A novel stochastic fractal search algorithm for optimal allocation of distributed generators in radial distribution systems

2018 ◽  
Vol 70 ◽  
pp. 773-796 ◽  
Author(s):  
Tri Phuoc Nguyen ◽  
Dieu Ngoc Vo
Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-36
Author(s):  
Le Chi Kien ◽  
Thuan Thanh Nguyen ◽  
Bach Hoang Dinh ◽  
Thang Trung Nguyen

In this paper, a proposed modified stochastic fractal search algorithm (MSFS) is applied to find the most appropriate site and size of capacitor banks for distribution systems with 33, 69, and 85 buses. Two single-objective functions are considered to be reduction of power loss and reduction of total cost of energy loss and capacitor investment while satisfying limit of capacitors, limit of conductor, and power balance of the systems. MSFS was developed by performing three new mechanisms including new diffusion mechanism and two new update mechanisms on the conventional stochastic fractal search algorithm (SFS). As a result, MSFS can reduce 0.002%, 0.003%, and 0.18% of the total power loss from SFS for the three study systems. As compared to other methods, MSFS can reduce power loss from 0.07% to 3.98% for the first system, from 3.7% to 7.3% for the second system, and from 0.92% to 6.98% for the third system. For the reduction of total cost, the improvement level of the proposed method over SFS and two other methods is more significant. It is 0.03%, 1.22%, and 5.76% for the second system and 2.31%, 0.87%, and 3.77% for the third system. It is emphasized that the proposed method can find the global optimal solutions for all study cases while SFS was still implementing search process nearby or far away from the solutions. Furthermore, MSFS can converge to the best solutions much faster than these compared methods. Consequently, it can be concluded that the proposed method is very effective for finding the best location and size of added capacitors in distribution power systems.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Tung Tran The ◽  
Dieu Vo Ngoc ◽  
Nguyen Tran Anh

This paper proposes a chaotic stochastic fractal search algorithm (CSFSA) method to solve the reconfiguration problem for minimizing the power loss and improving the voltage profile in distribution systems. The proposed method is a metaheuristic method developed for overcoming the weaknesses of the conventional SFSA with two processes of diffuse and update. In the first process, new points will be created from the initial points by the Gaussian walk. For the second one, SFSA will update better positions for the particles obtained in the diffusion process. In addition, this study has also integrated the chaos theory to improve the SFSA diffusion process as well as increase the rate of convergence and the ability to find the optimal solution. The effectiveness of the proposed CSFSA has been verified on the 33-bus, 84-bus, 119-bus, and 136-bus distribution systems. The obtained results from the test cases by CSFSA have been verified to those from other natural methods in the literature. The result comparison has indicated that the proposed method is more effective than many other methods for the test systems in terms of power loss reduction and voltage profile improvement. Therefore, the proposed CSFSA can be a very promising potential method for solving the reconfiguration problem in distribution systems.


2021 ◽  
Vol 264 ◽  
pp. 04084
Author(s):  
Ikrom Khonturaev ◽  
Mansur Khasanov ◽  
Muhiddin Anarbaev ◽  
Abror Kurbanov ◽  
Anvar Suyarov ◽  
...  

In recent years the use of renewable energy sources (RES) by many power grid companies worldwide has increased significantly. The trend towards RES use is mainly due to environmental issues and rising fuel prices associated with conventional electricity generation. This paper introduces a hybrid approach to find the optimal location and size of distributed generations (DG) in the radial distribution system (RDS). The proposed approach is based on the atom search optimization (ASO) technique to calculate the optimal allocation of DGs and power loss sensitivity (PLS) index to obtain the best buses for DGs installation in RDS. The presented approach is applied to IEEE 33-bus RDS to increase voltage profile and minimize the power losses. The results obtained prove that the developed approach can be highly effective in integrating DG into RDS compared to many other methods in the literature.


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