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Short-term multinodal load forecasting in distribution systems using general regression neural networks
(2011-10-05)
Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, ...
Spatial load forecasting using a demand propagation approach
(2011-05-31)
A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses ...
Consumer behavior after the Brazilian power rationing in 2001
(2006-12-01)
In June 2001, after a dry period, the level of the water reservoirs in Brazil was below their operational levels. This situation, combined with other historical factors, led the country into a period of power rationing. ...
Preprocessing data for short-term load forecasting with a general regression neural network and a moving average filter
(2011-10-05)
This paper proposes a filter based on a general regression neural network and a moving average filter, for preprocessing half-hourly load data for short-term multinodal load forecasting, discussed in another paper. Tests ...
Spatial electric load forecasting using a local movement approach
(2009-12-09)
An agent based model for spatial electric load forecasting using a local movement approach for the spatiotemporal allocation of the new loads in the service zone is presented. The density of electrical load for each of the ...
Electric power systems load forecasting: A survey
(1999-01-01)
This work reviews the latest works on load forecasting, classifying them according to presented methods and models, as statistical, intelligent systems, neural networks and fuzzy logic. As there are many different models ...
Data Issues in Spatial Electric Load Forecasting
(Ieee, 2014-01-01)
The magnitude and geographic location of electricity demand in the planning horizon are vital pieces of information for power distribution companies in planning future network expansion and operation. Such information is ...
Considering Urban Dynamics in spatial electric load forecasting
(2012-12-11)
When dealing with spatio-temporal simulations of load growth inside a service zone, one of the most important problems faced by a Distribution Utility is how to represent the different relationships among different areas. ...
Use of virtual load curves for the training of neural networks for residential electricity consumption forecasting applications
(Ieee, 2018-01-01)
Smart grids are becoming increasingly closer to consumers, especially residential consumers, bringing with them a wide range of possibilities. The level of information obtained on a smart grid will be much higher when ...
Use of virtual load curves for the training of neural networks for residential electricity consumption forecasting applications
(2019-01-25)
Smart grids are becoming increasingly closer to consumers, especially residential consumers, bringing with them a wide range of possibilities. The level of information obtained on a smart grid will be much higher when ...