Research of the micro grid renewable energy control system based on renewable related data mining and forecasting technology
by Lin Yue; Yao-jun Qu; Yan-xia Song; Shunshoku Kanae; Jing Bai
International Journal of Computational Science and Engineering (IJCSE), Vol. 24, No. 4, 2021

Abstract: The output power of renewable energy has the characteristics of random fluctuation and instability, which has a harmful effect on stability of renewable power grid and causes the problem of low utilisation ratio on renewable energy output power. Thus, this paper proposes a method to predict the output power of renewable energy based on data mining technology. Firstly, the renewable generation power prediction accuracies of three different algorithm, linear regression, decision tree and random forest, are obtained and compared. Secondly, by applying the prediction result to the power dispatch control system, grid-connected renewable power will be consumed by grid-connected load to improve the utilisation ratio of renewable power. A simulation model and experiment platform is established to verify and analyse the prediction usefulness. The experiment shows that the prediction accuracy of the random forest algorithm is the highest. The tendency of renewable energy output power within a period can be calculated by using data mining technology, and the designed experiment platform system can adjust the working state automatically by following the instruction from the data mining result, which can increase the utilisation ratio of renewable energy output power and improve the stability of renewable power grid.

Online publication date: Thu, 12-Aug-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com