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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
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    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.
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    3. 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.

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