A decomposition approach to forecasting electric power system commercial load using an artificial neural network

2002 ◽  
Author(s):  
G. Mbamalu ◽  
M.E. El-Hawary
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Power System ◽  
Electric Power ◽  
Electric Power System ◽  
Decomposition Approach ◽  
Artificial Neural

scholarly journals Data Preprocessing for Load Forecasting using Artificial Neural Network

2020 ◽  
Author(s):  
Rafael S. F. Ferraz ◽  
Renato S. F. Ferraz ◽  
Lucas F. S. Azeredo ◽  
Benemar A. de Souza
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Power System ◽  
Demand Forecasting ◽  
Energy Resource ◽  
Data Preprocessing ◽  
Electric Power System ◽  
Percentage Error ◽  
Gradual Change ◽  
Artificial Neural

An accurate demand forecasting is essential for planning the electric dispatch in power system, contributing financially to electricity companies and helping in the security and continuity of electricity supply. In addition, it is evident that the distributed energy resource integration in the electric power system has been increasing recently, mostly from the photovoltaic generation, resulting in a gradual change of the load curve profile. Therefore, the 24 hours ahead prediction of the electrical demand of Campina Grande, Brazil, was realized from artificial neural network with a focus on the data preprocessing. Thus, the time series variations, such as hourly, diary and seasonal, were reduced in order to obtain a better demand prediction. Finally, it was compared the results between the forecasting with the preprocessing application and the prediction without the  preprocessing stage. Based on the results, the first methodology presented lower mean absolute percentage error with 7.95% against 10.33% of the second one.

scholarly journals Voltage instability analysis based on modal analysis technique and artificial neural network

2019 ◽  
Vol 13 (3) ◽  
pp. 1274
Author(s):  
Ahmad Fateh Mohamad Nor ◽  
Marizan Sulaiman
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Power System ◽  
Modal Analysis ◽  
Electric Power System ◽  
Test Power ◽  
High Tendency ◽  
Voltage Instability ◽  
Analysis Technique ◽  
Artificial Neural

<span>One of the paramount importance in the operation of electrical power system operation order to sustain the equilibrium of the system is the stability of the load buses’ voltages. If the load buses voltages are not stable, this can cause serious problem especially power system blackout. This paper presents the analysis of voltage instability in electric power system by using modal analysis technique. However, one of the challenges of modal analysis is the intencive and complex calculation procedures. In order to overcome that, this paper implements Artificial Neural Network (ANN) to improve the implementation of modal analysis technique. ANN is used to determine the participation factors obtained from the modal analysis technique. The results show that modal analysis technique is able to show which bus is close towards experiencing voltage instability. In addition, the results also show that ANN is able to predict the values of participation factors. A load bus is considered a weak bus if the bus has high tendency towards experiencing voltage instability. IEEE-14 bus test power system has been chosen as the test power system.</span>

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