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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 ...
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 ...
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. ...
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 ...
Forecasting energy time-series data using a fuzzy ARTMAP neural network
(2020-10-14)
Time-series forecasting is an important field of machine learning and is fundamental in analyzing trends based on historical data from various sources. In this paper, a fuzzy ARTMAP neural network for time-series forecasting ...
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 ...
A novel neural model to electrical load forecasting in transformers
(Int Inst Informatics & Systemics, 2001-01-01)
The paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized ...
Multinodal Load Forecasting in Power Electric Systems using a Neural Network with Radial Basis Function
(Trans Tech Publications Ltd, 2011-01-01)
In this paper we present the results of the use of a methodology for multinodal load forecasting through an artificial neural network-type Multilayer Perceptron, making use of radial basis functions as activation function ...
Short term load forecasting for power exchange between Brasil and Paraguay
(2018-06-25)
This work presents a case study of short term load forecasting to assist in the power exchange real time dispatch operation between Brazil and Paraguay at Itaipu Dam. A classical method with statistical approach, Seasonal ...