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Comparison results of two optimization techniques for a combined wind and solar power plant
Author(s) -
Samarakou M. T.,
Grigoriadou M.,
Caroubalos C.
Publication year - 1988
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.4440120210
Subject(s) - method of steepest descent , gradient descent , optimization algorithm , simplex algorithm , simplex , power station , power (physics) , computer science , mathematical optimization , control theory (sociology) , mathematics , engineering , electrical engineering , physics , linear programming , geometry , control (management) , quantum mechanics , machine learning , artificial intelligence , artificial neural network
Two optimization techniques have been tested on an hour‐by‐hour simulation of a combined wind and solar power plant. The system also includes a battery storage system as well as a group of diesel generators. The two optimization techniques are: simplex from the package of MINUITS written at CERN and a modified steepest descent algorithm. Both techniques are suited to hour‐by‐hour simulation for the above system since the function being minimized is monotonically decreasing towards a minimum. The comparison results showed that the steepest descent algorithm converges slightly faster than the simplex one. Moreover, the application of the techniques for two different sites with different load profiles let us conclude that the results are stable.