Wind Energy Productivity Evaluation Using Weibull Statistical Method

The wind power is the important complement to fossil fuels usage, bears the advantages of clean, green and renewable. The state has determined to develop the regions locating along the interior coast in Jiangsu province, and the exploitation of wind energy is a key constituent. Wind in these regions has the peculiar properties which affect the wind energy utilization, in the paper the simulation of wind farm in coast region is investigated, one virtual reality system is constructed which involves the representation of sea by level of detail, and representation the hydrogen generation by particle filter. The virtual reality system is able to serve as the platform of wind farm construction, wind energy productivity predication, and the engineering test.

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A Unique Unified Wind Speed Approach to Decision-Making for Dispersed Locations

Sustainability ◽

10.3390/su13169340 ◽

2021 ◽

Vol 13 (16) ◽

pp. 9340

Author(s):

Ayman M. Mansour ◽

Abdulaziz Almutairi ◽

Saeed Alyami ◽

Mohammad A. Obeidat ◽

Dhafer Almkahles ◽

...

Keyword(s):

Wind Speed ◽

Wind Energy ◽

Optimal Management ◽

Training Set ◽

Energy Productivity ◽

Innovative Method ◽

Effective Operation ◽

Network Operations ◽

Learning Software ◽

Grid Operators

The repercussions of high levels of environmental pollution coupled with the low reserves and increased costs of traditional energy sources have led to the widespread adaptation of wind energy worldwide. However, the expanded use of wind energy is accompanied by major challenges for electric grid operators due to the difficulty of controlling and forecasting the production of wind energy. The development of methods for addressing these problems has therefore attracted the interest of numerous researchers. This paper presents an innovative method for assessing wind speed in different and widely spaced locations. The new method uses wind speed data from multiple sites as a single package that preserves the characteristics of the correlations among those sites. Powerful Waikato Environment for Knowledge Analysis (Weka) machine learning software has been employed for supporting data preprocessing, clustering, classification, visualization, and feature selection and for using a standard algorithm to construct decision trees according to a training set. The resultant arrangement of the sites according to likely wind energy productivity facilitates enhanced decisions related to the potential for the effective operation of wind energy farms at the sites. The proposed method is anticipated to provide network operators with an understanding of the possible productivity of each site, thus facilitating their optimal management of network operations. The results are also expected to benefit investors interested in establishing profitable projects at those locations.

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Wind Energy Technology, Status Review

Wind Engineering ◽

10.1260/0309524001495440 ◽

2000 ◽

Vol 24 (2) ◽

pp. 65-72 ◽

Cited By ~ 1

Author(s):

David Milborrow

Keyword(s):

Wind Energy ◽

Wind Turbines ◽

Offshore Wind ◽

Energy Technology ◽

Offshore Wind Energy ◽

Energy Productivity ◽

Design Concepts ◽

Unit Capacity ◽

The Cost

Wind energy technology has developed extremely rapidly, and many commercial wind turbines now on the market have capacity ratings of one megawatt or more. Energy productivity per unit of rotor area has steadily improved. Turbine prices have decreased per unit capacity, so the cost of wind-generated electricity has fallen steadily. This paper examines design concepts, applications and economics, and looks to further developments, including offshore wind energy.

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