Load Frequency Control in Interconnected Power System by Nonlinear Term and Uncertainty Considerations by Using of Harmony Search Optimization Algorithm and Fuzzy-Neural Network

2018 ◽  
Author(s):  
M.Mollayousefi Zadeh ◽  
S.M.T Bathaee
Keyword(s):  
Neural Network ◽  
Optimization Algorithm ◽  
Fuzzy Neural Network ◽  
Nonlinear Term ◽  
Frequency Control ◽  
Harmony Search ◽  
Load Frequency Control ◽  
Interconnected Power System ◽  
Search Optimization ◽  
Fuzzy Neural

Applying Artificial Intelligence to Short-Term Traffic Flow Forecasting

2012 ◽  
Vol 433-440 ◽  
pp. 5214-5217
Author(s):  
Hai Huang
Keyword(s):  
Neural Network ◽  
Traffic Flow ◽  
Optimization Algorithm ◽  
Fuzzy Neural Network ◽  
Pso Algorithm ◽  
Local Optimum ◽  
Short Term ◽  
Traffic Flow Forecasting ◽  
Fuzzy Neural ◽  
Low Efficiency

Short-term traffic flow forecasting has a high requirement for the responding time and accuracy of the forecasting method because the result is directly used for instant traffic inducing. Based on the introduction of the fuzzy neural network model for short-term traffic flow forecasting together with its detailed procedures, this paper adopt the particle swarm optimization algorithm to train the fuzzy neural network. Its global searching and optimization algorithm helps to overcome the shortcomings of the traditional fuzzy neural network, such as its low efficiency and “local optimum”. A case study is also given for the PSO algorithm to train the fuzzy neural network for traffic flow forecasting. The result shows that the average square error is 0.932 when the PSO algorithm is put to use for the network training, which is 3.926 when the PSO is not used. Thus result is more accurate and it requires less time for the training procedures. It proves this method is feasible and efficient.

scholarly journals An Optimal LFC in Two-Area Power Systems Using a Meta-heuristic Optimization Algorithm

2017 ◽  
Vol 7 (6) ◽  
pp. 3217
Author(s):  
Mushtaq Najeeb ◽  
Muhamad Mansor ◽  
Hameed Feyad ◽  
Esam Taha ◽  
Ghassan Abdullah
Keyword(s):  
Power Systems ◽  
Optimization Algorithm ◽  
Control Algorithm ◽  
Frequency Control ◽  
Harmony Search ◽  
Load Frequency Control ◽  
Heuristic Optimization ◽  
Maximum Deviation ◽  
Peak Time ◽  
Operation Conditions

In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. This meta-heuristic algorithm is called harmony search (HS), it is used to tune PI controller parameters ( ) automatically. The developed controller (HS-PI) with LFC loop is very important to minimize the system frequency and keep the system power is maintained at scheduled values under sudden loads changes. Integral absolute error (IAE) is used as an objective function to enhance the overall system performance in terms of settling time, maximum deviation, and peak time. The two-area power systems and developed controller are modelled using MATLAB software (Simulink/Code). As a result, the developed control algorithm (HS-PI) is more robustness and efficient as compared to PSO-PI control algorithm under same operation conditions.

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