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[實習主題] -- 邁向智慧電網:利用人工智慧預測風力發電量

已更新:2023年2月19日

指導教授: 謝依芸 教授

專案經理: 曾靖琇

實習名額: 1~2位

是否可遠距: 可


地球溫室效應加劇,全球再生能源漸漸興起,各國陸續訂定相關政策。我國國發會也在去年3月提出2050淨零排放目標,其中離岸風電的裝置容量計畫在2050年達到40GW~55GW。 然而,一昧地追求裝置容量增加,並不是對再生能源發電量提升的完整做法。實際發電量仍受到所在位置的氣候的影響,透過短時間氣象因子預測風力發電的單位發電量,評估電廠的較佳興建位置,在設置新電廠的同時考慮設備利用率則可以將實際發電量提升至更高,將風力發電能源發揮至更大。


The Earth's greenhouse effect is intensifying, and renewable energy is gradually gaining ground worldwide, with countries gradually formulating related policies. In March of last year, our National Development Council also proposed a net zero emissions target for 2050, with plans for offshore wind power to reach 40GW to 55GW by 2050. However, blindly pursuing an increase in installation capacity is not a complete solution to increasing renewable energy generation. The actual power generation is still affected by the climate of the location, and evaluating the optimal location for a power plant by predicting the unit power generation of wind power through short-term weather factors and considering equipment utilization rate during the installation of a new power plant can increase the actual power generation to a higher level and make better use of wind power energy.





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