On the Ability of Automatic Generation Control to Manage Critical Situations in Power Systems with Participation of Wind Power Plants Parks

2016 ◽  
pp. 105-120
Author(s):  
Suad S. Halilčević ◽  
Claudio Moraga
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
Power Plants ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Wind Power Plants ◽  
Generation Control ◽  
Critical Situations

scholarly journals Wind power integration into the automatic generation control of power systems with large-scale wind power

2014 ◽  
Vol 2014 (10) ◽  
pp. 538-545 ◽  
Author(s):  
Abdul Basit ◽  
Anca Daniela Hansen ◽  
Mufit Altin ◽  
Poul Sørensen ◽  
Mette Gamst
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
Large Scale ◽  
Automatic Generation ◽  
Automatic Generation Control ◽  
Wind Power Integration ◽  
Generation Control

Robust Optimization Algorithms for Solving Automatic Generation Control of Multi-Constrained Power System

2018 ◽  
pp. 75-114 ◽  
Author(s):  
Dipayan Guha ◽  
Provas Kumar Roy ◽  
Subrata Banerjee
Keyword(s):  
Power Systems ◽  
Power System ◽  
Power Plants ◽  
Fitness Function ◽  
Automatic Generation ◽  
Pid Controllers ◽  
Automatic Generation Control ◽  
The Stability ◽  
Teaching Learning ◽  
Generation Control

This chapter presents four effective evolutionary methods, namely grey wolf optimization (GWO), symbiotic organism search (SOS), JAYA, and teaching-learning-based optimization (TLBO), for solving automatic generation control (AGC) problem in power system. To show the effectiveness, two widely used interconnected power plants are examined. To extract maximum possible generation, distinct PID-controllers are designed employing ITAE-based fitness function. Further, to enhance the dynamic stability of concerned power systems, 2DOF-PID controllers are proposed in LFC area and optimally designed using aforesaid algorithms. To demonstrate the supremacy, obtained results are compared with some existing control algorithms. Moreover, robustness of the designed controller is believed under the action of random load perturbation (RLP). Finally, sensitivity analysis is carried out to show the stability of the designed system under loading and parametric disturbance conditions.

A FO-PID Controlled Automatic Generation Control of Multi Area Power Systems Tuned by Harmony Search

2020 ◽  
Vol 13 (1) ◽  
pp. 101-109
Author(s):  
Aurobindo Behera ◽  
Tapas K. Panigrahi ◽  
Arun K. Sahoo
Keyword(s):  
Power Systems ◽  
Harmony Search ◽  
Automatic Generation ◽  
System Stability ◽  
Automatic Generation Control ◽  
Similar System ◽  
Thermal Plant ◽  
Clear Idea ◽  
Generation Control ◽  
Fractional Controller

Background: Power system stability demands minimum variation in frequency, so that loadgeneration balance is maintained throughout the operation period. An Automatic Generation Control (AGC) monitors the frequency and varies the generation to maintain the balance. A system with multiple energy sources and use of a fractional controller for efficient control of stability is presented in the paper. At the outset a 2-area thermal system with governor dead band, generation rate constraint and boiler dynamics have been applied. Methods: A variation of load is deliberated for the study of the considered system with Harmony Search (HS) algorithm, applied for providing optimization of controller parameters. Integral Square Time Square Error (ISTSE) is chosen as objective function for handling the process of tuning controller parameters. : A study of similar system with various lately available techniques such as TLBO, hFA-PS and BFOA applied to PID, IDD and PIDD being compared to HS tuned fractional controller is presented under step and dynamic load change. The effort extended to a single area system with reheat thermal plant, hydel plant and a unit of wind plant is tested with the fractional controller scheme. Results: The simulation results provide a clear idea of the superiority of the combination of HS algorithm and FO-PID controller, under dynamically changing load. The variation of load is taken from 1% to 5% of the connected load. Conclusion: Finally, system robustness is shown by modifying essential factors by ± 30%.

Wind Speed Forecasting Based on FNN in Wind Farm

2014 ◽  
Vol 651-653 ◽  
pp. 1117-1122
Author(s):  
Zheng Ning Fu ◽  
Hong Wen Xie
Keyword(s):  
Neural Network ◽  
Wind Speed ◽  
Power Systems ◽  
Wind Power ◽  
Power Plants ◽  
Fuzzy Neural Network ◽  
Negative Impact ◽  
Wind Speed Forecasting ◽  
Wind Power Plants ◽  
Fuzzy Neural

Wind speed forecasting plays a significant role to the operation of wind power plants and power systems. An accurate forecasting on wind power can effectively relieve or avoid the negative impact of wind power plants on power systems and enhance the competition of wind power plants in electric power market. Based on a fuzzy neural network (FNN), a method of wind speed forecasting is presented in this paper. By mining historical data as the learning stylebook, the fuzzy neural network (FNN) forecasts the wind speed. The simulation results show that this method can improve the accuracy of wind speed forecasting effectively.

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