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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, ...
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 ...
Short-Term Multinodal Load Forecasting Using a Modified General Regression Neural Network
(Institute of Electrical and Electronics Engineers (IEEE), 2011-10-01)
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, a technique that is precise, reliable, and ...
Short-Term Multinodal Load Forecasting Using a Modified General Regression Neural Network
(Institute of Electrical and Electronics Engineers (IEEE), 2011-10-01)
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, a technique that is precise, reliable, and ...
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. ...
Short-Term Multinodal Load Forecasting Using a Modified General Regression Neural Network
(Institute of Electrical and Electronics Engineers (IEEE), 2014)
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 ...
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 ...