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Stochastic Power Management in Microgrid with Efficient Energy Storage

  • Itrat Fatima
  • Nadeem JavaidEmail author
  • Abdul Wahid
  • Zunaira Nadeem
  • Muqqadas Naz
  • Zahoor Ali Khan
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 17)

Abstract

In order to mitigate the extra cost and to reduce the energy consumption, distributive power system are widely accepted in recent years. The reason of adaptation of distributive power system is the scalability of power supply and demand which helps in reliable power supply and optimizes the annual expenditures. Moreover, the integration of power distributive systems with renewable energy sources enabled the optimal utilization of photovoltaic arrays for effective and cost efficient power supply. To exploit the integration of distributive power and renewable sources, we solve the power dispatch problem with heuristic optimization techniques. We have performed scheduling for supply side management. For this purpose, we have formulate our problem using chance constrained optimization and transformed the problem into mixed integer linear programming. Finally, simulation results demonstrate that the proposed scheduling method for microgrid performs efficiently and effectively.

Keywords

Smart grid Microgrid Renewable energy sources Supply side management Chance constrained optimization Mixed integer linear programming 

References

  1. 1.
    Motevasel, M., Seifi, A.R.: Expert energy management of a micro-grid considering wind energy uncertainty. Energy Convers. Manage. 83, 58–72 (2014)CrossRefGoogle Scholar
  2. 2.
    Davidović, T.: Bee colony optimization Part I: the algorithm overview. Yugoslav J. Oper. Res. 25(1) (2016)Google Scholar
  3. 3.
    Mohanty, B., Tripathy, S.: A teaching learning based optimization technique for optimal location and size of DG in distribution network. J. Electr. Syst. Inf. Technol. 3(1), 33–44 (2016)Google Scholar
  4. 4.
    Hasanpor Divshali, P., Choi, B.J.: Electrical market management considering power system constraints in smart distribution grids. Energies 9(6), 405 (2016)CrossRefGoogle Scholar
  5. 5.
    Varela Souto, A.: Optimization and Energy Management of a Microgrid Based on Frequency Communications (2016)Google Scholar
  6. 6.
    Naderipour, A., Mohd Zin, A.A., Habibuddin, M.H., Moradi, M., Miveh, M., Afrouzi, H.N.: A new compensation control strategy for grid-connected wind turbine and fuel cell inverters in a microgrid. Int. J. Power Electron. Drive Syst. (IJPEDS) 8(1), 272–278 (2017)CrossRefGoogle Scholar
  7. 7.
    Trivedi, I.N., Thesiya, D.K., Esmat, A., Jangir, P.: A multiple environment dispatch problem solution using ant colony optimization for micro-grids. In: International Conference on Power and Advanced Control Engineering (ICPACE), 2015, pp. 109–115. IEEE (2015)Google Scholar
  8. 8.
    Olivas, F., Valdez, F., Castillo, O., Gonzalez, C.I., Martinez, G., Melin, P.: Ant colony optimization with dynamic parameter adaptation based on interval type-2 fuzzy logic systems. Appl. Soft Comput. 53, 74–87 (2017)CrossRefGoogle Scholar
  9. 9.
    Li, X., Wang, Y., Wang, Z., Shu, X., Zhang, Y.: The open electrical and electronic engineering journal. Open Electr. Electron. Eng. J. 10, 46–57 (2016)CrossRefGoogle Scholar
  10. 10.
    Thirumalaisamy, B., Jegannathan, K.: A novel energy management scheme using ANFIS for independent microgrid. Int. J. Renew. Energy Res. (IJRER) 6(3), 735–746 (2016)Google Scholar
  11. 11.
    Lin, W.-M., Tu, C.-S., Tsai, M.-T.: Energy management strategy for MG by using enhanced bee colony optimization. Energies 9(1), 5 (2015)CrossRefGoogle Scholar
  12. 12.
    Huld, T., Moner-Girona, M., Kriston, A.: Geospatial analysis of photovoltaic mini-grid system performance. Energies 10(2), 218 (2017)CrossRefGoogle Scholar
  13. 13.
    Dehghanpour, E., Karegar, H., Kheirollahi, R., Soleymani, T.: Optimal coordination of directional overcurrent relays in microgrids by using cuckoo-linear optimization algorithm and fault current limiter. IEEE Trans. Smart Grid (2016)Google Scholar
  14. 14.
    Wang, J., Li, Y., Zhou, Y.: Interval number optimization for household load scheduling with uncertainty. Energy Buildings 130, 613–624 (2016)CrossRefGoogle Scholar
  15. 15.
    Moon, S., Lee, J.-W.: Multi-residential demand response scheduling with multi-class appliances in smart grid. IEEE Trans. Smart Grid (2016)Google Scholar
  16. 16.
    Dong, W., Li, Y., Xiang, J.: Optimal sizing of a stand-alone hybrid power system based on battery/hydrogen with an improved ant colony optimization. Energies 9(10), 785 (2016)CrossRefGoogle Scholar
  17. 17.
  18. 18.
  19. 19.
    World’s Largest Carbon Neutral Fuel Cell Power Plant, 16 October 2012. Accessed 21 Oct 2017Google Scholar
  20. 20.
    Zachar, M., Daoutidis, P.: Microgrid/Macrogrid energy exchange: a novel market structure and stochastic scheduling. IEEE Trans. Smart Grid 8(1), 178–189 (2017)CrossRefGoogle Scholar
  21. 21.
  22. 22.
  23. 23.
    Roy, K., Mandal, K.K., Mandal, A.C.: Modeling and managing of MG connected system using improved artificial bee colony algorithm. Int. J. Electr. Power Energy Syst. 75, 50–58 (2016)CrossRefGoogle Scholar
  24. 24.
    Cheng, Y.-S., Chuang, M.-T., Liu, Y.-H., Wang, S.-C., Yang, Z.-Z.: A particle swarm optimization based power dispatch algorithm with roulette wheel re-distribution mechanism for equality constraint. Renew. Energy 88, 58–72 (2016)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Itrat Fatima
    • 1
  • Nadeem Javaid
    • 1
    Email author
  • Abdul Wahid
    • 1
  • Zunaira Nadeem
    • 3
  • Muqqadas Naz
    • 1
  • Zahoor Ali Khan
    • 2
  1. 1.Department of Computer ScienceCOMSATS Institute of Information TechnologyIslamabadPakistan
  2. 2.Internetworking Program, Faculty of EngineeringDalhousie UniversityHalifaxCanada
  3. 3.National University of Science and TechnologyIslamabadPakistan

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