IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i4p1007-d142300.html
   My bibliography  Save this article

Energy Quality Management for a Micro Energy Network Integrated with Renewables in a Tourist Area: A Chinese Case Study

Author

Listed:
  • Hai Lu

    (Electric Power Test and Research Institute, Yunnan Power Grid, Kunming 650217, China
    These authors contributed equally to this work.)

  • Jiaquan Yang

    (Electric Power Test and Research Institute, Yunnan Power Grid, Kunming 650217, China
    These authors contributed equally to this work.)

  • Kari Alanne

    (Department of Mechanical Engineering, Aalto University, P.O. Box 14100, 00076 Aalto, Finland)

Abstract

For a tourist area (TA), energy utilization is mostly concentrated in certain period of time. Therefore, the peak load is several times more than the average load. A Micro Energy Network Integrated with Renewables (MENR) system is considered as a potential solution to mitigate this problem. To design an appropriate MENR system, a multi-objective energy quality management (EQM) method based on the Genetic Algorithm is proposed. Here, EQM aims at reducing the primary energy consumption and optimizing the energy shares of various renewables in a MENR system. In addition to minimizing life-cycle costs and maximizing the exergy efficiency of a MENR system, the issue of system reliability is addressed. Then, a case study is presented, where the EQM method is applied to a TA located in Dali, China. Three possible reference MENR scenarios are analyzed. After confirming the reference scenarios, advanced MENR scenarios with improved system reliability are discussed. The rest of the work is dedicated to investigating the effects of various energy storage systems (ESSs) parameters and the number of electric vehicles (EVs) on MENR scenarios. The results suggest that there are significant differences between various MENR scenarios depending on the number of EVs and the investment reduction of ESSs.

Suggested Citation

  • Hai Lu & Jiaquan Yang & Kari Alanne, 2018. "Energy Quality Management for a Micro Energy Network Integrated with Renewables in a Tourist Area: A Chinese Case Study," Energies, MDPI, vol. 11(4), pages 1-24, April.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:1007-:d:142300
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/4/1007/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/11/4/1007/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Henning, Hans-Martin & Palzer, Andreas, 2014. "A comprehensive model for the German electricity and heat sector in a future energy system with a dominant contribution from renewable energy technologies—Part I: Methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 1003-1018.
    3. Sherwani, A.F. & Usmani, J.A. & Varun, 2010. "Life cycle assessment of solar PV based electricity generation systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(1), pages 540-544, January.
    4. 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.
    5. Aboelsood Zidan & Hossam A. Gabbar, 2016. "DG Mix and Energy Storage Units for Optimal Planning of Self-Sufficient Micro Energy Grids," Energies, MDPI, vol. 9(8), pages 1-18, August.
    6. Palzer, Andreas & Henning, Hans-Martin, 2014. "A comprehensive model for the German electricity and heat sector in a future energy system with a dominant contribution from renewable energy technologies – Part II: Results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 1019-1034.
    7. Alberto Dolara & Francesco Grimaccia & Giulia Magistrati & Gabriele Marchegiani, 2017. "Optimization Models for Islanded Micro-Grids: A Comparative Analysis between Linear Programming and Mixed Integer Programming," Energies, MDPI, vol. 10(2), pages 1-20, February.
    8. Zhao, Bo & Zhang, Xuesong & Li, Peng & Wang, Ke & Xue, Meidong & Wang, Caisheng, 2014. "Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island," Applied Energy, Elsevier, vol. 113(C), pages 1656-1666.
    9. Guo, Li & Wang, Nan & Lu, Hai & Li, Xialin & Wang, Chengshan, 2016. "Multi-objective optimal planning of the stand-alone microgrid system based on different benefit subjects," Energy, Elsevier, vol. 116(P1), pages 353-363.
    10. Crawford, R.H., 2009. "Life cycle energy and greenhouse emissions analysis of wind turbines and the effect of size on energy yield," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2653-2660, December.
    11. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    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. Ivan Lorencin & Nikola Anđelić & Vedran Mrzljak & Zlatan Car, 2019. "Genetic Algorithm Approach to Design of Multi-Layer Perceptron for Combined Cycle Power Plant Electrical Power Output Estimation," Energies, MDPI, vol. 12(22), pages 1-26, November.
    2. Lyubov Y. Matich, 2017. "Roadmaps as a Tool for Modeling Complex Systems," HSE Working papers WP BRP 73/STI/2017, National Research University Higher School of Economics.

    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. 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.
    2. 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.
    3. 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.
    4. Izadyar, Nima & Ong, Hwai Chyuan & Chong, W.T. & Leong, K.Y., 2016. "Resource assessment of the renewable energy potential for a remote area: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 908-923.
    5. 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.
    6. 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.
    7. Mauleón, Ignacio, 2019. "Assessing PV and wind roadmaps: Learning rates, risk, and social discounting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 71-89.
    8. Ma, Weiwu & Xue, Xinpei & Liu, Gang, 2018. "Techno-economic evaluation for hybrid renewable energy system: Application and merits," Energy, Elsevier, vol. 159(C), pages 385-409.
    9. Graham Palmer, 2017. "A Framework for Incorporating EROI into Electrical Storage," Biophysical Economics and Resource Quality, Springer, vol. 2(2), pages 1-19, June.
    10. Schreiner, Lena & Madlener, Reinhard, 2022. "Investing in power grid infrastructure as a flexibility option: A DSGE assessment for Germany," Energy Economics, Elsevier, vol. 107(C).
    11. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    12. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    13. Maruf, Md. Nasimul Islam, 2021. "Open model-based analysis of a 100% renewable and sector-coupled energy system–The case of Germany in 2050," Applied Energy, Elsevier, vol. 288(C).
    14. Theresa Liegl & Simon Schramm & Philipp Kuhn & Thomas Hamacher, 2023. "Considering Socio-Technical Parameters in Energy System Models—The Current Status and Next Steps," Energies, MDPI, vol. 16(20), pages 1-19, October.
    15. Mehrabankhomartash, Mahmoud & Rayati, Mohammad & Sheikhi, Aras & Ranjbar, Ali Mohammad, 2017. "Practical battery size optimization of a PV system by considering individual customer damage function," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 36-50.
    16. Shirizadeh, Behrang & Quirion, Philippe, 2022. "The importance of renewable gas in achieving carbon-neutrality: Insights from an energy system optimization model," Energy, Elsevier, vol. 255(C).
    17. Al Busaidi, Ahmed Said & Kazem, Hussein A & Al-Badi, Abdullah H & Farooq Khan, Mohammad, 2016. "A review of optimum sizing of hybrid PV–Wind renewable energy systems in oman," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 185-193.
    18. Avinash Vijay & Adam Hawkes, 2017. "The Techno-Economics of Small-Scale Residential Heating in Low Carbon Futures," Energies, MDPI, vol. 10(11), pages 1-23, November.
    19. Bartholdsen, Hans-Karl & Eidens, Anna & Löffler, Konstantin & Seehaus, Frederik & Wejda, Felix & Burandt, Thorsten & Oei, Pao-Yu & Kemfert, Claudia & Hirschhausen, Christian von, 2019. "Pathways for Germany's Low-Carbon Energy Transformation Towards 2050," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 12(15), pages 1-33.
    20. Khatib, Tamer & Mohamed, Azah & Sopian, K., 2013. "A review of photovoltaic systems size optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 454-465.

    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:gam:jeners:v:11:y:2018:i:4:p:1007-:d:142300. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.