IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v133y2019icp971-999.html
   My bibliography  Save this article

Optimization of renewable hybrid energy systems – A multi-objective approach

Author

Listed:
  • Eriksson, E.L.V.
  • Gray, E.MacA.

Abstract

For a successful transition to a renewable energy economy, optimisation of renewable energy systems must evolve to take into account not only technical and/or economic objectives, but also environmental and socio-political objectives. A Normalised Weighted Constrained Multi-Objective (NWCMO) meta-heuristic optimisation algorithm has been proposed for achieving a compromise between mutually conflicting technical, economic, environmental and socio-political objectives, in order to simulate and optimise a renewable energy system of any configuration. In this paper, an optimisation methodology based on these four classes of objective is presented. The methodology was implemented using Particle Swarm Optimisation and tested against data from the literature. In the Case Study the original results could be reproduced, but the newly-implemented algorithm was further able to find a more optimal design solution under the same constraints. The influence of additional quantified socio-political inputs was explored.

Suggested Citation

  • Eriksson, E.L.V. & Gray, E.MacA., 2019. "Optimization of renewable hybrid energy systems – A multi-objective approach," Renewable Energy, Elsevier, vol. 133(C), pages 971-999.
    • Handle: RePEc:eee:renene:v:133:y:2019:i:c:p:971-999
    DOI: 10.1016/j.renene.2018.10.053
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148118312370
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2018.10.053?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. Borhanazad, Hanieh & Mekhilef, Saad & Gounder Ganapathy, Velappa & Modiri-Delshad, Mostafa & Mirtaheri, Ali, 2014. "Optimization of micro-grid system using MOPSO," Renewable Energy, Elsevier, vol. 71(C), pages 295-306.
    2. Mahmoud, Marwan M. & Ibrik, Imad H., 2006. "Techno-economic feasibility of energy supply of remote villages in Palestine by PV-systems, diesel generators and electric grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(2), pages 128-138, April.
    3. 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.
    4. Thomas Wiedmann & John Barrett, 2010. "A Review of the Ecological Footprint Indicator—Perceptions and Methods," Sustainability, MDPI, vol. 2(6), pages 1-49, June.
    5. 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.
    6. Eriksson, E.L.V. & Gray, E.MacA., 2017. "Optimization and integration of hybrid renewable energy hydrogen fuel cell energy systems – A critical review," Applied Energy, Elsevier, vol. 202(C), pages 348-364.
    7. Daud, Abdel-Karim & Ismail, Mahmoud S., 2012. "Design of isolated hybrid systems minimizing costs and pollutant emissions," Renewable Energy, Elsevier, vol. 44(C), pages 215-224.
    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. Akhlaque Ahmad Khan & Ahmad Faiz Minai & Rupendra Kumar Pachauri & Hasmat Malik, 2022. "Optimal Sizing, Control, and Management Strategies for Hybrid Renewable Energy Systems: A Comprehensive Review," Energies, MDPI, vol. 15(17), pages 1-29, August.
    2. Ullah, Zia & Elkadeem, M.R. & Kotb, Kotb M. & Taha, Ibrahim B.M. & Wang, Shaorong, 2021. "Multi-criteria decision-making model for optimal planning of on/off grid hybrid solar, wind, hydro, biomass clean electricity supply," Renewable Energy, Elsevier, vol. 179(C), pages 885-910.
    3. Ming, Bo & Liu, Pan & Guo, Shenglian & Cheng, Lei & Zhang, Jingwen, 2019. "Hydropower reservoir reoperation to adapt to large-scale photovoltaic power generation," Energy, Elsevier, vol. 179(C), pages 268-279.
    4. Dincer, Hasan & Yuksel, Serhat, 2019. "Balanced scorecard-based analysis of investment decisions for the renewable energy alternatives: A comparative analysis based on the hybrid fuzzy decision-making approach," Energy, Elsevier, vol. 175(C), pages 1259-1270.
    5. Alfonso Angel Medina-Santana & Leopoldo Eduardo Cárdenas-Barrón, 2022. "Optimal Design of Hybrid Renewable Energy Systems Considering Weather Forecasting Using Recurrent Neural Networks," Energies, MDPI, vol. 15(23), pages 1-28, November.
    6. He, Yi & Guo, Su & Zhou, Jianxu & Ye, Jilei & Huang, Jing & Zheng, Kun & Du, Xinru, 2022. "Multi-objective planning-operation co-optimization of renewable energy system with hybrid energy storages," Renewable Energy, Elsevier, vol. 184(C), pages 776-790.
    7. Sean Williams & Michael Short & Tracey Crosbie & Maryam Shadman-Pajouh, 2020. "A Decentralized Informatics, Optimization, and Control Framework for Evolving Demand Response Services," Energies, MDPI, vol. 13(16), pages 1-30, August.
    8. Güven, Aykut Fatih & Yörükeren, Nuran & Samy, Mohamed Mahmoud, 2022. "Design optimization of a stand-alone green energy system of university campus based on Jaya-Harmony Search and Ant Colony Optimization algorithms approaches," Energy, Elsevier, vol. 253(C).
    9. Mokhtara, Charafeddine & Negrou, Belkhir & Settou, Noureddine & Settou, Belkhir & Samy, Mohamed Mahmoud, 2021. "Design optimization of off-grid Hybrid Renewable Energy Systems considering the effects of building energy performance and climate change: Case study of Algeria," Energy, Elsevier, vol. 219(C).
    10. Mulako D. Mukelabai & K. G. U. Wijayantha & Richard E. Blanchard, 2022. "Hydrogen for Cooking: A Review of Cooking Technologies, Renewable Hydrogen Systems and Techno-Economics," Sustainability, MDPI, vol. 14(24), pages 1-30, December.
    11. Jin, Xiaoyu & Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Zhang, Yi & Zhao, Zhipeng & Lu, Jia, 2022. "Wasserstein metric-based two-stage distributionally robust optimization model for optimal daily peak shaving dispatch of cascade hydroplants under renewable energy uncertainties," Energy, Elsevier, vol. 260(C).
    12. Noorollahi, Younes & Golshanfard, Aminabbas & Hashemi-Dezaki, Hamed, 2022. "A scenario-based approach for optimal operation of energy hub under different schemes and structures," Energy, Elsevier, vol. 251(C).
    13. Jahangir, Mohammad Hossein & Montazeri, Mohammad & Mousavi, Seyed Ali & Kargarzadeh, Arash, 2022. "Reducing carbon emissions of industrial large livestock farms using hybrid renewable energy systems," Renewable Energy, Elsevier, vol. 189(C), pages 52-65.
    14. Wadim Strielkowski & Elena Volkova & Luidmila Pushkareva & Dalia Streimikiene, 2019. "Innovative Policies for Energy Efficiency and the Use of Renewables in Households," Energies, MDPI, vol. 12(7), pages 1-17, April.
    15. Rullo, P. & Braccia, L. & Luppi, P. & Zumoffen, D. & Feroldi, D., 2019. "Integration of sizing and energy management based on economic predictive control for standalone hybrid renewable energy systems," Renewable Energy, Elsevier, vol. 140(C), pages 436-451.
    16. Ailliot, Pierre & Boutigny, Marie & Koutroulis, Eftichis & Malisovas, Athanasios & Monbet, Valérie, 2020. "Stochastic weather generator for the design and reliability evaluation of desalination systems with Renewable Energy Sources," Renewable Energy, Elsevier, vol. 158(C), pages 541-553.
    17. Fonseca, Juan D. & Commenge, Jean-Marc & Camargo, Mauricio & Falk, Laurent & Gil, Iván D., 2021. "Multi-criteria optimization for the design and operation of distributed energy systems considering sustainability dimensions," Energy, Elsevier, vol. 214(C).
    18. Gong, Yu & Liu, Pan & Ming, Bo & Li, Dingfang, 2021. "Identifying the effect of forecast uncertainties on hybrid power system operation: A case study of Longyangxia hydro–photovoltaic plant in China," Renewable Energy, Elsevier, vol. 178(C), pages 1303-1321.
    19. Fioriti, Davide & Pintus, Salvatore & Lutzemberger, Giovanni & Poli, Davide, 2020. "Economic multi-objective approach to design off-grid microgrids: A support for business decision making," Renewable Energy, Elsevier, vol. 159(C), pages 693-704.
    20. 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).

    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. 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.
    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. Mandelli, Stefano & Barbieri, Jacopo & Mereu, Riccardo & Colombo, Emanuela, 2016. "Off-grid systems for rural electrification in developing countries: Definitions, classification and a comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1621-1646.
    4. Mohammadali Kiehbadroudinezhad & Adel Merabet & Ahmed G. Abo-Khalil & Tareq Salameh & Chaouki Ghenai, 2022. "Intelligent and Optimized Microgrids for Future Supply Power from Renewable Energy Resources: A Review," Energies, MDPI, vol. 15(9), pages 1-21, May.
    5. Zakaria Belboul & Belgacem Toual & Abdellah Kouzou & Lakhdar Mokrani & Abderrahman Bensalem & Ralph Kennel & Mohamed Abdelrahem, 2022. "Multiobjective Optimization of a Hybrid PV/Wind/Battery/Diesel Generator System Integrated in Microgrid: A Case Study in Djelfa, Algeria," Energies, MDPI, vol. 15(10), pages 1-30, May.
    6. Juaidi, Adel & Montoya, Francisco G. & Ibrik, Imad H. & Manzano-Agugliaro, Francisco, 2016. "An overview of renewable energy potential in Palestine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 943-960.
    7. 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.
    8. Galindo Noguera, Ana Lisbeth & Mendoza Castellanos, Luis Sebastian & Silva Lora, Electo Eduardo & Melian Cobas, Vladimir Rafael, 2018. "Optimum design of a hybrid diesel-ORC / photovoltaic system using PSO: Case study for the city of Cujubim, Brazil," Energy, Elsevier, vol. 142(C), pages 33-45.
    9. Cheng, Yu-Shan & Chuang, Man-Tsai & Liu, Yi-Hua & Wang, Shun-Chung & Yang, Zong-Zhen, 2016. "A particle swarm optimization based power dispatch algorithm with roulette wheel re-distribution mechanism for equality constraint," Renewable Energy, Elsevier, vol. 88(C), pages 58-72.
    10. Jiao, P.H. & Chen, J.J. & Peng, K. & Zhao, Y.L. & Xin, K.F., 2020. "Multi-objective mean-semi-entropy model for optimal standalone micro-grid planning with uncertain renewable energy resources," Energy, Elsevier, vol. 191(C).
    11. 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.
    12. Hemmati, S. & Ghaderi, S.F. & Ghazizadeh, M.S., 2018. "Sustainable energy hub design under uncertainty using Benders decomposition method," Energy, Elsevier, vol. 143(C), pages 1029-1047.
    13. 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).
    14. Fodhil, F. & Hamidat, A. & Nadjemi, O., 2019. "Potential, optimization and sensitivity analysis of photovoltaic-diesel-battery hybrid energy system for rural electrification in Algeria," Energy, Elsevier, vol. 169(C), pages 613-624.
    15. 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.
    16. Ramli, Makbul A.M. & Bouchekara, H.R.E.H. & Alghamdi, Abdulsalam S., 2018. "Optimal sizing of PV/wind/diesel hybrid microgrid system using multi-objective self-adaptive differential evolution algorithm," Renewable Energy, Elsevier, vol. 121(C), pages 400-411.
    17. Sudhanshu Ranjan & D. C. Das & A. Latif & N. Sinha, 2021. "Electric vehicles to renewable-three unequal areas-hybrid microgrid to contain system frequency using mine blast algorithm based control strategy," 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. 12(5), pages 961-975, October.
    18. 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.
    19. Ying-Yi Hong & Yuan-Ming Lai & Yung-Ruei Chang & Yih-Der Lee & Pang-Wei Liu, 2015. "Optimizing Capacities of Distributed Generation and Energy Storage in a Small Autonomous Power System Considering Uncertainty in Renewables," Energies, MDPI, vol. 8(4), pages 1-20, March.
    20. 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.

    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:renene:v:133:y:2019:i:c:p:971-999. 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/renewable-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.