A two-stage method using biogeography-based optimization for simultaneous network reconfiguration and renewable energy integration

• Main Authors: Al Samman, Mohammad, Mokhlis, Hazlie, Rahman, Mir Toufikur, Mansor, Nurulafiqah Nadzirah, Alotaibi, Majed A.
• Format: Article
• Published: AIP Publishing 2020
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/25166/; https://doi.org/10.1063/1.5144366

Renewable Energy Resources (RERs) are a promising source of energy with hardly any pollution. Due to the intermittent nature from the output power of the nondispatchable RER and the load variations in the distribution network, it is important to frequently perform Network Reconfiguration (NR) to minimize the power loss and improve the network's voltage profile. Finding the optimal NR while simultaneously considering the dispatchable RER integration is important but challenging because of the complex combinational nature of the problem, and therefore, it is commonly solved by meta-heuristic techniques. However, the conventional meta-heuristic techniques involve random initializations and normally generate many nonfeasible solutions, which obstruct the search process. With the aim of improving the accuracy and consistency of the solution, this study proposes a two-stage method using biogeography-based optimization to attain the NR simultaneously with the RER placement and sizing for the sake of minimizing power loss and voltage deviation. The first stage simplifies the distribution network and then utilizes the simplified form to provide a better set of initial solutions and to maintain the network radiality. Thereafter, the second stage finds the final NR and RER locations and sizes. The simulations are carried out on 33-bus, 69-bus, and 118-bus systems, and the results are compared with previously published methods and some well-known optimization methods. In addition, load variations and RER's uncertainty are also considered. The obtained results show that the proposed method outperforms the existing methods. The results also indicate the significance of the hourly NR in reducing power loss. © 2020 Author(s).