Application of Immune Log-Normal Evolutionary Programming in Distributed Generation Installation

2017 ◽  
Vol 6 (3) ◽  
pp. 730
Author(s):  
M. H. Mansor ◽  
I. Musirin ◽  
M. M. Othman ◽  
S. A. Shaaya ◽  
S. A. Syed Mustaffa
Keyword(s):  
Power System ◽  
Distributed Generation ◽  
Evolutionary Programming ◽  
Test System ◽  
Optimal Location ◽  
Total System ◽  
Transmission Network ◽  
Artificial Immune ◽  
A New Technique ◽  
Log Normal

<p>Nowadays, the location and sizing of distributed generation (DG) units in power system network are crucial to be at optimal as it will affect the power system operation in terms of stability and security. In this paper, a new technique termed as Immune Log-Normal Evolutionary Programming (ILNEP) is applied to find the optimal location and size of distributed generation units in power system network. Voltage stability is considered in solving this problem. The proposed technique has been tested on the IEEE 26 bus Reliability Test System to find the optimal location and size of distributed generation in transmission network. In order to study the performance of ILNEP technique in solving DG Installation problem, the results produced by ILNEP were compared with other meta-heuristic techniques like evolutionary programming (EP) and artificial immune system (AIS). It is found that the proposed technique gives better solution in term of lower total system loss compared to the other two techniques.<em></em></p>

Impact of Distributed Generation on the Fault Current in Power Distribution System

2017 ◽  
Vol 6 (2) ◽  
pp. 357
Author(s):  
Zuhaila Mat Yasin ◽  
Izni Nadhirah Sam’ón ◽  
Norziana Aminudin ◽  
Nur Ashida Salim ◽  
Hasmaini Mohamad
Keyword(s):  
Power System ◽  
Distributed Generation ◽  
Power Distribution ◽  
Distribution System ◽  
Test System ◽  
Optimal Location ◽  
Fault Current ◽  
Double Line ◽  
Power Distribution System ◽  
The Impact

<p>Monitoring fault current is very important in power system protection. Therefore, the impact of installing Distributed Generation (DG) on the fault current is investigated in this paper. Three types of fault currents which are single line-to-ground, double line-to-ground and three phase fault are analyzed at various fault locations. The optimal location of DG was identified heuristically using power system simulation program for planning, design and analysis of distribution system (PSS/Adept). The simulation was conducted by observing the power losses of the test system by installing DG at each load buses. Bus with minimum power loss was chosen as the optimal location of DG. In order to study the impact of DG to the fault current, various locations and sizes of DG were also selected. The simulations were conducted on IEEE 33-bus distribution test system and IEEE 69-bus distribution test system. The results showed that the impact of DG to the fault current is significant especially when fault occurs at busses near to DG location.</p>

Prediction of Undervoltage Load Shedding Using Quantum-Inspired Evolutionary Programming-Support Vector Machine

2015 ◽  
Vol 785 ◽  
pp. 43-47
Author(s):  
Zuhaila Mat Yasin ◽  
Zuhaina Zakaria ◽  
Titik Khawa Abdul Rahman
Keyword(s):  
Support Vector Machine ◽  
Computation Time ◽  
Evolutionary Programming ◽  
Test System ◽  
Least Square ◽  
Support Vector ◽  
Rbf Kernel ◽  
Validation Procedure ◽  
Programming Support ◽  
A New Technique

This paper presents a new technique to predict the optimal amount of load to be shed at various loading conditions using Quantum-Inspired Evolutionary Programming–Support Vector Machine (QIEP-SVM). QIEP is utilised to optimise the RBF Kernel parameters in Least-Square Support Vector Machine (LS-SVM). The objective of the optimisation is to minimise the mean square error (MSE). The performance of QIEP-SVM technique was compared with those obtained from LS-SVM technique with prediction accuracy through a 10-fold cross-validation procedure. All simulations in this study were carried out using IEEE 69-bus distribution test system. QIEP-SVM model had shown better prediction performance as compared to LS-SVM. The results also indicate that the proposed approach outperforms the most recently reported technique in terms of accuracy and fast computation time.

scholarly journals Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system

2019 ◽  
Vol 8 (3) ◽  
pp. 978-984
Author(s):  
Nur Ainna Shakinah Abas ◽  
Ismail Musirin ◽  
Shahrizal Jelani ◽  
Mohd Helmi Mansor ◽  
Naeem M. S. Honnoon ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Distributed Generation ◽  
Distribution System ◽  
Optimization Technique ◽  
Evolutionary Programming ◽  
Test System ◽  
Voltage Profile ◽  
Power Losses ◽  
Programming Technique ◽  
Distributed Generations

This paper presents the optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simulation is used to find the random number of locations of MDGs. This involved the testing of the proposed technique on IEEE 69-bus distribution test system. It is found that the proposed approach successfully solved the MDGs installation problem by reducing the power losses and improving the minimum voltage of the distribution system.

scholarly journals Multi-Objective Immune-Commensal-Evolutionary Programming for Total Production Cost and Total System Loss Minimization via Integrated Economic Dispatch and Distributed Generation Installation

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7733
Author(s):  
Mohd Helmi Mansor ◽  
Ismail Musirin ◽  
Muhammad Murtadha Othman
Keyword(s):  
Distributed Generation ◽  
Production Cost ◽  
Optimization Technique ◽  
Economic Dispatch ◽  
Evolutionary Programming ◽  
Production Costs ◽  
Total System ◽  
Total Production ◽  
Multi Objective Optimization ◽  
Multi Objective

Economic Dispatch (ED) problems have been solved using single-objective optimization for so long, as Grid System Operators (GSOs) previously only focused on minimizing the total production cost. In modern power systems, GSOs require not only optimizing the total production cost but also, at the same time, optimizing other important objectives, such as the total emissions of the greenhouse gasses, total system loss and voltage stability. This requires a suitable multi-objective optimization approach in ensuring the ED solution produced is satisfying all the objectives. This paper presents a new multi-objective optimization technique termed Multi-Objective Immune-Commensal-Evolutionary Programming (MOICEP) for minimizing the total production cost and total system loss via integrated Economic Dispatch and Distributed Generation installation (ED-DG). This involved the application of a weighted-sum multi-objective approach that combined with an optimization technique called Immune-Commensal-Evolutionary Programming (ICEP). The proposed MOICEP has been compared with other multi-objective techniques, which are Multi-Objective-Evolutionary Programming (MOEP) and Multi-Objective-Artificial Immune System (MOAIS). It was found that MOICEP performs very well in producing better optimization results for all the three types of Economic Dispatch (ED) problems compared to MOEP and MOAIS in terms of cheap total production costs and low total system loss.

scholarly journals Optimal Placement and Sizing of SVC for Improving Voltage Profile of Power System

2011 ◽  
pp. 146-150
Author(s):  
Shraddha Udgir ◽  
Sarika Varshney ◽  
Laxmi Srivastava
Keyword(s):  
Power Systems ◽  
Power System ◽  
Capital Investment ◽  
Reactive Power ◽  
Test System ◽  
Vital Role ◽  
Optimal Location ◽  
Optimal Placement ◽  
Voltage Profile ◽  
Stability Margins

In emerging electric power systems, increased transactions often lead to the situations where the system no longer remains in secure operating region. The flexible AC transmission system (FACTS) controllers can play a vital role in the power system security enhancement. However, due to high capital investment, it is necessary to place these controllers optimally in a power system. FACTS devices can regulate the active and reactive power control as well as adaptive to voltage-magnitude control simultaneously because of their flexibility and fast control characteristics. Placement of these devices at optimal location can lead to control in line flow and maintain bus voltages in desired level and so improve voltage profile and stability margins. This paper proposes a systematic method for finding optimal location of SVC to improve voltage profile of a power system. A contingency analysis to determine the critical outages with respect to voltage security is also examined in order to evaluate the effect of SVC on the location analysis. Effectiveness of the proposed method is demonstrated on IEEE 30-bus test system.

A Multi-objective Hybrid Heuristic Approach for Optimal Setting of FACTS Devices in Power System Operation

2016 ◽  
Vol 5 (3) ◽  
pp. 120
Author(s):  
Sai Ram Inkollu ◽  
Venkata Reddy Kota
Keyword(s):  
Power System ◽  
Power Flow ◽  
Transmission Loss ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Test System ◽  
Optimal Location ◽  
Voltage Profile ◽  
Loss Minimization ◽  
Facts Devices

<p>Improvement of power system performance in terms of increased voltage profile and decreased transmission loss is becoming one of the challenging tasks to the system operators under open access environment. Apart from traditional power flow controlling devices, use of Flexible AC Transmission System (FACTS) devices can give an attractive solution for the operation and control of deregulated power system. The type, size, location and number of FACTS devices are to be optimized appropriately in order to get the targeted benefits. In this paper, two FACTS devices, Thyristor Controller Phase Shift Transformer (TCPST) and Interline Power Flow Controller (IPFC) are selected to obtain the required performance such as improvement of voltage profile and loss minimization. To search the optimal location and optimal rating of the selected FACTS devices, a hybrid algorithm which formulated with Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) is proposed. At the first step, the optimization problem is solved for finding the optimal location of FACTS devices using PSO with an objective of voltage profile maximization and later GSA is implemented to optimize their parameters with an objective of transmission loss minimization. The proposed method is implemented on IEEE 30-bus test system and from the simulation results it can be proved that this technique is well suited for real-time application.  </p><p align="center"><strong><br /></strong></p>

Optimal DG Placement with the Aim of Profits Maximization

2016 ◽  
Vol 1 (2) ◽  
pp. 249 ◽  
Author(s):  
Sobhan Dorahaki
Keyword(s):  
Distributed Generation ◽  
Power Plants ◽  
Test System ◽  
Optimal Location ◽  
System Capacity ◽  
Economic Calculation ◽  
Power Networks ◽  
Correct Location ◽  
Voltage Support ◽  
Generation Power

<p>Using distributed generation power plants is common due to advantages such as system capacity release, voltage support and reduced energy losses in power networks. Prior to the creation of distributed generation plants (DG), economic calculation is needed in order to find the optimum location. In this study, IEEE 57 bus test system is evaluated using two index of LMP and CP. Then, the optimal location of distributed generation plants is studied in experimental network. Finally, the effects of DG correct location on buses LMP after DG installation is studied.</p>

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