Managing wind power variability and uncertainty through increased power system flexibility: Dissertation

    Research output: ThesisDissertation

    Abstract

    Variability and uncertainty of wind power generation increase the cost of maintaining the short-term energy balance in power systems. As the share of wind power grows, this cost becomes increasingly important. This thesis examines different options to mitigate such cost increases. More detailed analysis is performed on three of these: flexibility of conventional power plants, smart charging of electric vehicles (EVs), and flexibility in heat generation and use. The analysis has been performed with a stochastic unit commitment model (WILMAR) and a generation planning model (Balmorel). Electric boilers can absorb excess power generation and enable shutdown of combined heat and power (CHP) units during periods of high wind generation and low electricity demand. Heat storages can advance or postpone heat generation and hence affect the operation of electric boilers and CHP units. The availability of heat measures increased the cost optimal share of wind power from 35% to 47% in one of the analysed scenarios. The analysis of EVs revealed that smart charging would be a more important source of flexibility than vehicle-to-grid (V2G), which contributed 23% to the 227 /vehicle/year cost savings when smart charging with V2G was compared with immediate charging. Another result was that electric vehicles may actually reduce the overall CO2 emissions when they enable a higher share of wind power generation. Most studies about wind power integration have not included heat loads or EVs as means to decrease costs induced by wind power variability and uncertainty. While the impact will vary between power systems, the thesis demonstrates that they may bring substantial benefits. In one case, the cost optimal share of wind-generated electricity increased from 35% to 49% when both of these measures were included.
    Original languageEnglish
    QualificationDoctor Degree
    Awarding Institution
    • Aalto University
    Supervisors/Advisors
    • Lund, Peter D., Supervisor, External person
    Award date27 Sep 2013
    Place of PublicationEspoo
    Publisher
    Print ISBNs978-951-38-8005-7
    Electronic ISBNs978-951-38-8006-4
    Publication statusPublished - 2013
    MoE publication typeG5 Doctoral dissertation (article)

    Keywords

    • wind power
    • unit commitment
    • economic dispatch
    • generation planning
    • energy balance
    • electric boiler
    • heat storage
    • heat pump
    • electric vehicle
    • hydro power
    • flexibility
    • variability
    • uncertainty

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