Wind and Sea Breeze Characteristics for the Offshore Wind Farms in the Central Coastal Area of Taiwan

Abstract

Renewable energy is crucial for achieving net zero emissions. Taiwan has abundant wind resources and most major wind farms are offshore over the Taiwan Strait due to a lack of space on land. A thorough study that includes time series modeling of wind speed and sea breeze identification and evaluation for Taiwan’s offshore wind farms was conducted. The time series modeling identified two periodic (annual and diurnal) components and an autoregressive model for multiple-year wind speed time series. A new method for sea breeze type identification and magnitude evaluation is proposed. The method (named as EACH) utilizes a vector and an ellipse to represent the wind condition of a day. Verification of the type identification determined by the new method in two cases of different seasons has been conducted by using surface weather charts and wind data measured by lidar. It is a concise, effective, and programmable way to filter a number of dates for type identification and speed change precursor of sea breeze. We found that the typical daily wind power production of corkscrew sea breeze in Central Taiwan is more than 33 times that of pure sea breeze and more than 9 times that of backdoor sea breeze, which highlights the impact of sea breeze types on wind power.

A Technical and Operational Perspective on Quality Analysis of Stitching Images with Multi-Row Panorama and Multimedia Sources for Visualizing the Tourism Site of Onshore Wind Farm

“…According to Thayumanavan et al [5], rapid development in power electronic converters over the past two decades has given wind power technology advantages over other renewable and green energy technologies, such as high power generation capacity, high conversion efficiency, a pollution-free power generation process, and high availability. Studies on wind power development have been conducted in places such as Greece, China, and Taiwan [6][7][8][9]. This extensive research into wind power reveals its importance as a source of green energy.…”

Assessment of Offshore Wind Power Potential and Wind Energy Prediction Using Recurrent Neural Networks

“…They determined wind turbine capacity factors and performance factors for four specific locations. Meanwhile, Cheng et al [14] established a wind speed statistical model for Central Taiwan, aiming to improve the accuracy of very short-term wind speed predictions. Based on the literature mentioned above, it is recognized that a careful selection of specific wind turbines is crucial for accurately estimating effective wind power generation capacity.…”