• DocumentCode
    3581177
  • Title

    Decision making model for determining firm energy and generation reserves assuming demand follows a doubly truncated normal distribution

  • Author

    Cedeno, Enrique B.

  • Author_Institution
    Bus. Sch., Nanjing Tech Univ., Nanjing, China
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Adequate generation reserves are needed to avoid failures in case electricity demand exceeds available online generation capacity. Properly determining generation reserves promotes efficient resource allocation. This paper establishes a model to purchase optimal quantities of firm energy and of various reserve capacities for a dispatch period to cover randomness in demand considering transmission network, contingency constraints and costs to start and stop reserve generators. Demand is modeled using a Doubly-truncated Normal Distribution. A synthetic example consisting of 27 generators selling firm and reserve energy created to replicate the operational conditions for a dispatch period of the Midwest Independent System Operator (MISO) is presented to illustrate the proposed procedure.
  • Keywords
    decision making; normal distribution; power generation dispatch; power generation reliability; power transmission reliability; Doubly Truncated Normal Distribution; MISO; contingency constraint; decision making model; dispatch period; failure avoidance; firm energy determination; generation reserve capacity; midwest independent system operator; resource allocation; transmission network; Decision making; Electricity; Gaussian distribution; Generators; Mathematical model; Spinning; Vectors; decision making; demand uncertainty; deregulation; power generation; power quality; power system management; power system planning; resource management; stock market;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2014 IEEE PES Asia-Pacific
  • Type

    conf

  • DOI
    10.1109/APPEEC.2014.7066193
  • Filename
    7066193