Power Load Prediction Based on Fractal Theory

المؤلفون المشاركون

Wanqing, Song
Jian-Kai, Liang
Cattani, Carlo

المصدر

Advances in Mathematical Physics

العدد

المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-6، 6ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2015-03-19

دولة النشر

مصر

عدد الصفحات

6

التخصصات الرئيسية

الفيزياء

الملخص EN

The basic theories of load forecasting on the power system are summarized.

Fractal theory, which is a new algorithm applied to load forecasting, is introduced.

Based on the fractal dimension and fractal interpolation function theories, the correlation algorithms are applied to the model of short-term load forecasting.

According to the process of load forecasting, the steps of every process are designed, including load data preprocessing, similar day selecting, short-term load forecasting, and load curve drawing.

The attractor is obtained using an improved deterministic algorithm based on the fractal interpolation function, a day’s load is predicted by three days’ historical loads, the maximum relative error is within 3.7%, and the average relative error is within 1.6%.

The experimental result shows the accuracy of this prediction method, which has a certain application reference value in the field of short-term load prediction.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Jian-Kai, Liang& Cattani, Carlo& Wanqing, Song. 2015. Power Load Prediction Based on Fractal Theory. Advances in Mathematical Physics،Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1053032

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Jian-Kai, Liang…[et al.]. Power Load Prediction Based on Fractal Theory. Advances in Mathematical Physics No. 2015 (2015), pp.1-6.
https://search.emarefa.net/detail/BIM-1053032

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Jian-Kai, Liang& Cattani, Carlo& Wanqing, Song. Power Load Prediction Based on Fractal Theory. Advances in Mathematical Physics. 2015. Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1053032

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1053032