IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v78y2015icp165-172.html
   My bibliography  Save this article

Sustainable energy system design with distributed renewable resources considering economic, environmental and uncertainty aspects

Author

Listed:
  • Abdullah, M.A.
  • Muttaqi, K.M.
  • Agalgaonkar, A.P.

Abstract

Electricity generation using renewable energy generation technologies is one of the most practical alternatives for network planners in order to achieve national and international Greenhouse Gas (GHG) emission reduction targets. Renewable Distributed Generation (DG) based Hybrid Energy System (HES) is a sustainable solution for serving electricity demand with reduced GHG emissions. A multi-objective optimisation technique for minimising cost, GHG emissions and generation uncertainty has been proposed in this paper to design HES for sustainable power generation and distribution system planning while considering economic and environmental issues and uncertainty in power availability of renewable resources. Life cycle assessment has been carried out to estimate the global warming potential of the embodied GHG emissions from the electricity generation technologies. The uncertainty in the availability of renewable resources is modelled using the method of moments. A design procedure for building sustainable HES has been presented and the sensitivity analysis is conducted for determining the optimal solution set.

Suggested Citation

  • Abdullah, M.A. & Muttaqi, K.M. & Agalgaonkar, A.P., 2015. "Sustainable energy system design with distributed renewable resources considering economic, environmental and uncertainty aspects," Renewable Energy, Elsevier, vol. 78(C), pages 165-172.
    • Handle: RePEc:eee:renene:v:78:y:2015:i:c:p:165-172
    DOI: 10.1016/j.renene.2014.12.044
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148114008714
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2014.12.044?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. Zhou, Wei & Lou, Chengzhi & Li, Zhongshi & Lu, Lin & Yang, Hongxing, 2010. "Current status of research on optimum sizing of stand-alone hybrid solar-wind power generation systems," Applied Energy, Elsevier, vol. 87(2), pages 380-389, February.
    2. Diaf, S. & Notton, G. & Belhamel, M. & Haddadi, M. & Louche, A., 2008. "Design and techno-economical optimization for hybrid PV/wind system under various meteorological conditions," Applied Energy, Elsevier, vol. 85(10), pages 968-987, October.
    3. Perera, A.T.D. & Attalage, R.A. & Perera, K.K.C.K. & Dassanayake, V.P.C., 2013. "Designing standalone hybrid energy systems minimizing initial investment, life cycle cost and pollutant emission," Energy, Elsevier, vol. 54(C), pages 220-230.
    4. 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.
    5. Abbes, Dhaker & Martinez, André & Champenois, Gérard, 2014. "Life cycle cost, embodied energy and loss of power supply probability for the optimal design of hybrid power systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 98(C), pages 46-62.
    6. 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.
    7. Dufo-López, Rodolfo & Bernal-Agustín, José L., 2008. "Multi-objective design of PV–wind–diesel–hydrogen–battery systems," Renewable Energy, Elsevier, vol. 33(12), pages 2559-2572.
    8. Abdullah, M.A. & Agalgaonkar, A.P. & Muttaqi, K.M., 2014. "Climate change mitigation with integration of renewable energy resources in the electricity grid of New South Wales, Australia," Renewable Energy, Elsevier, vol. 66(C), pages 305-313.
    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. Tsao, Yu-Chung & Thanh, Vo-Van & Lu, Jye-Chyi, 2019. "Multiobjective robust fuzzy stochastic approach for sustainable smart grid design," Energy, Elsevier, vol. 176(C), pages 929-939.
    2. Cosmi, Carmelina & Dvarionenė, Jolanta & Marques, Isabel & Di Leo, Senatro & Gecevičius, Giedrius & Gurauskienė, Inga & Mendes, Gisela & Selada, Catarina, 2015. "A holistic approach to sustainable energy development at regional level: The RENERGY self-assessment methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 693-707.
    3. Ahmed, Asam & Sutrisno, Setiadi Wicaksono & You, Siming, 2020. "A two-stage multi-criteria analysis method for planning renewable energy use and carbon saving," Energy, Elsevier, vol. 199(C).
    4. A. Rahman, Hasimah & Majid, Md. Shah & Rezaee Jordehi, A. & Chin Kim, Gan & Hassan, Mohammad Yusri & O. Fadhl, Saeed, 2015. "Operation and control strategies of integrated distributed energy resources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1412-1420.
    5. Ioannou, Anastasia & Angus, Andrew & Brennan, Feargal, 2017. "Risk-based methods for sustainable energy system planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 602-615.
    6. Díaz, Guzmán & Planas, Estefanía & Andreu, Jon & Kortabarria, Iñigo, 2015. "Joint cost of energy under an optimal economic policy of hybrid power systems subject to uncertainty," Energy, Elsevier, vol. 88(C), pages 837-848.
    7. 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).
    8. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Træholt, Chresten, 2018. "Optimization under uncertainty of a biomass-integrated renewable energy microgrid with energy storage," Renewable Energy, Elsevier, vol. 123(C), pages 204-217.
    9. Han, Jie & Ouyang, Leixin & Xu, Yuzhen & Zeng, Rong & Kang, Shushuo & Zhang, Guoqiang, 2016. "Current status of distributed energy system in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 288-297.
    10. Takashi Owaku & Hiromi Yamamoto & Atsushi Akisawa, 2023. "Optimal SOFC-CHP Installation Planning and Operation Model Considering Geographic Characteristics of Energy Supply Infrastructure," Energies, MDPI, vol. 16(5), pages 1-19, February.
    11. Zhou, Yuan & Wang, Jiangjiang & Li, Yuxin & Wei, Changqi, 2023. "A collaborative management strategy for multi-objective optimization of sustainable distributed energy system considering cloud energy storage," Energy, Elsevier, vol. 280(C).
    12. Novoa, Laura & Neal, Russ & Samuelsen, Scott & Brouwer, Jack, 2020. "Fuel cell transmission integrated grid energy resources to support generation-constrained power systems," Applied Energy, Elsevier, vol. 276(C).
    13. Mazzeo, Domenico & Matera, Nicoletta & De Luca, Pierangelo & Baglivo, Cristina & Maria Congedo, Paolo & Oliveti, Giuseppe, 2020. "Worldwide geographical mapping and optimization of stand-alone and grid-connected hybrid renewable system techno-economic performance across Köppen-Geiger climates," Applied Energy, Elsevier, vol. 276(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. Elma, Onur & Selamogullari, Ugur Savas, 2012. "A comparative sizing analysis of a renewable energy supplied stand-alone house considering both demand side and source side dynamics," Applied Energy, Elsevier, vol. 96(C), pages 400-408.
    2. 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.
    3. Sawle, Yashwant & Gupta, S.C. & Bohre, Aashish Kumar, 2018. "Review of hybrid renewable energy systems with comparative analysis of off-grid hybrid system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2217-2235.
    4. Asma Mohamad Aris & Bahman Shabani, 2015. "Sustainable Power Supply Solutions for Off-Grid Base Stations," Energies, MDPI, vol. 8(10), pages 1-38, September.
    5. Das, Barun K. & Al-Abdeli, Yasir M. & Kothapalli, Ganesh, 2017. "Optimisation of stand-alone hybrid energy systems supplemented by combustion-based prime movers," Applied Energy, Elsevier, vol. 196(C), pages 18-33.
    6. Perera, A.T.D. & Attalage, R.A. & Perera, K.K.C.K. & Dassanayake, V.P.C., 2013. "Designing standalone hybrid energy systems minimizing initial investment, life cycle cost and pollutant emission," Energy, Elsevier, vol. 54(C), pages 220-230.
    7. 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.
    8. Myeong Jin Ko & Yong Shik Kim & Min Hee Chung & Hung Chan Jeon, 2015. "Multi-Objective Optimization Design for a Hybrid Energy System Using the Genetic Algorithm," Energies, MDPI, vol. 8(4), pages 1-26, April.
    9. 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.
    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. Ould Bilal, B. & Sambou, V. & Ndiaye, P.A. & Kébé, C.M.F. & Ndongo, M., 2010. "Optimal design of a hybrid solar–wind-battery system using the minimization of the annualized cost system and the minimization of the loss of power supply probability (LPSP)," Renewable Energy, Elsevier, vol. 35(10), pages 2388-2390.
    13. 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.
    14. 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.
    15. Mohamed, Mohamed A. & Eltamaly, Ali M. & Alolah, Abdulrahman I., 2017. "Swarm intelligence-based optimization of grid-dependent hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 515-524.
    16. 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.
    17. Gupta, R.A. & Kumar, Rajesh & Bansal, Ajay Kumar, 2015. "BBO-based small autonomous hybrid power system optimization incorporating wind speed and solar radiation forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1366-1375.
    18. Upadhyay, Subho & Sharma, M.P., 2014. "A review on configurations, control and sizing methodologies of hybrid energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 47-63.
    19. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin, 2017. "Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 531-573.
    20. Khan, Mohammad Junaid & Yadav, Amit Kumar & Mathew, Lini, 2017. "Techno economic feasibility analysis of different combinations of PV-Wind-Diesel-Battery hybrid system for telecommunication applications in different cities of Punjab, India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 577-607.

    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:78:y:2015:i:c:p:165-172. 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.