Meta-heuristic matrix moth–flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability

2020 ◽  
Vol 20 ◽  
pp. 101118 ◽  
Author(s):  
Ali Jafar-Nowdeh ◽  
Manoochehr Babanezhad ◽  
Saber Arabi-Nowdeh ◽  
Amirreza Naderipour ◽  
Hesam Kamyab ◽  
...  
Keyword(s):  
Distribution Networks ◽  
Renewable Sources ◽  
Optimal Reconfiguration

scholarly journals Optimal Reconfiguration of Distribution Networks Using Hybrid Heuristic-Genetic Algorithm

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1544 ◽  
Author(s):  
Damir Jakus ◽  
Rade Čađenović ◽  
Josip Vasilj ◽  
Petar Sarajčev
Keyword(s):  
Distribution Network ◽  
Distribution Networks ◽  
Total Power ◽  
Computational Time ◽  
Small Scale ◽  
Network Reconfiguration ◽  
Optimal Distribution ◽  
Voltage Profile ◽  
Distribution Network Reconfiguration ◽  
Optimal Reconfiguration

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.

Optimal Configuration and Reconfiguration of Electric Distribution Networks

2011 ◽  
pp. 268-292
Author(s):  
Armin Ebrahimi Milani ◽  
Mahmood Reza Haghifam
Keyword(s):  
Power Loss ◽  
Optimization Procedure ◽  
Distribution Networks ◽  
Time Varying ◽  
High Quality ◽  
Sample Distribution ◽  
Power Loss Reduction ◽  
The Status ◽  
Optimal Reconfiguration ◽  
Practical Scheme

Power loss reduction can be considered as one of the main purposes for a distribution system’s designers and operators, especially for recent non-governmental networks. Moreover, the nature of power loss challenges different methods to solve this problem, while various studies indicate effectiveness of reconfiguration and its high portion for this case. Thus, “reconfiguration” can be introduced as an optimization procedure to obtain economical high quality operation by changing the status of sectionalizing switches in these networks. Some major points such as using different switch types, considering number of switching and time varying loads, which are almost neglected or not applied simultaneously in most pervious essays, are the main motivation to propose this chapter. A heuristic practical scheme is proposed to perform optimal reconfiguration, and all previous neglected topics are fully discussed. Proposed method will apply to sample distribution networks, and the effectiveness of this method will be discussed through several case studies and comparisons.

Hosting Capacity Maximization Based on Optimal Reconfiguration of Distribution Networks with Optimized Soft Open Point Operation

2020 ◽  
pp. 179-193
Author(s):  
Ibrahim Mohamed Diaaeldin ◽  
Shady H. E. Abdel Aleem ◽  
Ahmed El-Rafei ◽  
Almoataz Y. Abdelaziz ◽  
Ahmed F. Zobaa
Keyword(s):  
Distribution Networks ◽  
Capacity Maximization ◽  
Optimal Reconfiguration ◽  
Open Point
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