Prediction of Electricity Consumption Profiles Using Potential Polynomials of Degree One and Artificial Neural Networks in Smart Metering Infrastructure
This work analyzes methods and algorithms for predicting the behavior of electricity consumption based on neural networks using data obtained from the Advanced Measurement Infrastructure (AMI) of an educational institution. Also, a contrast between the use of conventional neural networks (ANN), wave...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Pedagógica y Tecnológica de Colombia
- Repositorio:
- RiUPTC: Repositorio Institucional UPTC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uptc.edu.co:001/14308
- Acceso en línea:
- https://revistas.uptc.edu.co/index.php/ingenieria/article/view/12772
https://repositorio.uptc.edu.co/handle/001/14308
- Palabra clave:
- AMI
medición inteligente
P1P
predicción de consumo eléctrico
WNN
AMI
electricity consumption prediction
P1P
smart metering
WNN
- Rights
- License
- Copyright (c) 2021 Pablo Urgilés, Juan Inga-Ortega, Arturo Peralta, Andrés Ortega