Big Data Analysis of Energy Economics in Wind Power Market

Hui Liu (), Nikolaos Nikitas (), Yanfei Li () and Rui Yang ()
Additional contact information
Hui Liu: Central South University
Nikolaos Nikitas: University of Leeds
Yanfei Li: Hunan Agricultural University
Rui Yang: Central South University

Chapter Chapter 4 in Big Data in Energy Economics, 2022, pp 95-115 from Springer

Abstract: Abstract Wind energy is a type of representative clean energy. In recent years, the world has gradually increased the attention to the utilization efficiency of wind energy. The wind power market also contains huge development prospects and opportunities. This chapter focuses on wind energy to carry out big data analysis of energy economy. To realize the trend analysis of wind energy, this chapter first proposes a spatial scale wind energy prediction framework and embeds four different binary optimization algorithms into it. Several actual datasets collected from wind farms are used to test the forecasting performance of each model. Subsequently, the conversion efficiency of wind energy is briefly introduced. Finally, the market economy of wind power applications is analyzed for China, America, and Europe. Although the wind energy applications in these regions vary, they all show promising prospects. Wind power is expanding dramatically to meet the growing energy needs of the world.

Keywords: Wind energy; Wind power market; Energy economics; Spatial prediction; Wind power application (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:mgmchp:978-981-16-8965-9_4

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DOI: 10.1007/978-981-16-8965-9_4

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