Modelling of an integrated gas and\ud electricity network with significant\ud wind capacity

Doctoral thesis English OPEN
Qadrdan, Meysam
  • Subject: TK
    arxiv: Physics::Atmospheric and Oceanic Physics

The large scale integration of wind generation capacity into an electricity\ud network poses technical as well as economic challenges. In this research,\ud three major challenges introduced by wind including non-correlated power\ud output from geographically dispersed wind farms, wind variability and wind\ud uncertainty were studied. In order to address each of the aforementioned\ud challenges an appropriate modelling approach and case studies were used.\ud The impacts of power output from dispersed wind farms on the Great Britain\ud transmission reinforcement were studied using an optimal DC load flow combined\ud with a power generation model. It was shown that Western and\ud Eastern HVDC links play a crucial role to bypass the Scotland to England\ud transmission bottleneck.\ud The impacts of wind variability on the GB gas and electricity network were\ud investigated through application of the Combined gas and Electricity Network\ud (CGEN) Model. Additional gas storage capacity was shown to be an\ud efficient option to compensate for wind variability.\ud Two-stage and multi-stage stochastic programming models were developed\ud to examine the impact of wind forecast uncertainty on the GB electricity and\ud gas networks. Stochastic modelling approaches were shown to be efficient\ud methods for scheduling and operating the system under wind uncertainty.\ud The key contributions of this thesis are the investigation of the impacts of\ud wind generation variability on the gas network, and development of twostage\ud and multi-stage stochastic programming models of integrated gas and\ud electricity network.
  • References (9)

    [14] R. Rubio, D. Ojeda-Esteybar, O. Ano, and A. Vargas. Integrated natural gas and electricity market: A survey of the state of the art in operation planning and market issues. In Transmission and Distribution Conference and Exposition: Latin America, 2008 IEEE/PES, pages 1 -8, aug. 2008. 4, 7

    [15] M. Chaudry, N. Jenkins, and G. Strbac. Multi-time period combined gas and electricity network optimisation. Electric Power Systems Research, 78(7):1265 - 1279, 2008. 4, 5, 7, 10, 11

    [16] J. Munoz, N. Jimenez-Redondo, J. Perez-Ruiz, and J. Barquin. Natural gas network modeling for power systems reliability studies. In Power Tech Conference Proceedings, 2003 IEEE Bologna, volume 4, page 8 pp. Vol.4, june 2003. 4, 5

    [17] D. Berry. Renewable energy as a natural gas price hedge: the case of wind. Energy Policy, 33(6):799 - 807, 2005. 4, 7

    [18] M.S. Morals and J.W.M. Lima. Natural gas network pricing and its influence on electricity and gas markets. In Power Tech Conference Proceedings, 2003 IEEE Bologna, volume 3, page 6 pp. Vol.3, 2003. 4

    [19] B. Lu and M. Shahidehpour. Unit commitment with flexible generating units. Power Systems, IEEE Transactions on, 20(2):1022 - 1034, may 2005. 4

    [20] Z. Li. Natural gas for generation: a solution or a problem? Power and Energy Magazine, IEEE, 3(4):16 - 21, july-aug. 2005. 5 [25] Electricity network strategy group (ensg). http://www.decc.gov. uk/assets/decc/11/meeting-energy-demand/future-elec-network/ 2032-electricity-networks-strategy-group-ensg.pdf. 6, 8, 24 [67] J. Dupacová, N. Gröwe-Kuska, and W. Römisch. Scenario reduction in stochastic programming: An approach using probability metrics, 2003. 73 [69] P. Beraldi, D. Conforti, and A. Violi. A two-stage stochastic programming model for electric energy producers. Comput. Oper. Res., 35:3360-3370, October 2008. 77 [81] A. Charnes and W. W. Cooper. Chance constrained programming. Management Science, 6:73 - 79, 1959. 79

    [83] A. Prekopa. On probabilistic constrained programming. Princeton: Princeton University Press, 1970. 79

    [84] U.A. Ozturk, M. Mazumdar, and B.A. Norman. A solution to the stochastic unit commitment problem using chance constrained programming. Power Systems, IEEE Transactions on, 19(3):1589 - 1598, aug. 2004. 79

  • Related Research Results (1)
    Inferred
    School of Engineering (2014)
    40%
  • Metrics
    0
    views in OpenAIRE
    0
    views in local repository
    253
    downloads in local repository

    The information is available from the following content providers:

    From Number Of Views Number Of Downloads
    Online Research @ Cardiff - IRUS-UK 0 253
Share - Bookmark