The Study on Electric Power System Based on Swarm Intelligence

In this paper, we introduce the swarm intelligence computation and its applications in power system. Because swarm intelligence does not need any precondition of centralized control and global model, it is very suitable to solve large scale power system nonlinear optimization problems which are hard to establish effective formalized models and difficult to be solved by traditional methods. In order to apply swarm intelligence better in power system, we propose two central research directions in the future: (1) The mathematical basis of swarm intelligence is unsubstantial and it lacks profound and pervasive theoretical analysis, so we must analysis its convergence and selection of parameters, especially the parameter selection of large scale power system optimization problems. (2) Because swarm intelligence is internally parallel, we should realize it based on the parallel computation theory. This work will also be helpful for the real-time need of power system.

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Computationally Efficient Hybrid Method for Transmission Network Expansion Planning

International Journal of Emerging Electric Power Systems ◽

10.1515/ijeeps-2016-0145 ◽

2017 ◽

Vol 18 (2) ◽

Cited By ~ 1

Author(s):

Ashu Verma ◽

Soumya Das ◽

P. R. Bijwe

Keyword(s):

Power System ◽

Large Scale ◽

Optimization Problems ◽

Hybrid Approach ◽

Solution Process ◽

System Optimization ◽

Mixed Integer ◽

Transmission Network ◽

Network Expansion ◽

Expansion Planning

Abstract Transmission network expansion planning (TNEP) is an important and computationally very demanding problem in power system. Many computational approaches have been proposed to handle TNEP in the past. The problem is mixed integer, large scale and its complexity increases exponentially with the size of the system. Metaheuristic techniques have gained a lot of importance in last few years to solve the power system optimization problems, due to their ability to handle complex optimization functions and constraints. Many of them have been successfully applied for TNEP. The biggest challenge in these techniques is the requirement of large computational efforts. This paper uses a two-stage solution process to solve the TNEP problems. The first stage uses compensation based method to generate a quick, suboptimal solution. The valuable information contained in this solution is used to generate a set of heuristics aimed at drastically reducing the number of population for fitness evaluations required in the 2nd stage with application of metaheuristic method. The resulting hybrid approach produces very good quality solutions very efficiently. Results for 24 bus and 93 bus test systems have been obtained with the proposed method to ascertain the potential of the method in comparison to earlier approaches.

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A Novel Methodology for Adaptive Coordination of Multiple Controllers in Electrical Grids

Mathematics ◽

10.3390/math9131474 ◽

2021 ◽

Vol 9 (13) ◽

pp. 1474

Author(s):

Ruben Tapia-Olvera ◽

Francisco Beltran-Carbajal ◽

Antonio Valderrabano-Gonzalez ◽

Omar Aguilar-Mejia

Keyword(s):

Power Systems ◽

Power System ◽

Electric Power ◽

Large Scale ◽

Short Circuit ◽

Dynamic Performance ◽

Low Frequency ◽

Electric Power System ◽

Design Stage ◽

Positive Interaction

This proposal is aimed to overcome the problem that arises when diverse regulation devices and controlling strategies are involved in electric power systems regulation design. When new devices are included in electric power system after the topology and regulation goals were defined, a new design stage is generally needed to obtain the desired outputs. Moreover, if the initial design is based on a linearized model around an equilibrium point, the new conditions might degrade the whole performance of the system. Our proposal demonstrates that the power system performance can be guaranteed with one design stage when an adequate adaptive scheme is updating some critic controllers’ gains. For large-scale power systems, this feature is illustrated with the use of time domain simulations, showing the dynamic behavior of the significant variables. The transient response is enhanced in terms of maximum overshoot and settling time. This is demonstrated using the deviation between the behavior of some important variables with StatCom, but without or with PSS. A B-Spline neural networks algorithm is used to define the best controllers’ gains to efficiently attenuate low frequency oscillations when a short circuit event is presented. This strategy avoids the parameters and power system model dependency; only a dataset of typical variable measurements is required to achieve the expected behavior. The inclusion of PSS and StatCom with positive interaction, enhances the dynamic performance of the system while illustrating the ability of the strategy in adding different controllers in only one design stage.

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Towards a direct test for large scale electric power system instabilities

10.1109/cdc.1985.268474 ◽

1985 ◽

Cited By ~ 9

Author(s):

Robert Thomas ◽

James Thorp

Keyword(s):

Power System ◽

Electric Power ◽

Large Scale ◽

Electric Power System ◽

Direct Test

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Optimum Selection of Hydraulic Devices for Water Hammer Control in the Pipeline Systems Using Genetic Algorithm

Volume 1: Fora, Parts A, B, C, and D ◽

10.1115/fedsm2003-45262 ◽

2003 ◽

Cited By ~ 3

Author(s):

Bong Seong Jung ◽

Bryan W. Karney

Keyword(s):

Genetic Algorithm ◽

Steady State ◽

Optimization Problems ◽

System Optimization ◽

Water Hammer ◽

Pipeline System ◽

Optimal Size ◽

Protection Strategy ◽

Hydraulic Devices ◽

Selection Of

Genetic algorithms have been used to solve many water distribution system optimization problems, but have generally been limited to steady state or quasi-steady state optimization. However, transient events within pipe system are inevitable and the effect of water hammer should not be overlooked. The purpose of this paper is to optimize the selection, sizing and placement of hydraulic devices in a pipeline system considering its transient response. A global optimal solution using genetic algorithm suggests optimal size, location and number of hydraulic devices to cope with water hammer. This study shows that the integration of a genetic algorithm code with a transient simulator can improve both the design and the response of a pipe network. This study also shows that the selection of optimum protection strategy is an integrated problem, involving consideration of loading condition, device and system characteristics, and protection strategy. Simpler transient control systems are often found to outperform more complex ones.

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