Open AccessSolving the problem of optimizing wind farm design using genetic algorithms
Author(s) -
Amelec Viloria,
Hugo Nuñez Lobo,
Omar Bonerge Píneda Lezama
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/872/1/012029
Subject(s) - wind power , renewable energy , sustainability , fossil fuel , environmental pollution , genetic algorithm , production (economics) , metaheuristic , environmental economics , natural resource economics , computer science , environmental science , engineering , mathematical optimization , economics , environmental protection , algorithm , ecology , waste management , mathematics , biology , macroeconomics , electrical engineering
Renewable energies have become a topic of great interest in recent years because the natural sources used for the generation of these energies are inexhaustible and non-polluting. In fact, environmental sustainability requires a considerable reduction in the use of fossil fuels, which are highly polluting and unsustainable [1]. In addition, serious environmental pollution is threatening human health, and many public concerns have been raised [2]. As a result, many countries have proposed ambitious plans for the production of green energy, including wind power, and consequently, the market for wind energy is expanding rapidly worldwide [3]. In this research, an evolutionary metaheuristic is implemented, specifically genetic algorithms.