In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids allows real-time collection of data on the operating status of the electricity grid. Based on this availability of data, it is feasible and convenient to predict consumption in the short term, from a few hours to a week. The hypothesis of the study is that the method used to present time variables to a prediction system of electricity consumption affects the results
[EN] Demand prediction has been playing an increasingly important role for electricity management, a...
We use machine learning techniques to forecast Brazilian power electricity consumption (PEC) for sho...
We use machine learning techniques to forecast Brazilian power electricity consumption (PEC) for sho...
In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids...
In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids...
Energy consumption prediction application is one of the most important fieldsthat is artificially co...
PhD thesis in Information technologyDigitalization and decentralization of energy supply have introd...
Digitalization and decentralization of energy supply have introduced several challenges to emerging ...
Electricity distribution companies have been incorporating new technologies that allow them to obtai...
This paper presents a novel approach to forecast day-ahead electricity consumption for residential ...
Maintaining the electricity balance in the Swedish national power grid is a continuous challenge for...
Maintaining the electricity balance in the Swedish national power grid is a continuous challenge for...
This paper presents a system for visualizing electricity consumptiondata along with the implementati...
We use machine learning techniques to forecast Brazilian power electricity consumption (PEC) for sho...
[EN] Demand prediction has been playing an increasingly important role for electricity management, a...
[EN] Demand prediction has been playing an increasingly important role for electricity management, a...
We use machine learning techniques to forecast Brazilian power electricity consumption (PEC) for sho...
We use machine learning techniques to forecast Brazilian power electricity consumption (PEC) for sho...
In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids...
In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids...
Energy consumption prediction application is one of the most important fieldsthat is artificially co...
PhD thesis in Information technologyDigitalization and decentralization of energy supply have introd...
Digitalization and decentralization of energy supply have introduced several challenges to emerging ...
Electricity distribution companies have been incorporating new technologies that allow them to obtai...
This paper presents a novel approach to forecast day-ahead electricity consumption for residential ...
Maintaining the electricity balance in the Swedish national power grid is a continuous challenge for...
Maintaining the electricity balance in the Swedish national power grid is a continuous challenge for...
This paper presents a system for visualizing electricity consumptiondata along with the implementati...
We use machine learning techniques to forecast Brazilian power electricity consumption (PEC) for sho...
[EN] Demand prediction has been playing an increasingly important role for electricity management, a...
[EN] Demand prediction has been playing an increasingly important role for electricity management, a...
We use machine learning techniques to forecast Brazilian power electricity consumption (PEC) for sho...
We use machine learning techniques to forecast Brazilian power electricity consumption (PEC) for sho...