Short-term load forecast of a low load factor power system for optimization of merit order dispatch using adaptive learning algorithm

2012 ◽  
Author(s):  
K. Pramelakumari ◽  
S. R. Anand ◽  
V. P. Jagathy Raj ◽  
E. A. Jasmin
Keyword(s):  
Power System ◽  
Adaptive Learning ◽  
Learning Algorithm ◽  
Load Factor ◽  
Short Term ◽  
Load Forecast ◽  
Low Load

scholarly journals Neural network model of decision making in electric power facilities under conditions of uncertainty

2021 ◽  
Vol 304 ◽  
pp. 01001
Author(s):  
Isomiddin Siddikov ◽  
Oksana Porubay
Keyword(s):  
Neural Network ◽  
Power System ◽  
Electric Power ◽  
Adaptive Learning ◽  
Fuzzy Inference ◽  
Learning Algorithm ◽  
Local Power ◽  
Operating Modes ◽  
System A ◽  
Takagi Sugeno

The article is devoted to the issue of creating a mathematical model of the problem of making management decisions in electric power facilities based on modern intelligent technologies, which makes it possible to take into account the influence of various factors on the operating modes of the power system. A systematic approach to describing processes in the mathematical language of the theory of fuzzy sets is proposed. To solve the problem of controlling the operating modes of the power system, a neurofuzzy network has been developed that combines the algorithms of Takagi-Sugeno fuzzy inference, as well as a recurrent neural network. An adaptive learning algorithm based on the Frechet method is proposed for training a neural network. The analysis of the efficiency of the fuzzy control model under the conditions of various modes of functioning of the local power system is carried out.

Credibility assessment of short-term load forecast in power system

2012 ◽  
Author(s):  
Zhikun Zhang ◽  
Canbing Li ◽  
Yijia Cao ◽  
Liangxing Tang ◽  
Junxiong Li ◽  
...  
Keyword(s):  
Power System ◽  
Credibility Assessment ◽  
Short Term ◽  
Load Forecast

Risk due to load forecast uncertainty in short term power system planning

1998 ◽  
Vol 13 (4) ◽  
pp. 1493-1499 ◽  
Author(s):  
A.P. Douglas ◽  
A.M. Breipohl ◽  
F.N. Lee ◽  
R. Adapa
Keyword(s):  
Power System ◽  
Power System Planning ◽  
Short Term ◽  
System Planning ◽  
Forecast Uncertainty ◽  
Load Forecast

Multi-objective QPSO for short-term load forecast based on diagonal recursive neural network

2021 ◽  
pp. 1-12
Author(s):  
Lan Zhang ◽  
Lei Xu
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Power System ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Short Term ◽  
Swarm Optimization ◽  
Load Forecast ◽  
Multi Objective ◽  
Recursive Neural Network

The short-term load forecast is an important part of power system operation, which is usually a nonlinear problem. The processing of load forecast data and the selection of forecasting methods are particularly important. In order to get accurate and effective prediction for power system load, this article proposes a hybrid multi-objective quantum particle swarm optimization (QPSO) algorithm for short-term load forecast of power system based on diagonal recursive neural network. Firstly, a multi-objective mathematical model for short-term load forecast is proposed. Secondly, the discrete particle swarm optimization (PSO) algorithm is used to select the characteristics of load data and screen out the appropriate data. Finally, the hybrid multi-objective QPSO algorithm is used to train diagonal recursive neural network. The experimental results show that the hybrid multi-objective QPSO for short-term load forecast based on diagonal recursive neural network is effective.

scholarly journals Neuro-short-term load forecast of the power system in Kuwait

1997 ◽  
Vol 21 (4) ◽  
pp. 215-219 ◽  
Author(s):  
Abdullah S. Al-Fuhaid ◽  
Mohamed A. El-Sayed ◽  
Magdi S. Mahmoud
Keyword(s):  
Power System ◽  
Short Term ◽  
Load Forecast
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