Analysis and Prediction of Wind Speed Effects in East Asia and the Western Pacific Based on Multi-Source Data

Abstract

With the increasing problem of global warming caused by the massive use of fossil fuels, biomass energy as a renewable energy source has attracted widespread attention throughout the globe. In this paper, we analyzed the spatial and temporal variation in wind energy in the East Asia and Western Pacific areas using IGRA site data, ERA5, and NCEP/NCAR reanalysis data from 2000 to 2021, and multi-variate empirical orthogonal function (MV-EOF) decomposition with the Pettitt mutation test, and the seasonal autoregression integrated moving average (SARIMA) model was used to predict the trend of wind speed. The spatial and temporal variations in wind energy in East Asia and Western Pacific areas were analyzed, and it was found that the richer wind-energy resources were mainly concentrated in the “Three Norths” (North China, Northwest China, and Northeast China) and Mongolia, followed by the Western Pacific areas. In addition, the T’ai-hang Mountains and the Qinghai-Tibet Plateau in China block the wind resources in the eastern and southern regions of East Asia, resulting in a shortage of wind resources in this region. In addition, the summer wind speed is significantly lower than in the other three seasons. The first-mode contributions of the MV-EOF wind field and geopotential heights, respectively, are 29.47% and 37.75%. The results show that: (1) There are significant seasonal differences in wind-energy resources in the study area, with the lowest wind speed in summer and the highest wind speed in winter. (2) The wind energy in the study area has significant regional characteristics. For example, China’s Qinghai-Tibet Plateau, Inner Mongolia, Xinjiang region, and Mongolia are rich in wind-energy resources. (3) Wind-energy resources in the study area have gradually increased since 2010, mainly due to changes in large-scale oceanic and atmospheric circulation patterns caused by global warming.

A statistical study of wind speed and its connectivity with relative humidity and temperature in Ughelli, Delta State, Nigeria

“…Wind is one of the important weather variables that gives shape to the external environment and also determines the amount of wind energy that can be generated in relation to its speed. Hence, in maximizing wind energy resources, it is pertinent that the wind speed is examined with several techniques (Dec et al, 2018;Tang et al, 2022). As a climatic variable, wind is the pressure gradient that gives the momentum for air movement and whose outcomes oftentimes may be detrimental when it is accompanied by a storm.…”

Evaluation of Wind Energy Potential in Omu Aran, Nigeria Using Weibull and Rayleigh Models

“…It should be noted that the South Western region of Nigeria is closer to the equator and characterized with a hot and humid climate, and a higher level of rainfall, while the Northern part has a hot and dry climate with lower rainfall and higher temperatures. Also, since the topography is a factor that can significantly affect the wind patterns (Tang et al, 2022). As a result, there is an urgent need for more research into the most appropriate models for predicting wind energy potential in Nigeria.…”