The “Smart” concept from an electrical sustainability viewpoint

I Llanez-Caballero, L Ibarra, A Peña-Quintal… - Energies, 2023 - mdpi.com
Nowadays, there are many technological-intensive applications that claim to be “smart”.
From smartphones to the smart grid, people relate the word smart with technical novelty …

Machine learning based demand response scheme for IoT enabled PV integrated smart building

P Balakumar, T Vinopraba… - Sustainable Cities and …, 2023 - Elsevier
The short-term forecasting of electric power consumption and renewable energy generation
with high efficiency and advanced demand side management is essential for improving the …

Systematic literature review on fuzzy hybrid methods in photovoltaic solar energy: opportunities, challenges, and guidance for implementation

N Kedir, PHD Nguyen, C Pérez, P Ponce, AR Fayek - Energies, 2023 - mdpi.com
The application of fuzzy hybrid methods has significantly increased in recent years across
various sectors. However, the application of fuzzy hybrid methods for modeling systems or …

Power consumption forecast model using ensemble learning for smart grid

J Kumar, R Gupta, D Saxena, AK Singh - The Journal of Supercomputing, 2023 - Springer
The prediction of power consumption of smart meters plays a vital role in power distribution
and management in the smart grid, which depends on real-time and historical data …

[HTML][HTML] Estrategias de predicción de consumo energético en edificaciones: una revisión

L Ortega-Diaz, J Cárdenas-Rangel, G Osma-Pinto - TecnoLógicas, 2023 - scielo.org.co
Los edificios son uno de los principales actores contaminantes del medio ambiente, por lo
que es necesario fortalecer las estrategias para la reducción de su consumo energético …

[PDF][PDF] PoQ-Consensus Based Private Electricity Consumption Forecasting via Federated Learning.

Y Zhu, S Sun, C Liu, X Tian, J He… - … -Computer Modeling in …, 2023 - cdn.techscience.cn
With the rapid development of artificial intelligence and computer technology, grid
corporations have also begun to move towards comprehensive intelligence and …

[PDF][PDF] DEVELOPMENT OF AN EFFICIENT DEEP LEARNING SYSTEM FOR AUTOMATIC PREDICTION OF POWER DEMAND BASED ON THE FORECASTING OF …

T Aravind, P Suresh - Neural Network World, 2023 - nnw.cz
Electrical load prediction aids electrical producing and allocation firms in planning capacity
and management to ensure that all customers get the energy they need on a consistent …

Opportunities and Challenges of Using Artificial Intelligence in Energy Communities

V Atias - 2023 International Conference Automatics and …, 2023 - ieeexplore.ieee.org
Energy communities are legal entities that produce, store, and sell renewable energy (RE)
while also exchanging it inside the community via the public grid. They provide economic …

Estrategias de predicción de consumo energético en edificaciones: una revisión

LO Diaz, JC Rangel, GAO Pinto - TecnoLógicas, 2023 - dialnet.unirioja.es
Los edificios son uno de los principales actores contaminantes del medio ambiente, por lo
que es necesario fortalecer las estrategias para la reducción de su consumo energético …

IoT and Sustainability Energy Systems: Risk and Opportunity

P Nanjundan, JP George - AI-Powered IoT in the Energy Industry: Digital …, 2023 - Springer
Abstract As IoT (Internet of Things) and smart technologies have developed rapidly, many
technological advancements have been made possible. The IoT's main objective is to assist …