Chaotic Mutation Immune Evolutionary Programming for Voltage Security with the Presence of DGPV

<p>Due to environmental concern and certain constraint on building a new power plant, renewable energy particularly distributed generation photovoltaic (DGPV) has becomes one of the promising sources to cater the increasing energy demand of the power system. Furthermore, with appropriate location and sizing, the integration of DGPV to the grid will enhance the voltage stability and reduce the system losses. Hence, this paper proposed a new algorithm for DGPV optimal location and sizing of a transmission system based on minimization of Fast Voltage Stability Index (FVSI) with considering the system constraints. Chaotic Mutation Immune Evolutionary Programming (CMIEP) is developed by integrating the piecewise linear chaotic map (PWLCM) in the mutation process in order to increase the convergence rate of the algorithm. The simulation was applied on the IEEE 30 bus system with a variation of loads on Bus 30. The simulation results are also compared with Evolutionary Programming (EP) and Chaotic Evolutionary Programming (CEP) and it is found that CMIEP performed better in most of the cases.</p>

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Index-based transmission for distributed generation in voltage stability and loss control incorporating optimization technique

IAES International Journal of Artificial Intelligence (IJ-AI) ◽

10.11591/ijai.v9.i2.pp244-251 ◽

2020 ◽

Vol 9 (2) ◽

pp. 244

Author(s):

Fareed Danial Ahmad Kahar ◽

Ismail Musirin ◽

Muhamad Faliq Mohamad Nazer ◽

Shahrizal Jelani ◽

Mohd Helmi Mansor

Keyword(s):

Distributed Generation ◽

Optimization Algorithm ◽

Voltage Stability ◽

Optimization Technique ◽

Stability Index ◽

Test System ◽

Voltage Security ◽

Grasshopper Optimization Algorithm ◽

Grasshopper Optimization ◽

Loss Control

<span lang="EN-US">The integration of Distributed Generation (DG) in a distribution network may significantly affect distribution performance. With the penetration of DG, voltage security is no longer an issue in the transmission network. This paper presents a study of Distributed Generation on the IEEE 26-Bus Reliability Test System (RTS) with the use of Fast Voltage Stability Index (FVSI) for determining its location and incorporated with Grasshopper Optimization Algorithm (GOA) to optimize the sizing of the DG. The study emphasizes the power loss of the system in which a comparison between Evolutionary Programming (EP) and Grasshopper Optimization Algorithm is done to determine which optimization technique gives an optimal result for the DG solution. The results show that the proposed algorithm is able to provide a slightly better result compared to EP.</span>

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Optimization of Real Power Loss and Voltage Stability Index for Distribution Systems with Distributed Generation

International Journal of Engineering Research in Africa ◽

10.4028/www.scientific.net/jera.33.100 ◽

2017 ◽

Vol 33 ◽

pp. 100-114 ◽

Cited By ~ 2

Author(s):

Mostafa Elshahed ◽

Mahmoud Dawod ◽

Zeinab H. Osman

Keyword(s):

Genetic Algorithm ◽

Distributed Generation ◽

Distribution Systems ◽

Voltage Stability ◽

Reactive Power ◽

Optimization Problems ◽

Stability Index ◽

Mixed Integer ◽

Voltage Profile ◽

Voltage Stability Index

Integrating Distributed Generation (DG) units into distribution systems can have an impact on the voltage profile, power flow, power losses, and voltage stability. In this paper, a new methodology for DG location and sizing are developed to minimize system losses and maximize voltage stability index (VSI). A proper allocation of DG has to be determined using the fuzzy ranking method to verify best compromised solutions and achieve maximum benefits. Synchronous machines are utilized and its power factor is optimally determined via genetic optimization to inject reactive power to decrease system losses and improve voltage profile and VSI. The Augmented Lagrangian Genetic Algorithm with nonlinear mixed-integer variables and Non-dominated Sorting Genetic Algorithm have been implemented to solve both single/multi-objective function optimization problems. For proposed methodology effectiveness verification, it is tested on 33-bus and 69-bus radial distribution systems then compared with previous works.

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A Novel Spatial Obstructed Distance by Dynamic Piecewise Linear Chaotic Map and Dynamic Nonlinear PSO

Lecture Notes in Computer Science - Advances in Swarm Intelligence ◽

10.1007/978-3-642-13498-2_61 ◽

2010 ◽

pp. 468-475

Author(s):

Xueping Zhang ◽

Yawei Liu ◽

Jiayao Wang ◽

Haohua Du

Keyword(s):

Piecewise Linear ◽

Chaotic Map ◽

Piecewise Linear Chaotic Map

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Swarm-Intelligence-Based Optimal Placement and Sizing of Distributed Generation in Distribution Network

Advances in Systems Analysis, Software Engineering, and High Performance Computing - Applied Computational Intelligence and Soft Computing in Engineering ◽

10.4018/978-1-5225-3129-6.ch002 ◽

2018 ◽

pp. 29-48 ◽

Cited By ~ 1

Author(s):

Mahesh Kumar ◽

Perumal Nallagownden ◽

Irraivan Elamvazuthi ◽

Pandian Vasant ◽

Luqman Hakim Rahman

Keyword(s):

Distributed Generation ◽

Radial Distribution ◽

Distribution System ◽

Voltage Stability ◽

Reactive Power ◽

Distribution Network ◽

Stability Index ◽

Pso Algorithm ◽

Distribution Networks ◽

Optimal Placement

In the distribution system, distributed generation (DG) are getting more important because of the electricity demands, fossil fuel depletion and environment concerns. The placement and sizing of DGs have greatly impact on the voltage stability and losses in the distribution network. In this chapter, a particle swarm optimization (PSO) algorithm has been proposed for optimal placement and sizing of DG to improve voltage stability index in the radial distribution system. The two i.e. active power and combination of active and reactive power types of DGs are proposed to realize the effect of DG integration. A specific analysis has been applied on IEEE 33 bus system radial distribution networks using MATLAB 2015a software.

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GENERALIZED ARITHMETIC CODING USING DISCRETE CHAOTIC MAPS

International Journal of Bifurcation and Chaos ◽

10.1142/s0218127412502562 ◽

2012 ◽

Vol 22 (10) ◽

pp. 1250256 ◽

Cited By ~ 9

Author(s):

QIUZHEN LIN ◽

KWOK-WO WONG ◽

JIANYONG CHEN

Keyword(s):

Chaotic Maps ◽

Piecewise Linear ◽

Chaotic Map ◽

Interval Mapping ◽

International Standards ◽

Arithmetic Coding ◽

Initial Value ◽

Compression Performance ◽

Piecewise Linear Chaotic Map ◽

Generalized Arithmetic

Making use of the Lebesgue measure preserving property of the piecewise linear chaotic map, a discrete piecewise linear chaotic map is employed to perform the generalized arithmetic coding, which is an optimal entropy coding algorithm adopted by international standards. After a number of message symbols have been encoded by the reverse interval mapping, an enlargement on the encoding interval is performed and some codeword bits are exported accordingly. Based on the enlarged encoding interval, the subsequent symbols are encoded with the modified chaotic maps, the lower and upper bounds of which are determined by the final encoding interval of the symbols already encoded. In the decoding process, the message symbols are recovered by iterating the corresponding chaotic map from an appropriate initial value. The encoding interval enlargement is tracked by performing reverse interval mapping on the decoded symbols. More codeword bits are shifted into the register to form the initial value for decoding the subsequent symbols. Simulation results verify that the compression performance of our scheme is very close to the entropy bound and is comparable to traditional finite-precision arithmetic coding. In addition, cryptographic capability can be integrated into our scheme to make it a joint compression and encryption scheme. Its security is enhanced when compared with the existing schemes based on traditional arithmetic coding.

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A Novel Joint for Image Encryption and Coding Using Piecewise Linear Chaotic Map

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2016.5683 ◽

2016 ◽

Vol 13 (10) ◽

pp. 7137-7143

Author(s):

Bin Wang ◽

Shihua Zhou ◽

Changjun Zhou ◽

Xuedong Zheng

Keyword(s):

Image Encryption ◽

Binary Data ◽

Piecewise Linear ◽

Chaotic Map ◽

Secret Key ◽

Initial Value ◽

Tent Map ◽

Piecewise Linear Chaotic Map ◽

Plain Image ◽

Gray Level Image

Due to the features of chaotic maps, they are widely used into encrypting and coding information. Inspired by the tent map which is used to code and encrypt binary data, a novel joint for image encryption and coding based on piecewise linear chaotic map is proposed in this paper. We divide piecewise linear chaotic map into 256 parts according to the property of gray level image. In order to enhance the security of image, the image is subsequently encrypted by the piecewise linear chaotic map in which the secret key of image encryption is determined by the initial of chaotic map. This stage of image encryption possesses high key and plain-image sensitivities which results from the secret key related to plain-image. Finally, the encrypted image is coded by the piecewise linear chaotic map with a different initial value. The experimental results validate the effect of the proposed system and demonstrate that the encrypted and coded image is secure for transmission.

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