A Model Reference Approach for Interarea Modal Damping in Large Power Systems

2011 ◽  
pp. 343-362
Author(s):  
Aranya Chakrabortty
Keyword(s):  
Power Systems ◽  
Model Reference ◽  
Large Power ◽  
Modal Damping

scholarly journals A Neural Network-Based Model Reference Control Architecture for Oscillation Damping in Interconnected Power System

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3653
Author(s):  
Uddin ◽  
Zeb ◽  
Zeb ◽  
Ishfaq ◽  
Khan ◽  
...  
Keyword(s):  
Neural Network ◽  
Power Systems ◽  
Power System ◽  
Performance Indicator ◽  
Stable Condition ◽  
External Perturbation ◽  
Absolute Error ◽  
Unified Power Flow Controller ◽  
Two Phase ◽  
Model Reference

In this paper, a model reference controller (MRC) based on a neural network (NN) is proposed for damping oscillations in electric power systems. Variation in reactive load, internal or external perturbation/faults, and asynchronization of the connected machine cause oscillations in power systems. If the oscillation is not damped properly, it will lead to a complete collapse of the power system. An MRC base unified power flow controller (UPFC) is proposed to mitigate the oscillations in 2-area, 4-machine interconnected power systems. The MRC controller is using the NN for training, as well as for plant identification. The proposed NN-based MRC controller is capable of damping power oscillations; hence, the system acquires a stable condition. The response of the proposed MRC is compared with the traditionally used proportional integral (PI) controller to validate its performance. The key performance indicator integral square error (ISE) and integral absolute error (IAE) of both controllers is calculated for single phase, two phase, and three phase faults. MATLAB/Simulink is used to implement and simulate the 2-area, 4-machine power system.

Coordination of power flow control in large power systems

2001 ◽  
Vol 16 (4) ◽  
pp. 776-781
Author(s):  
Fan Li ◽  
Baohua Li ◽  
Xujun Zheng
Keyword(s):  
Power Systems ◽  
Flow Control ◽  
Power Flow ◽  
Large Power ◽  
Power Flow Control

scholarly journals A novel measurement-based procedure for dynamic equivalents of electric power systems for stability studies using improved sine cosine algorithm

2019 ◽  
Vol 70 (6) ◽  
pp. 454-464
Author(s):  
Omar Benmiloud ◽  
Salem Arif
Keyword(s):  
Power Systems ◽  
Dynamic Properties ◽  
Specific Area ◽  
Pattern Search ◽  
Fine Tuning ◽  
Large Power ◽  
Area Of Interest ◽  
Starting Point ◽  
Sine Cosine Algorithm ◽  
Dynamic Equivalent

Abstract Dynamic equivalent (DE) is an important process of multi-area interconnected power systems. It allows to perform stability assessment of a specific area (area of interest) at minimum cost. This study is intended to investigate the dynamic equivalent of two relatively large power systems. The fourth-order model of synchronous generators with a simplified excitation system is used as equivalent to the group of generators in the external system. To improve the accuracy of the estimated model, the identification is carried in two stages. First, using the global search Sine Cosine Algorithm (SCA) to find a starting set values, then this set is used as starting point for the fine-tuning made through the Pattern Search (PS) algorithm. To increase the reliability of the model’s parameters, two disturbances are used to avoid the identification based on a specific event. The developed program is applied on two standard power systems, namely, the New England (NE) system and the Northeast Power Coordinating Council (NPCC) system. Simulation results confirm the ability of the optimized model to preserve the main dynamic properties of the original system with accuracy.

scholarly journals Total variation as a metric for complementarity in energy resources time series

2021 ◽  
Author(s):  
Diana Cantor ◽  
Andrés Ochoa ◽  
Oscar Mesa
Keyword(s):  
Time Series ◽  
Power Systems ◽  
Total Variation ◽  
Correlation Coefficients ◽  
Mathematical Concept ◽  
Large Power ◽  
Electric System ◽  
Geographical Scale ◽  
Auto Regressive ◽  
High Degree

Complementarity has become an essential concept in energy supply systems. Although there are some other metrics, most studies use correlation coefficients to quantify complementarity. The standard interpretation is that a high negative correlation indicates a high degree of complementarity. However, we show that the correlation is not an entirely satisfactory measure of complementarity. As an alternative, we propose a new index based on the mathematical concept of the total variation. For two time series, the new index φ is one minus the ratio of the total variation of the sum to the sum of the two series' total variation. We apply the index first to an auto-regressive (AR) process and then to various Colombian electric system series. The AR case clearly illustrates the limitations of the correlation coefficient as a measure of complementarity. We then evaluate complementarity across various space-time scales in the Colombian power sectors, considering hydro and wind projects. The complementarity assessment on a broad temporal and geographical scale helps analyze large power systems with different energy sources. The case study of the Colombian hydropower systems suggests that φ is better than ρ because (i) it considers scale, whereas ρ, being non-dimensional, is insensitive to the scale and even to the physical dimensions of the variables; (ii) one can apply φ to more than two resources; and (iii) ρ tends to overestimate complementarity.

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