Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition

Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition

<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. Whilst different models are proposed for STLF, they are based on small historical datasets and are...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Dabeeruddin Syed (16864260) (author)
مؤلفون آخرون: Haitham Abu-Rub (16855500) (author), Ali Ghrayeb (16864266) (author), Shady S. Refaat (16864269) (author), Mahdi Houchati (16891560) (author), Othmane Bouhali (8252544) (author), Santiago Banales (16891563) (author)
منشور في: 2021
الموضوعات:
Engineering
Electrical engineering
Information and computing sciences
Data management and data science
Machine learning
Load modeling
Predictive models
Load forecasting
Forecasting
Energy consumption
Data models
Clustering algorithms
Deep neural networks
Distribution transformers
k-medoids clustering
Short-term load forecasting
الوسوم: إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

مواد مشابهة

مواد مشابهة