Optimal Allocation of Wind Turbines in Active Distribution Networks by Using Multi-Period Optimal Power Flow and Genetic Algorithms

  • P. Siano
  • P. Chen
  • Z. Chen
  • A. Piccolo
Chapter
Part of the Green Energy and Technology book series (GREEN)

Abstract

In order to achieve an effective reduction of greenhouse gas emissions, the future electrical distribution networks will need to accommodate higher amount of renewable energy based distributed generation such as Wind Turbines.

This will require a re-evaluation and most likely a revision of traditional methodologies, so that they can be used for the planning and management of future electrical distribution networks. Such networks evolve from the current passive systems to active networks and smart grids, managed through systems based on Information Communication Technology.

This chapter proposes a hybrid optimization method that aims at maximizing the Net Present Value related to the investment made by Wind Turbines developers in an active distribution network. The proposed method combines a Genetic Algorithm with a multi-period optimal power flow.

The method, integrating active management schemes such as coordinated voltage control, energy curtailment and power factor control is demonstrated on a 69-bus 11 kV radial distribution network.

Keywords

Wind Turbine Reactive Power Distribution Network Wind Energy Smart Grid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. 1.
    Ault, G.W., Currie, R.A.F., McDonald, J.R.: Active Power Flow Management Solutions for Maximising DG Connection Capacity. In: Proc. of IEEE Power Eng. Society General Meeting, pp. 1–5 (2006)Google Scholar
  2. 2.
    Boutsika, T.N., Papathanassiou, S.A.: Shortcircuit calculations in networks with distributed generation. Electric Power Systems Research 78, 1181–1191 (2008)CrossRefGoogle Scholar
  3. 3.
    Celli, G., Ghiani, E., Mocci, S., Pilo, F.: A multiobjective evolutionary algorithm for the sizing and siting of distributed generation. IEEE Trans. Power Systems 20(2), 750–757 (2005a)CrossRefGoogle Scholar
  4. 4.
    Celli, G., Pilo, F., Pisano, G., Soma, G.G.: Optimal participation of a microgrid to the energy market with an intelligent EMS. In: Proc. of the 7th International Power Engineering Conference, vol. 2, pp. 663–668 (2005b)Google Scholar
  5. 5.
    Currie, R.A.F., Ault, G.W., Foote, C.E.T., Burt, G.M., McDonald, J.R.: Fundamental research challenges for active management of distribution networks with high levels of renewable generation. In: Proc. of 39th Int. Universities Power Eng. Conf., vol. 2, pp. 1024–1028 (2004)Google Scholar
  6. 6.
    Currie, R.A.F., Ault, G.W., Foote, C.E.T., McDonald, J.R.: Active power-flow management utilising operating margins for the increased connection of distributed generation. IET Generation, Transmission & Distribution 1(1), 197–202 (2007)CrossRefGoogle Scholar
  7. 7.
    Das, D.: A Fuzzy Multiobjective Approach for Network Reconfiguration of Distribution Systems. IEEE Trans. Power Delivery 21(1), 202–209 (2006)CrossRefGoogle Scholar
  8. 8.
    Djapic, P., Ramsay, C., Pudjianto, D., Strbac, G., Mutale, J., Jenkins, N., Allan, R.: Taking an active approach. IEEE Pow. & Energy Magazine 5(4), 68–77 (2007)CrossRefGoogle Scholar
  9. 9.
    Dugan, R., Wacławiak, M.: Using energy as a measure of risk in distribution planning. In: Proc. of 19th Int. Conf. on Electricity Distribution, pp. 1–4 (2007)Google Scholar
  10. 10.
    El-Khaltam, W., Bhattacharya, K., Hegazy, Y., Salama, M.M.A.: Optimal investment planning for distributed generation in a competitive electricity market. IEEE Trans. Power Systems 19(3), 1674–1684 (2004)CrossRefGoogle Scholar
  11. 11.
    European Commission, EUR 22040: European Technology Platform SmartGrids, Office for Official Publications of the European Communities (2006) Google Scholar
  12. 12.
    Harrison, G.P., Wallace, A.R.: Optimal power flow evaluation of distribution network capacity for the connection of distributed generation. IEE Proceedings Generation, Transmission & Distribution 152(1), 115–122 (2005)CrossRefGoogle Scholar
  13. 13.
    Harrison, G., Piccolo, A., Siano, P., Wallace, A.R.: Exploring the Trade-offs Between Incentives for Distributed Generation Developers and DNOs. IEEE Trans. on Power Systems 22, 821–828 (2007b)CrossRefGoogle Scholar
  14. 14.
    Harrison, G.P., Piccolo, A., Siano, P., Wallace, A.R.: Hybrid GA and OPF evaluation of network capacity for distributed generation connections. Electrical Power Systems Research 78, 392–398 (2008)CrossRefGoogle Scholar
  15. 15.
    Harrison, G.P., Piccolo, A., Siano, P., Wallace, A.R.: Distributed Generation Capacity Evaluation Using Combined Genetic Algorithm and OPF. International Journal of Emerging Electric Power Systems 8, 1–13 (2007a)CrossRefGoogle Scholar
  16. 16.
    IEC 60909-1: Short-circuit currents in three-phase a.c. systems—Part 1:factors for the calculation of short-circuit currents according to IEC 60909-0 (2002) Google Scholar
  17. 17.
    IEC 60909-2: Electrical equipment—Data for short-circuit current calculations in accordance with IEC 909 (1992) Google Scholar
  18. 18.
    IEC 60909-3: Short-circuit currents in three-phase a.c. systems—Part 3: currents during two separate simultaneous line-to-earth short circuits and partial short-circuit currents flowing through earth (2003) Google Scholar
  19. 19.
    IEC 60909-4 : Short-circuit currents in three-phase a.c. systems—Part 4:examples for the calculation of short-circuit currents (2000) Google Scholar
  20. 20.
    Keane, A., O’Malley, M.: Optimal Allocation of Embedded Generation on Distribution Networks. IEEE Trans. Power Systems 20(3), 1640–1646 (2005)CrossRefGoogle Scholar
  21. 21.
    Keane, A., O’Malley, M.: Optimal Utilization of Distribution Networks for Energy Harvesting. IEEE Trans. on Power Systems 22(1), 467–475 (2007)CrossRefGoogle Scholar
  22. 22.
    Kim, K.H., Lee, Y.J., Rhee, S.B., Lee, S.K., You, S.K.: Dispersed generator placement using fuzzy-GA in distribution systems. In: Proc. of IEEE PES Summer Meeting, Chicago, USA, pp. 1148–1153 (2002)Google Scholar
  23. 23.
    Kuri, B., Redfern, M., Li, F.: Optimization of rating and positioning of dispersed generation with minimum network disruption. In: Proc. of IEEE Power Eng. Soc. Gen. Meeting, Denver, CO, pp. 2074–2078 (2004)Google Scholar
  24. 24.
    Liew, S.N., Strbac, G.: Maximising penetration of wind generation in existing distribution networks. In: Proc. of IEE Proc. Generation, Transmission and Distribution, vol. 149, pp. 256–262 (2002)Google Scholar
  25. 25.
    Masters, C.L.: Voltage rise: The big issue when connecting embedded generation to long 11 kV overhead lines. Power Eng. J. 16(1), 5–12 (2002)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Mutale, J.: Benefits of Active Management of Distribution Networks with Distributed Generation. In: Proc. of Power Systems Conf. and Exp., pp. 601–606 (2006)Google Scholar
  27. 27.
    Nara, K., Hayashi, Y., Ikeda, K., Ashizawa, T.: Application of tabu search to optimal placement of distributed generators. In: Proc. of IEEE PES Winter Meeting, pp. 918–923 (2001)Google Scholar
  28. 28.
    Ochoa, L.F., Dent, C.J., Harrison, G.P.: Maximisation of intermittent distributed generation in active networks. In: Proc. of IET-CIRED Seminar SmartGrids for Distribution, pp. 1–4 (2008)Google Scholar
  29. 29.
    Ochoa, L.F., Keane, A., Dent, C., Harrison, G.P.: Applying active network management schemes to an Irish distribution network for wind power maximisation. In: Proc. of Int. Conf. on Electricity Distribution, pp. 1–4 (2009)Google Scholar
  30. 30.
    Piccolo, A., Siano, P.: Evaluating the Impact of Network Investment Deferral on Distributed Generation Expansion. IEEE Trans. Power Systems 24(3), 1559–1567 (2009)CrossRefGoogle Scholar
  31. 31.
    Prica, M., Ilic, M.D.: Optimal Distribution Service Pricing for Investment Planning. In: Proc. of IEEE PES General Meeting, Tampa (Florida, USA), pp. 1–7 (2007)Google Scholar
  32. 32.
    Pudjianto, D., Castro, M., Djapic, P., Stojkovska, B., Strbac, G., Allan, R.N.: Transmission Investment and Pricing in Systems with Significant Penetration of Wind Generation. In: Proc. of IEEE Power Engineering Society General Meeting, pp. 1–3 (2007)Google Scholar
  33. 33.
    Rau, N.S., Wan, Y.H.: Optimum location of resources in distributed planning. IEEE Trans. Power Systems 9(4), 2014–2020 (1994)CrossRefGoogle Scholar
  34. 34.
    Roberts, V., Collinson, A., Beddoes, A.: Active networks for the accommodation of dispersed generation. In: Proc. of 2003 CIRED Conf., pp. 1–6 (2003)Google Scholar
  35. 35.
    Samotyj, M., Howe, B.: Creating Tomorrow’s Intelligent Electric Power Delivery System. In: Proc. of 2005 CIRED Conf., pp. 1–5 (2005)Google Scholar
  36. 36.
    Schwaegerl, C., Bollen, M.H.J., Karoui, K., Yagmur, A.: Voltage control in distribution systems as a limitation of the hosting capacity for distributed energy resources. In: Proc. of 18th Int. Conf. on Electricity Distribution, pp. 1–5 (2005)Google Scholar
  37. 37.
    Shafiu, A., Bopp, T., Chilvers, I., Strbac, G.: Active management and protection of distribution networks with distributed generation. In: Proc. of IEEE Power Eng. Society General Meeting, vol. 1, pp. 1098–1103 (2004)Google Scholar
  38. 38.
    Shafiu, A., Jenkins, N., Strbac, G.: Measurement location for state estimation of distribution networks with generation. IEE Proc. Gen., Trans. and Distr. 152, 240–246 (2005)CrossRefGoogle Scholar
  39. 39.
    Siano, P., Ochoa, L.F., Harrison, G.P., Piccolo, A.: Assessing the strategic benefits of distributed generation ownership for DNOs. IET Generation, Transmission & Distribution 3(3), 225–236 (2009)CrossRefGoogle Scholar
  40. 40.
    SUSTELNET. Review of technical options and constraints for integration of Distributed Generation in electricity networks (2003), http://www.sustelnet.net
  41. 41.
    Strbac, G., Jenkins, N., Hird, M., Djapic, P., Nicholson, G.: Integration of operation of embedded generation and distribution networks. Technical Report (2002)Google Scholar
  42. 42.
    Tsili, M., Papathanassiou, S.: A review of grid code technical requirements for wind farms. IET Renewable Power Generation 3(3), 308–332 (2009)CrossRefGoogle Scholar
  43. 43.
    Vovos, P.N., Harrison, G.P., Wallace, A.R., Bialek, J.W.: Optimal Power Flow as a tool for fault level constrained network capacity analysis. IEEE Trans. Power Systems 20(2), 734–741 (2005)CrossRefGoogle Scholar
  44. 44.
    Vovos, P.N., Bialek, J.W.: Direct incorporation of fault level constraints in optimal power flow as a tool for network capacity analysis. IEEE Trans. Power Systems 20(4), 2125–2134 (2005)CrossRefGoogle Scholar
  45. 45.
    Vovos, P.N., Kiprakis, A.E., Wallace, A.R., Harrison, G.P.: Centralised and Distributed Voltage Control: Impact on Distributed Generation Penetration. IEEE Trans. Power Systems 22(1), 476–483 (2007)CrossRefGoogle Scholar
  46. 46.
    Zhang, J., Cheng, H., Wang, C., Xia, Y., Shen, X., Yu, J.: Quantitive assessment of active management of distribution network with distributed generation. In: Proc. of Third Int. Conf. on Electric Utility Deregulation and Restructuring and Power Technologies, pp. 2519–2524 (2008)Google Scholar
  47. 47.
    Zhang, J., Cheng, H., Wanga, C.: Technical and economic impacts of active management on distribution network. Electrical Power and Energy Systems 31, 130–138 (2009)CrossRefGoogle Scholar
  48. 48.
    Zimmerman, R.D., Gan, D.: MATPOWER – A MATLAB Power System Simulation Package, User’s Manual, School of Electrical Engineering, Cornell University (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • P. Siano
    • 1
  • P. Chen
    • 2
  • Z. Chen
    • 2
  • A. Piccolo
    • 1
  1. 1.Department of Industrial EngineeringUniversity of SalernoFiscianoItaly
  2. 2.Department of Energy TechnologyAalborg UniversityAalborgDenmark

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