IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v16y2012i3p1577-1587.html
   My bibliography  Save this article

A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems

Author

Listed:
  • Abedi, S.
  • Alimardani, A.
  • Gharehpetian, G.B.
  • Riahy, G.H.
  • Hosseinian, S.H.

Abstract

The power management strategy (PMS) plays an important role in the optimum design and efficient utilization of hybrid energy systems. The power available from hybrid systems and the overall lifetime of system components are highly affected by PMS. This paper presents a novel method for the determination of the optimum PMS of hybrid energy systems including various generators and storage units. The PMS optimization is integrated with the sizing procedure of the hybrid system. The method is tested on a system with several widely used generators in off-grid systems, including wind turbines, PV panels, fuel cells, electrolyzers, hydrogen tanks, batteries, and diesel generators. The aim of the optimization problem is to simultaneously minimize the overall cost of the system, unmet load, and fuel emission considering the uncertainties associated with renewable energy sources (RES). These uncertainties are modeled by using various possible scenarios for wind speed and solar irradiation based on Weibull and Beta probability distribution functions (PDF), respectively. The differential evolution algorithm (DEA) accompanied with fuzzy technique is used to handle the mixed-integer nonlinear multi-objective optimization problem. The optimum solution, including design parameters of system components and the monthly PMS parameters adapting climatic changes during a year, are obtained. Considering operating limitations of system devices, the parameters characterize the priority and share of each storage component for serving the deficit energy or storing surplus energy both resulted from the mismatch of power between load and generation. In order to have efficient power exploitation from RES, the optimum monthly tilt angles of PV panels and the optimum tower height for wind turbines are calculated. Numerical results are compared with the results of optimal sizing assuming pre-defined PMS without using the proposed power management optimization method. The comparative results present the efficacy and capability of the proposed method for hybrid energy systems.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:rensus:v:16:y:2012:i:3:p:1577-1587
    DOI: 10.1016/j.rser.2011.11.030
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032111005764
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2011.11.030?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. Kashefi Kaviani, A. & Riahy, G.H. & Kouhsari, SH.M., 2009. "Optimal design of a reliable hydrogen-based stand-alone wind/PV generating system, considering component outages," Renewable Energy, Elsevier, vol. 34(11), pages 2380-2390.
    2. Mondol, Jayanta Deb & Yohanis, Yigzaw G. & Norton, Brian, 2007. "The impact of array inclination and orientation on the performance of a grid-connected photovoltaic system," Renewable Energy, Elsevier, vol. 32(1), pages 118-140.
    3. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
    4. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
    5. Garcia, Raquel S. & Weisser, Daniel, 2006. "A wind–diesel system with hydrogen storage: Joint optimisation of design and dispatch," Renewable Energy, Elsevier, vol. 31(14), pages 2296-2320.
    6. Dufo-López, Rodolfo & Bernal-Agustín, José L. & Contreras, Javier, 2007. "Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage," Renewable Energy, Elsevier, vol. 32(7), pages 1102-1126.
    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. Zghal, Wissem & Kantchev, Gueorgui & Kchaou, Hédi, 2011. "Optimization and management of the energy produced by a wind energizing system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 1080-1088, February.
    9. Mostafaeipour, A. & Sedaghat, A. & Dehghan-Niri, A.A. & Kalantar, V., 2011. "Wind energy feasibility study for city of Shahrbabak in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2545-2556, August.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. Maleki, Akbar & Ameri, Mehran & Keynia, Farshid, 2015. "Scrutiny of multifarious particle swarm optimization for finding the optimal size of a PV/wind/battery hybrid system," Renewable Energy, Elsevier, vol. 80(C), pages 552-563.
    4. Yuichiro Yoshida & Hooman Farzaneh, 2020. "Optimal Design of a Stand-Alone Residential Hybrid Microgrid System for Enhancing Renewable Energy Deployment in Japan," Energies, MDPI, vol. 13(7), pages 1-18, April.
    5. 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.
    6. 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.
    7. 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.
    8. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
    9. Hadidian Moghaddam, Mohammad Jafar & Kalam, Akhtar & Nowdeh, Saber Arabi & Ahmadi, Abdollah & Babanezhad, Manoochehr & Saha, Sajeeb, 2019. "Optimal sizing and energy management of stand-alone hybrid photovoltaic/wind system based on hydrogen storage considering LOEE and LOLE reliability indices using flower pollination algorithm," Renewable Energy, Elsevier, vol. 135(C), pages 1412-1434.
    10. Pérez-Navarro, A. & Alfonso, D. & Álvarez, C. & Ibáñez, F. & Sánchez, C. & Segura, I., 2010. "Hybrid biomass-wind power plant for reliable energy generation," Renewable Energy, Elsevier, vol. 35(7), pages 1436-1443.
    11. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    12. Nasiri, Reza & Radan, Ahmad, 2011. "Adaptive decoupled control of 4-leg voltage-source inverters for standalone photovoltaic systems: Adjusting transient state response," Renewable Energy, Elsevier, vol. 36(10), pages 2733-2741.
    13. Fux, Samuel F. & Benz, Michael J. & Guzzella, Lino, 2013. "Economic and environmental aspects of the component sizing for a stand-alone building energy system: A case study," Renewable Energy, Elsevier, vol. 55(C), pages 438-447.
    14. Nithya Saiprasad & Akhtar Kalam & Aladin Zayegh, 2019. "Triple Bottom Line Analysis and Optimum Sizing of Renewable Energy Using Improved Hybrid Optimization Employing the Genetic Algorithm: A Case Study from India," Energies, MDPI, vol. 12(3), pages 1-23, January.
    15. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    16. Allman, Andrew & Daoutidis, Prodromos, 2017. "Optimal design of synergistic distributed renewable fuel and power systems," Renewable Energy, Elsevier, vol. 100(C), pages 78-89.
    17. Bernal-Agustín, José L. & Dufo-López, Rodolfo, 2009. "Simulation and optimization of stand-alone hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 2111-2118, October.
    18. Gharavi, H. & Ardehali, M.M. & Ghanbari-Tichi, S., 2015. "Imperial competitive algorithm optimization of fuzzy multi-objective design of a hybrid green power system with considerations for economics, reliability, and environmental emissions," Renewable Energy, Elsevier, vol. 78(C), pages 427-437.
    19. Nasiri, Reza & Radan, Ahmad, 2011. "Pole-placement control of 4-leg voltage-source inverters for standalone photovoltaic systems: Considering digital delays," Renewable Energy, Elsevier, vol. 36(2), pages 858-865.
    20. Khan, Muhammad Waseem & Wang, Jie, 2017. "The research on multi-agent system for microgrid control and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1399-1411.

    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:rensus:v:16:y:2012:i:3:p:1577-1587. 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.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.