Open AccessMulti-criteria optimization of wind power plant parameters
Author(s) -
Aleksandr Melekhin
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1730/1/012067
Subject(s) - mathematical optimization , range (aeronautics) , aerodynamics , pareto principle , computer science , wind power , convergence (economics) , process (computing) , optimization problem , dimension (graph theory) , mathematics , engineering , aerospace engineering , pure mathematics , electrical engineering , economic growth , economics , operating system
The use of renewable energy sources to generate electricity is a hot topic. The author has developed a mathematical model of the aerodynamic process of a wind power plant with the solution of a multi-criteria optimization problem. The optimal range of controlled parameters affecting the aerodynamic process with a minimum amount of blown surface and maximum electrical energy production is determined. Regularities of aerodynamic process are established. The convergence of the results of the study in the calculation on the basis of theoretical dependencies and the solution of the mathematical model is determined. To find the optimal controlled parameters of the aerodynamic installation, a complex research method developed by the author is applied, based on multi-criteria optimization of parameters with the introduction of empirically obtained data. The preliminary procedure of IOSO NM 3.8 consists in the formation of an initial plan of the experiment, which can be implemented both in a passive way (using information about various parameters, optimization criteria and constraints obtained earlier) and in an active way, when too much is generated in the initial search area in accordance with a given distribution law. For each vector of variable parameters, the values of optimization criteria and constraints are determined by direct reference to the mathematical model of the object under study. The number of points that make up the initial plan of the experiment depends on the dimension of the problem and the chosen approximation functions. The solution results in a Pareto (optimal) set of solutions.