Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Optimal operation of distributed generations in micro-grids under uncertainties in load and renewable power generation using heuristic algorithm

Microgrid (MG) could allow renewable and clean resources to penetrate into a controllable utility and achieve maximum utilisation of existing energy and demand-side management. This study proposes a new paradigm for distribution system operation considering MG conception. This study is focused on probabilistic analysis of optimal power dispatch considering economic aspects in MGs environment with technical constraints. In this study the economic operation of small scale energy zones is formulated and solved as an optimisation problem. A typical MG consists wind turbine (WT), photo voltaic (PV), micro turbine, fuel cell, combined heat and power and electric loads. Fluctuation behaviour of loads and generated power by WTs and PVs are caused complexity in proposed problem. Cost function includes generated powers by units, power transaction between MGs and main grid, operation and maintenance cost of resources and cost of pollutants emission. Considering MG concept in smart grids, the balance between supply-demand is secured through power exchanging between MGs and main grid, so that the value of objective function be minimised. The imperialist competitive algorithm is applied to solve proposed problem and obtained results are compared with Monte Carlo simulation method.

References

    1. 1)
      • 23. Xi, W., Xiaoyan, Q., Runzhou, J., Dan, L., Gang, W., Qian, L.: ‘Clustering power systems strategy the future of distributed generation’. Proc. IEEE. Power System Technology, Chengdu, 2014, pp. 17121716.
    2. 2)
    3. 3)
      • 10. Wang, Z., Chen, B., Wang, J., Begovic, M.M., Chen, C.: ‘Coordinated energy management of networked microgrids in distribution systems’. Accepted for IEEE Trans. Smart Grid..
    4. 4)
    5. 5)
    6. 6)
      • 27. Seppala, A.: ‘Load research and load estimation in electricity distribution’. PhD thesis, Helsinki University of Technology, 1996.
    7. 7)
    8. 8)
      • 16. Sortomme, E., El-Sharkawi, M.A.: ‘Optimal power flow for a system of microgrids with controllable loads and battery storage’. IEEE/PES Power Systems Conf. and Exposition, Seattle, WA, 2009, pp. 15.
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
      • 22. Wirasanti, P., Ortjohann, E., Schmelter, A., Morton, D.: ‘Clustering power systems strategy the future of distributed generation’. Proc. IEEE. Power Electronics, Electrical Drives, Automation and Motion Symp., Sorrento, 2012, pp. 679683.
    15. 15)
    16. 16)
    17. 17)
    18. 18)
      • 19. Kargarian, A., Falahati, B., Yong Fu Baradar, : ‘Multiobjective optimal power flow algorithm to enhance multi-microgrids performance incorporating IPFC’. Proc. IEEE. Power and Energy Society General Meeting, San Diego, 2012, pp. 16.
    19. 19)
    20. 20)
    21. 21)
    22. 22)
    23. 23)
    24. 24)
    25. 25)
      • 5. Bertani, A., Borghetti, A., Bossi, C., et al: ‘Management of low voltage grids with high penetration of distributed generation: Concepts, implementations and experiments’. Presented at the 2007 CIGRE, Paris, France, 2006, pp. 113.
    26. 26)
      • 30. Atashpaz, E., Lucas, C.: ‘Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition’. Proc. IEEE. Congress on Evolutionary Computation, Singapore, 2007, pp. 46614667.
    27. 27)
      • 28. Chen, J., Yang, X., Zhu, L., Zhang, M.: ‘Microgrid economic operation and research on dispatch strategy’. Proc. Power Engineering and Automation Conf. (PEAM), Wuhan, 2012, pp. 16.
    28. 28)
    29. 29)
    30. 30)
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-rpg.2014.0357
Loading

Related content

content/journals/10.1049/iet-rpg.2014.0357
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address