Characteristics of Wind Resources and Post-Project Evaluation of Wind Farms in Coastal Areas of Zhejiang

Abstract

As the onshore wind farm technology matures, offshore wind energy has attracted increasing attention. Zhejiang has coastal areas with massive potential for wind resources because of its geographical location. Therefore, understanding the wind resources in these areas can lay a foundation for future development and utilization. On this basis, this study used the measured wind field data of a wind farm along the coast of Zhejiang from March 2014 to February 2015 and from March 2016 to February 2018 to investigate and compare the characteristics of wind energy resources, including average wind speed, Weibull shape and scale factors, wind direction variation, and wind energy density. Then, the capacity coefficient of a wind turbine predicted using the wind farm data was compared with the actual capacity coefficients of two wind turbines in the wind farm in 2019. Results revealed the following observations: The overall variations in the evaluation indicators followed clear patterns over the 3 years. For example, the main wind direction in the same season was the same, and the variations in the monthly average wind speed, the monthly wind power density, and the theoretical capacity factors were highly similar. The time-series data indicated that the difference in the indicators between summer and autumn was significantly larger than that between other seasons, with the maximum difference in monthly average wind speed of 1.46 times and the maximum difference in monthly wind power density of 1.5 times. The comparison results of the capacity coefficient showed that the theoretical and actual capacity coefficients were extremely close when the monthly average wind speed was less than 6 m/s, with the average difference being less than 9%. When the monthly average wind speed was greater than 6 m/s, the proximity between the theoretical and actual capacity coefficients was reduced, with an average difference of more than 9% and a maximum value of 28%. In general, the overall characteristics of wind resources in coastal areas of Zhejiang exhibited similar trends but fluctuated considerably in some months. Wind energy forecasts had significant discrepancies from the actual operation indicators of the wind farm when the wind speed was high.

Wind Speed Probability Distribution and Parameter Estimation Methods

“…Therefore, the MLE method has been a major method for solving the Weibull distribution function. The MLE method for estimating the Weibull parameters is formulated as [32]:…”

A Parametric Approach to Compare the Wind Potential of Sanghar and Gwadar Wind Sites

“…It is necessary to have the knowledge of different wind characteristics to do the wind power assessment of the selected sites. Wind continuously varies its magnitude, direction, and density due to its volatile nature [42]. In order to do the effective assessment and utilization of wind energy, wind characteristics needs to be considered precisely.…”

Layout Method of Met Mast Based on Macro Zoning and Micro Quantitative Siting in a Wind Farm

“…This screening index is mainly in response to standard [25]. Considering the wake effect of wind turbines, correction of free flow wind speed in front of wind turbines and so on, the value range of α is generally [2,4].…”

“…Met mast represents the basic equipment for wind resource monitoring and evaluation and plays an important role in the planning, construction and operation stage of wind farm [2,3]. The data of met mast not only represent an important basis for deciding whether to build a wind farm, but also the support for wind power prediction and closed-loop assessment of wind farms [4,5]. However, at present, some wind power enterprises are lack of emphasis on met mast.…”