access icon free Comparative analysis of design criteria for hybrid photovoltaic/wind/battery systems

Reliability analyses are essential for the design of hybrid photovoltaic/wind/battery systems. The selection of design criteria is an important task and has to ensure proper reliability and optimal configuration. In the literature, loss of power supply probability (LPSP) and loss of load hours (LOLH) are the most common reliability criteria used for this matter. This study presents a comparative analysis on LPSP and LOLH design criteria based on a Monte Carlo simulation, taking into consideration uncertainties in the variables involved in the design process. Moreover, two new statistical design criteria are proposed, aiming to avoid over-sizing of the optimal configuration. According to the obtained results, LOLH is a stricter design criterion compared with LPSP, leading to a more reliable energy system. In addition, the optimal configuration selected by using the proposed statistical design criteria showed better performance when compared with the solution based on LPSP or LOLH.

Inspec keywords: Monte Carlo methods; hybrid power systems; power generation reliability

Other keywords: energy system; hybrid photovoltaic-wind-battery systems; reliability analyses; LOLH design criteria; Monte Carlo simulation; design process; reliability; statistical design criteria; loss of power supply probability; LPSP design criteria; loss of load hours; comparative analysis; design criteria; optimal configuration

Subjects: Wind power plants; Solar power stations and photovoltaic power systems; Monte Carlo methods; Secondary cells; Reliability

References

    1. 1)
      • 22. Yang, H., Lu, L., Zhou, W.: ‘A novel optimization sizing model for hybrid solar-wind power generation system’, Sol. Energy, 2007, 81, (1), pp. 7684.
    2. 2)
      • 1. Bhandari, B., Lee, K.-T., Lee, G.-Y., et al: ‘Optimization of hybrid renewable energy power systems: a review’, Int. J. Precis. Eng. Manuf. Technol., 2015, 2, (1), pp. 99112.
    3. 3)
      • 17. Nikhil, P.G., Subhakar, D.: ‘Approaches for developing a regression model for sizing a stand-alone photovoltaic system’, IEEE J. Photovolt., 2015, 5, (1), pp. 250257.
    4. 4)
      • 27. Bilal, B.O., Sambou, V., Ndiaye, P.A., et al: ‘Multi-objective design of PV-wind-batteries hybrid systems by minimizing the annualized cost system and the loss of power supply probability (LPSP)’. 2013 IEEE Int. Conf. on Industrial Technology (ICIT), 2013, pp. 861868.
    5. 5)
      • 2. Mahmoud, M.S., Sunni, F.M.A.L., Saif Ur Rahman, M.: ‘Review of microgrid architectures – a system of systems perspective’, IET Renew. Power Gener., 2015, 9, (8), pp. 10641078.
    6. 6)
      • 19. Kandil, M., Saadawi, M., Saeed, M., et al: ‘Modified particle swarm optimisation technique for optimal design of small renewable energy system supplying a specific load at Mansoura University’, IET Renew. Power Gener., 2015, 9, (5), pp. 474483.
    7. 7)
      • 23. Upadhyay, S., Sharma, M.P.: ‘A review on configurations, control and sizing methodologies of hybrid energy systems’, Renew. Sustain. Energy Rev., 2014, 38, pp. 4763.
    8. 8)
      • 21. Tremblay, O., Dessaint, L., Dekkiche, A.: ‘A generic battery model for the dynamic simulation of hybrid electric vehicles’. 2007 IEEE Vehicle Power and Propulsion Conf., 2007, no. V, pp. 284289.
    9. 9)
      • 20. Cai, W., Ren, H., Jiao, Y., et al: ‘Analysis and simulation for grid-connected photovoltaic system based on MATLAB’. 2011 Int. Conf. on Electrical and Control Engineering, 2011, no. 1, pp. 6366.
    10. 10)
      • 3. Sinha, S., Chandel, S.S.: ‘Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems’, Renew. Sustain. Energy Rev., 2015, 50, pp. 755769.
    11. 11)
      • 6. Diaf, S., Diaf, D., Belhamel, M., et al: ‘A methodology for optimal sizing of autonomous hybrid PV/wind system’, Energy Policy, 2007, 35, (11), pp. 57085718.
    12. 12)
      • 12. Rangnekar, S., Khare, A., Mittal, A., et al: ‘Sizing and performance analysis of standalone wind-photovoltaic based hybrid energy system using ant colony optimisation’, IET Renew. Power Gener., 2016, 10, (7), pp. 964972.
    13. 13)
      • 25. Luna-Rubio, R., Trejo-Perea, M., Vargas-Vázquez, D., et al: ‘Optimal sizing of renewable hybrids energy systems: a review of methodologies’, Sol. Energy, 2012, 86, (4), pp. 10771088.
    14. 14)
      • 14. Askarzadeh, A., dos Santos Coelho, L.: ‘A novel framework for optimization of a grid independent hybrid renewable energy system: a case study of Iran’, Sol. Energy, 2015, 112, pp. 383396.
    15. 15)
      • 10. Khare, A., Rangnekar, S.: ‘Optimal sizing of a grid integrated solar photovoltaic system’, IET Renew. Power Gener., 2014, 8, (1), pp. 6775.
    16. 16)
      • 4. Chauhan, A., Saini, R.P.: ‘A review on integrated renewable energy system based power generation for stand-alone applications: configurations, storage options, sizing methodologies and control’, Renew. Sustain. Energy Rev., 2014, 38, pp. 99120.
    17. 17)
      • 9. Martinez, A., Abbes, D., Champenois, G.: ‘Eco-design optimisation of an autonomous hybrid wind–photovoltaic system with battery storage’, IET Renew. Power Gener., 2012, 6, (5), pp. 358371.
    18. 18)
      • 18. Gursoy, G., Baysal, M.: ‘Improved optimal sizing of hybrid PV/wind/battery energy systems’. 2014 Int. Conf. on Renewable Energy Research and Application (ICRERA), 2014, pp. 713716.
    19. 19)
      • 15. Shrestha, G.B., Goel, L.: ‘A study on optimal sizing of stand-alone photovoltaic stations’, IEEE Trans. Energy Convers., 1998, 13, (4), pp. 373378.
    20. 20)
      • 26. Sansa, I., Villafafilla, R., Belaaj, N.M.: ‘Optimal sizing design of an isolated microgrid based on the compromise between the reliability system and the minimal cost’. 2015 16th Int. Conf. on Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2015, pp. 715721.
    21. 21)
      • 11. Zhao, B., Zhang, X., Li, P., et al: ‘Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island’, Appl. Energy, 2014, 113, pp. 16561666.
    22. 22)
      • 13. Yazdani, A., Bhuiyan, F.A., Primak, S.L.: ‘Optimal sizing approach for islanded microgrids’, IET Renew. Power Gener., 2015, 9, (2), pp. 166175.
    23. 23)
      • 29. Erdinc, O., Uzunoglu, M.: ‘Optimum design of hybrid renewable energy systems: overview of different approaches’, Renew. Sustain. Energy Rev., 2012, 16, (3), pp. 14121425.
    24. 24)
      • 16. Nikhil, P.G., Subhakar, D.: ‘Sizing and parametric analysis of a stand-alone photovoltaic power plant’, IEEE J. Photovolt., 2013, 3, (2), pp. 776784.
    25. 25)
      • 30. Ordóñez, G., Osma, G., Vergara, P., et al: ‘Wind and solar energy potential assessment for development of renewables energies applications in Bucaramanga, Colombia’. IOP Conf. Series: Materials Science Engineering, June 2014, vol. 59, p. 012004.
    26. 26)
      • 5. Zhou, W., Lou, C., Li, Z., et al: ‘Current status of research on optimum sizing of stand-alone hybrid solar–wind power generation systems’, Appl. Energy, 2010, 87, (2), pp. 380389.
    27. 27)
      • 24. Bernal-Agustín, J.L., Dufo-López, R.: ‘Simulation and optimization of stand-alone hybrid renewable energy systems’, Renew. Sustain. Energy Rev., 2009, 13, (8), pp. 21112118.
    28. 28)
      • 8. Xu, L., Ruan, X., Member, S., et al: ‘An improved optimal sizing method for wind-solar-battery hybrid power system’, IEEE Trans. Sustain. Energy, 2013, 4, (3), pp. 774785.
    29. 29)
      • 28. Cano, A., Jurado, F., Sánchez, H., et al: ‘Optimal sizing of stand-alone hybrid systems based on PV/WT/FC by using several methodologies’, J. Energy Inst., 2014, 87, (4), pp. 330340.
    30. 30)
      • 7. Diaf, S., Notton, G., Belhamel, M., et al: ‘Design and techno-economical optimization for hybrid PV/wind system under various meteorological conditions’, Appl. Energy, 2008, 85, (10), pp. 968987.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rpg.2016.0250
Loading

Related content

content/journals/10.1049/iet-rpg.2016.0250
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading