Optimal Operation of Microgrids Containing Tidal Barrage with Hydro-Pumps

Document Type : Research paper

Authors

1 Department of Electrical Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran

2 Department of Electrical Engineering, Dariun Branch, Islamic Azad University, Dariun, Iran

Abstract

For providing required load in n coastal and island regions, tidal barrage can be integrated in microgrids. To produce electricity from tides, in tidal barrage, water is moved between sea and reservoir through sluices containing turbines to generate electricity. In operation phase, produced power of tidal barrages depends on number of turbines, sluices and hydro-pumps. Thus, to maximize generated energy of tidal barrage, optimum number of turbines, sluices and hydro-pumps can be obtained through heuristic optimization techniques. Because of tidal level variation, generated power of tidal barrages changes over time. Thus, for load supplying, other renewable resources such as photovoltaic units, batteries, fuel-based generation units and grid-connected mode of microgrid are utilized. In this research, two-stage optimal operation of microgrids composed of tidal barrage, photovoltaic units, batteries and fuel-based generation units is done. In first stage, optimum number of turbines, sluices and hydro-pumps related to tidal barrage is determined for maximizing produced energy of tidal unit during time horizon of the study. In second stage, remaining load of microgrid is provided by photovoltaic units, batteries, fuel-based generation units and main network. To this end, generated power of fuel-based plants and power exchanged between microgrid and main grid are determined for minimizing operating cost of microgrid. The operating cost including operating cost of fuel-based generation units, cost of exchanged power between main grid and microgrid and penalties of load curtailment is optimized using particle swarm optimization method. Numerical results presents among different optimization algorithms, particle swarm method has performed best in operation studies of tidal barrage. For understudied microgrid, maximum generated energy of tidal barrage is 25.052 MWh, and minimum operating cost of the microgrid is 39868 $.

Keywords

References

  1. Sufyan, N. Abd Rahim, C. Tan, M.A. Muhammad, and S.R. Sheikh Raihan, “Optimal sizing and energy scheduling of isolated microgrid considering the battery lifetime degradation,” PloS one, vol. 14, no. 2, p. e0211642, 2019.
  2. Javidsharifi, T. Niknam, J. Aghaei, and G. Mokryani, “Multi-objective short-term scheduling of a renewable-based microgrid in the presence of tidal resources and storage devices,” Appl. Energy, vol. 216, pp. 367–381, 2018.
  3. Krishnan, L.P. M.I. Sampath, F. Eddy, and H.B. Gooi, “Optimal scheduling of a microgrid including pump scheduling and network constraints,” Complexity, vol. 2018, 2018.
  4. Yang, X. Feng, and Z. Li, “Advanced microgrid energy management system for future sustainable and resilient power grid,” IEEE Trans. Ind. Appl., vol. 55, no. 6, pp. 7251–7260, 2019.
  5. Lahon, C.P. Gupta, and E. Fernandez, “Optimal power scheduling of cooperative microgrids in electricity market environment,” IEEE Trans. Industr. Inform., vol. 15, no. 7, pp. 4152–4163, 2018.
  6. Zhang, L. Guo, H. Zhang, L. Guo, K. Feng, and J. Lin, “An energy scheduling strategy with priority within islanded microgrids,” IEEE Access, vol. 7, pp. 135896–135908, 2019.
  7. Farzan, M.A. Jafari, R. Masiello, and Y. Lu, “Toward optimal day-ahead scheduling and operation control of microgrids under uncertainty,” IEEE Trans. Smart Grid, vol. 6, no. 2, pp. 499–507, 2014.
  8. Ghaedi and H. Gorginpour, “Generated power enhancement of the barrage type tidal power plants,” Ocean Eng., vol. 226, p. 108787, 2021.
  9. P. Neill, A. Angeloudis, P. E. Robins, I. Walkington, S. L. Ward, I. Masters, M. J. Lewis, M. Piano, A. Avdis, M. D. Piggott, et al., “Tidal range energy resource and optimization–past perspectives and future challenges,” Renew. Energ., vol. 127, pp. 763–778, 2018.
  10. Angeloudis, S.C. Kramer, A. Avdis, and M.D. Piggott, “Optimising tidal range power plant operation,” Appl. Energy, vol. 212, pp. 680–690, 2018.
  11. Zafar, A. E. Nezhad, A. Ahmadi, T. Erfani, and R. Erfani, “Trading off environmental and economic scheduling of a renewable energy based microgrid under uncertainties,” IEEE Access, vol. 11, pp. 459–475, 2022.
  12. P. Yuan, P. Li, Z.L. Li, and J. Xia, “Data-driven riskadjusted robust energy management for microgrids integrating demand response aggregator and renewable energies,” IEEE Trans. Smart Grid, vol. 14, no. 1, pp. 365–377, 2022.
  13. Peres, “Probabilistic optimal power flow for balanced islanded microgrids,” IEEE Lat. Am. Trans., vol. 21, no. 1, pp. 167–174, 2023.
  14. N. Liu and G.H. Yang, “Distributed fixed-time optimal resource management for microgrids,” IEEE Trans. Autom. Sci. Eng., 2022.
  15. R. Negahdari, A. Ghaedi, M. Nafar, and M. Simab, “Optimal operation of basin-based tidal units equipped with hydro-pumps,” J. Eng., vol. 2023, no. 2, p. e12225, 2023.
  16. Naderi, A. Dejamkhooy, S. Seyedshenava, and H. Shayeghi, “Milp based optimal design of hybrid microgrid by considering statistical wind estimation and demand response,” J. Oper. Autom. Power Eng., vol. 10, no. 1, pp. 54–65, 2022.
  17. Shayeghi and M. Alilou, “Multi-objective demand side management to improve economic and environmental issues of a smart microgrid,” J. Oper. Autom. Power Eng., vol. 9, no. 3, pp. 182–192, 2021.
  18. Aghajani and I. Heydari, “Energy management in microgrids containing electric vehicles and renewable energy sources considering demand response,” J. Oper. Autom. Power Eng., vol. 9, no. 1, pp. 34–48, 2021.
  19. Mirzadeh, M. Simab, and A. Ghaedi, “Reliability modeling of reservoir-based tidal power plants for determination of spinning reserve in renewable energy-based power systems,” Electr. Power Compon. Syst., vol. 47, no. 16-17, pp. 1534– 1550, 2019.
  20. Ghaedi, A. Abbaspour, M. Fotuhi-Friuzabad, and M. Parvania, “Incorporating large photovoltaic farms in power generation system adequacy assessment,” Sci. Iran., vol. 21, no. 3, pp. 924–934, 2014.
  21. Abunima and J. Teh, “Reliability modeling of pv systems based on time-varying failure rates,” IEEE Access, vol. 8, pp. 14367–14376, 2020.
  22. https://www.omie.es/en/market-resultts/daily/dailymarket/daily-hourly price
Journal of Operation and Automation in Power Engineering
Volume 13, Issue 1
January 2025
Pages 28-37

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History

  • Receive Date: 23 October 2022
  • Revise Date: 19 February 2023
  • Accept Date: 30 May 2023
  • First Publish Date: 20 August 2023

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