• DocumentCode
    635313
  • Title

    Optimization of the operation of hydro stations in market environment using Genetic Algorithms

  • Author

    Sampaio, G.S. ; Saraiva, J.T. ; Sousa, J.C. ; Mendes, V.T.

  • Author_Institution
    Fac. de Eng., Univ. do Porto, Porto, Portugal
  • fYear
    2013
  • fDate
    27-31 May 2013
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This paper describes an approach to the short term operation planning of hydro stations in market environment. The developed approach is based on the solution of an optimization problem to maximize the profit of a generation agent along a planning period discretized in hourly steps using a Genetic Algorithm. This problem includes the possibility of pumping since this is an important resource in the scope of electricity markets. The scheduling problem was developed starting with an initial simplified version in which the head loss is neglected and the head is assumed constant. Then, it was implemented a second model in which the nonlinear relation between the head, the hydro power and the water discharge is retained and finally an approach in which the hydro schedule obtained in a given step is used to update the hourly electricity prices used to compute the profit of the generation agent. The short term hydro scheduling problem is illustrated using two Case Studies - the first one was designed to run a set of initial tests to the developed algorithm and the second one refers to a set of hydro stations that mirrors a cascade of 8 stations in Portugal.
  • Keywords
    genetic algorithms; hydroelectric power stations; power generation economics; power generation planning; power generation scheduling; power markets; Portugal; electricity markets; electricity prices; generation agent; genetic algorithm; genetic algorithms; hydro power; hydro station operation optimization; market environment; nonlinear relation; profit maximization; scheduling problem; short term hydro scheduling problem; short term operation planning; water discharge; Computational modeling; Electricity supply industry; Genetic algorithms; Optimization; Schedules; Scheduling; day-ahead market; genetic algorithms; profit maximization; pumping; short-term hydro scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    European Energy Market (EEM), 2013 10th International Conference on the
  • Conference_Location
    Stockholm
  • Type

    conf

  • DOI
    10.1109/EEM.2013.6607278
  • Filename
    6607278