniques for PV-wind based hybrid renewable energy system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 652-673.
    3. Chauhan, Anurag & Saini, R.P., 2014. "A review on Integrated Renewable Energy System based power generation for stand-alone applications: Configurations, storage options, sizing methodologies and control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 99-120.
    4. Tezer, Tuba & Yaman, Ramazan & Yaman, Gülşen, 2017. "Evaluation of approaches used for optimization of stand-alone hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 840-853.
    5. Rahmat Khezri & Amin Mahmoudi & Hirohisa Aki & S. M. Muyeen, 2021. "Optimal Planning of Remote Area Electricity Supply Systems: Comprehensive Review, Recent Developments and Future Scopes," Energies, MDPI, vol. 14(18), pages 1-29, September.
    6. Siddaiah, Rajanna & Saini, R.P., 2016. "A review on planning, configurations, modeling and optimization techniques of hybrid renewable energy systems for off grid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 376-396.
    7. Dufo-López, Rodolfo & Cristóbal-Monreal, Iván R. & Yusta, José M., 2016. "Optimisation of PV-wind-diesel-battery stand-alone systems to minimise cost and maximise human development index and job creation," Renewable Energy, Elsevier, vol. 94(C), pages 280-293.
    8. Azaza, Maher & Wallin, Fredrik, 2017. "Multi objective particle swarm optimization of hybrid micro-grid system: A case study in Sweden," Energy, Elsevier, vol. 123(C), pages 108-118.
    9. Mayer, Martin János & Szilágyi, Artúr & Gróf, Gyula, 2020. "Environmental and economic multi-objective optimization of a household level hybrid renewable energy system by genetic algorithm," Applied Energy, Elsevier, vol. 269(C).
    10. Sinha, Sunanda & Chandel, S.S., 2015. "Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 755-769.
    11. Mahesh, Aeidapu & Sandhu, Kanwarjit Singh, 2015. "Hybrid wind/photovoltaic energy system developments: Critical review and findings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1135-1147.
    12. Scheubel, Christopher & Zipperle, Thomas & Tzscheutschler, Peter, 2017. "Modeling of industrial-scale hybrid renewable energy systems (HRES) – The profitability of decentralized supply for industry," Renewable Energy, Elsevier, vol. 108(C), pages 52-63.
    13. Dufo-López, Rodolfo & Cristóbal-Monreal, Iván R. & Yusta, José M., 2016. "Stochastic-heuristic methodology for the optimisation of components and control variables of PV-wind-diesel-battery stand-alone systems," Renewable Energy, Elsevier, vol. 99(C), pages 919-935.
    14. Jung, Jaesung & Villaran, Michael, 2017. "Optimal planning and design of hybrid renewable energy systems for microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 180-191.
    15. Asma Mohamad Aris & Bahman Shabani, 2015. "Sustainable Power Supply Solutions for Off-Grid Base Stations," Energies, MDPI, vol. 8(10), pages 1-38, September.
    16. Nadjemi, O. & Nacer, T. & Hamidat, A. & Salhi, H., 2017. "Optimal hybrid PV/wind energy system sizing: Application of cuckoo search algorithm for Algerian dairy farms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1352-1365.
    17. Fathima, A. Hina & Palanisamy, K., 2015. "Optimization in microgrids with hybrid energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 431-446.
    18. Jiaxin Lu & Weijun Wang & Yingchao Zhang & Song Cheng, 2017. "Multi-Objective Optimal Design of Stand-Alone Hybrid Energy System Using Entropy Weight Method Based on HOMER," Energies, MDPI, vol. 10(10), pages 1-17, October.
    19. Jaszczur, Marek & Hassan, Qusay & Palej, Patryk & Abdulateef, Jasim, 2020. "Multi-Objective optimisation of a micro-grid hybrid power system for household application," Energy, Elsevier, vol. 202(C).
    20. Guozheng Li & Rui Wang & Tao Zhang & Mengjun Ming, 2018. "Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g," Energies, MDPI, vol. 11(4), pages 1-26, March.

    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:energy:v:141:y:2017:i:c:p:2288-2299. 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.journals.elsevier.com/energy .

    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.