O'Sullivan, Jonathan

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O'Sullivan, Jonathan
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O'Sullivan, Jonathan

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  • Publication
    A sustainability strategy for Ireland’s electricity network
    (Risø National Laboratory for Sustainable Energy, 2009-09)
    O'Sullivan, Jonathan 
    ;
    Shine, J. 
    ;
    Walsh, A. 
    ;
    Keane, Andrew 
    ;
    O'Malley, Mark 
    The electricity system of Ireland is unique as it has no synchronous connections to other systems, while the existing non-synchronous connection provides limited flexibility. When coupled with a target of 40% electricity from renewables by 2020, exceeding any other country, the challenge is truly striking. However, this challenge also gives Ireland the opportunity to be the world leader in this area. The unique experience in solving this problem will provide the technology and knowledge to harness renewable energy sources globally and limit the dependency on petrochemicals. The continued development of the electricity distribution network as a smart network is a critical element of this process which spans electricity generation, transportation and energy end use. This paper described the various elements of ESB Networks’ sustainability strategy and the associated research themes being jointly pursued by ESB Networks, the Electric Power Research Institute (EPRI) and the Electricity Research Centre, University College Dublin.
      349
  • Publication
    New tool for integration of wind power forecasting into power system operation
    (IEEE, 2009-06)
    Gubina, Andrej F. 
    ;
    Keane, Andrew 
    ;
    Meibom, Peter 
    ;
    O'Sullivan, Jonathan 
    ;
    Goulding, Oisin 
    ;
    McCartan, Tom 
    ;
    O'Malley, Mark 
    The paper describes the methodology that has been developed for Transmission System Operators (TSOs) of Republic of Ireland, Eirgrid, and Northern Ireland, SONI the TSO in Northern Ireland, to study the effects of advanced wind power forecasting on optimal short-term power system scheduling. The resulting schedules take into account the electricity market conditions and feature optimal reserve scheduling. The short-term wind power prediction is provided by the Anemos tool, and the scheduling function, including the reserve optimisation, by the Wilmar tool. The proposed methodology allows for evaluation of the impacts that different types of wind energy forecasts (stochastic vs. deterministic vs. perfect) have on the schedules, and how the new incoming information via in-day scheduling impacts the quality of the schedules. Within the methodology, metrics to assess the quality of the schedules is proposed, including the costs, reliability and cycling. The resulting schedules are compared to the Day-ahead and In-day results of the existing scheduling methodology, Reserve Constrained Unit Commitment (RCUC), with the historical data used as the input for calibration.
      2339Scopus© Citations 9