scholarly journals A Nondominated Sorting Stochastic Fractal Search Algorithm for Multiobjective Distribution Network Reconfiguration with Distributed Generations

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Tung Tran The ◽  
Bao-Huy Truong ◽  
Khanh Dang Tuan ◽  
Dieu Vo Ngoc

This paper aims to propose a new multiobjective algorithm for multiobjective distributed network reconfiguration (DNR) with the placements of distributed generation (DG) in radial distribution networks (RDNs). The new proposed algorithm, called the nondominated sorting stochastic fractal search (NSSFS), is a new multiobjective version of the original SFS algorithm. NSSFS incorporated fast nondominated sorting strategies, crowding distance computation, and selection mechanism into SFS to find and maintain the best nondominated solutions. The proposed NSSFS algorithm was tested with eight multiobjective benchmark test functions to validate its performance. The NSSFS was then implemented to define the optimal network configuration, positions, and sizes of DG units in the RDNs, where real power loss, voltage profile, and voltage stability index were optimized simultaneously. The implementation of multiobjective DNR-DG (MODNR-DG) significantly enhanced the performance of the system. Based on the comparison outcomes, the NSSFS algorithm obtained better solution quality than other multiobjective techniques, proving the effectiveness of NSSFS in dealing with the MODNR-DG problem.

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4172 ◽  
Author(s):  
Ibrahim Diaaeldin ◽  
Shady Abdel Aleem ◽  
Ahmed El-Rafei ◽  
Almoataz Abdelaziz ◽  
Ahmed F. Zobaa

In this study, we allocated soft open points (SOPs) and distributed generation (DG) units simultaneously with and without network reconfiguration (NR), and investigate the contribution of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to distribution systems under different loading conditions. A recent meta-heuristic optimization algorithm called the discrete-continuous hyper-spherical search algorithm is used to solve the mixed-integer nonlinear problem of SOPs and DGs allocation, along with new NR methodology to obtain radial configurations in an efficient manner without the possibility of getting trapped in local minima. Further, multi-scenario studies are conducted on an IEEE 33-node balanced benchmark distribution system and an 83-node balanced distribution system from a power company in Taiwan. The contributions of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to the system, are investigated to determine the real benefits gained from their allocation. It was clear from the results obtained that simultaneous NR, SOP, and DG allocation into a distribution system creates a hybrid configuration that merges the benefits offered by radial distribution systems and mitigates drawbacks related to losses, power quality, and voltage violations, while offering a far more efficient and optimal network operation. Also, it was found that the contribution of the internal loss of SOPs to the total loss for different numbers of installed SOPs is not dependent on the number of SOPs and that loss minimization is not always guaranteed by installing more SOPs or DGs along with NR. One of the findings of the paper demonstrates that NR with optimizing tie-lines could reduce active losses considerably. The results obtained also validate, with proper justifications, that SOPs installed for the management of constraints in LV feeders could further reduce losses and efficiently address issues related to voltage violations and network losses.


Author(s):  
Ibrahim M. Diaaeldin ◽  
Shady H. E. Abdel Aleem ◽  
Ahmed El-Rafei ◽  
Almoataz Y. Abdelaziz ◽  
Ahmed F. Zobaa

In this paper, a recent meta-heuristic optimization algorithm called the discrete-continuous hyper-spherical search algorithm is used to solve the mixed-integer nonlinear problem of soft open points (SOPs) and renewable distributed generators allocation along with new network reconfiguration methodology under different loading conditions to minimize the total power loss in balanced distribution systems. Multi-scenario studies, which aim to improve the investigation of the overall performance of the strategies, are conducted on IEEE 33-node and 83-node balanced distribution systems. The contributions of SOP losses to the total active losses, as well as the effect of increasing the number of SOPs connected to the system, are investigated to determine the real benefits gained from their allocation. The results obtained validate, with proper justifications, the effectiveness of allocating both SOPs and renewable distributed generators with the proposed network reconfiguration methodology to provide the best operation of distribution networks with minimum losses and enhanced power quality performance. It was also shown that SOPs successfully assist the growing integration plans of the renewable distributed generators units and can address issues related to voltage violations and network losses efficiently.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-32
Author(s):  
Phuoc Tri Nguyen ◽  
Thi Nguyen Anh ◽  
Dieu Vo Ngoc ◽  
Tung Le Thanh

This research proposes a modified metaheuristic optimization algorithm, named as improved stochastic fractal search (ISFS), which is formed based on the integration of the quasiopposition-based learning (QOBL) and chaotic local search (CLS) schemes into the original SFS algorithm for solving the optimal capacitor placement (OCP) in radial distribution networks (RDNs). The test problem involves the determination of the optimal number, location, and size of fixed and switched capacitors at different loading conditions so that the network total yearly cost is minimized with simultaneous fulfillment of operating constraints. Also, the hourly on/off scheduling plans of switched shunt capacitors (SCs) considering a modified cost objective function are obtained. The proposed ISFS algorithm has been tested on two IEEE 69-bus and 119-bus RDNs and a practical 152-bus RDN. For clarifying the effectiveness and validation of the ISFS, the simulated results have been compared with those of other previously utilized solution approaches in the literature as well as the original SFS. From result comparison, the proposed ISFS outperforms other previous approaches regarding solution quality and statistical performance for the compared cases, especially in the complex and large-scale networks. Notably, compared with the original SFS, the proposed ISFS shows a significantly better performance in all the tested cases.


2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Tung Tran The ◽  
Sy Nguyen Quoc ◽  
Dieu Vo Ngoc

This paper proposes the Symbiotic Organism Search (SOS) algorithm to find the optimal network configuration and the placement of distributed generation (DG) units that minimize the real power loss in radial distribution networks. The proposed algorithm simulates symbiotic relationships such as mutualism, commensalism, and parasitism for solving the optimization problems. In the optimization process, the reconfiguration problem produces a large number of infeasible network configurations. To reduce these infeasible individuals and ensure the radial topology of the network, the graph theory was applied during the power flow. The implementation of the proposed SOS algorithm was carried out on 33-bus, 69-bus, 84-bus, and 119-bus distribution networks considering seven different scenarios. Simulation results and performance comparison with other optimization methods showed that the SOS-based approach was very effective in solving the network reconfiguration and DG placement problems, especially for complex and large-scale distribution networks.


Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1544 ◽  
Author(s):  
Damir Jakus ◽  
Rade Čađenović ◽  
Josip Vasilj ◽  
Petar Sarajčev

This paper describes the algorithm for optimal distribution network reconfiguration using the combination of a heuristic approach and genetic algorithms. Although similar approaches have been developed so far, they usually had issues with poor convergence rate and long computational time, and were often applicable only to the small scale distribution networks. Unlike these approaches, the algorithm described in this paper brings a number of uniqueness and improvements that allow its application to the distribution networks of real size with a high degree of topology complexity. The optimal distribution network reconfiguration is formulated for the two different objective functions: minimization of total power/energy losses and minimization of network loading index. In doing so, the algorithm maintains the radial structure of the distribution network through the entire process and assures the fulfilment of various physical and operational network constraints. With a few minor modifications in the heuristic part of the algorithm, it can be adapted to the problem of determining the distribution network optimal structure in order to equalize the network voltage profile. The proposed algorithm was applied to a variety of standard distribution network test cases, and the results show the high quality and accuracy of the proposed approach, together with a remarkably short execution time.


Author(s):  
Chinweike Innocent Amesi ◽  
Tekena Kashmony Bala ◽  
Anthony O. Ibe

This paper examined the power flow status of the Port Harcourt Town (Zone 4) distribution networks to improve the performance. The network consists of 18 injection substations fed from 4 different sizes of transformers with a total power rating of 165 MVA, 132/33kV at the Port Harcourt Town sub-transmission substation. Gauss-seidel power flow algorithm was used to analyse the network in Electrical Transient Analyzer Program software (ETAP 12.6) to determine the various bus operating voltages, power flow, and over or under-loaded Transformers’ units. From the base-case simulation results obtained, it shows that these injection distribution transformers (PH Town 106.3%, RSU 90.5%, Marine Base 86.5%, UTC 87.9%, Nzimiro 89.5%, and Borokiri 88.7%) were overloaded on the network and the operating voltages observed for (PH Town 95.1%, RSU 83.0%, Marine Base 83.4%, UTC 82.8%, Nzimiro 85.2%, and Borokiri 82.1%) indicates low voltage profile. However, using network reconfiguration technique as proposed in this paper; there was reduction in the percentage loading of the said Transformers as it was upgraded to affect positively on its lifespan with (PH Town 44.1%, RSU 65.3%, Marine Base 60.7%, UTC 47.3%, Nzimiro 61.3%, and Borokiri 52.0%) loading,  and the bus voltage profiles was improved for (PH Town 100%, RSU 98.4%, Marine Base 98.8%, UTC 98.2%, Nzimiro 98.6%, and Borokiri 99.1%) with additional facilities. It is recommended that the power infrastructure facilities in Port Harcourt Town distribution network be immediately upgraded to reduce losses and improve the electricity supply to consumers. Also, in regard to these analyses, the sub-transmission substation requires 240 MW of power for effective power delivery.


2018 ◽  
Vol 8 (5) ◽  
pp. 3445-3449 ◽  
Author(s):  
P. Balamurugan ◽  
T. Yuvaraj ◽  
P. Muthukannan

This paper deals with a new approach implemented to decrease power losses and improve voltage profile in distribution networks using Distribution STATic COMpensator (DSTATCOM). DSTATCOM location can be determined by the voltage stability index (VSI) and sizing can be identified by nature inspired, recently developed whale optimization algorithm (WOA). To check efficacy, the proposed technique is tested on two standard buses: Indian rural electrification 28-bus and IEEE 69-bus distribution systems. Obtained results show that optimal allocation of DSTATCOM effectively reduces power losses and improves voltage profile.


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.


2011 ◽  
Vol 26 (3) ◽  
pp. 1080-1088 ◽  
Author(s):  
Rayapudi Srinivasa Rao ◽  
Sadhu Venkata Lakshmi Narasimham ◽  
Manyala Ramalinga Raju ◽  
A. Srinivasa Rao

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