Restore Power Losses using the Hybrid of the Minimum Spanning Tree and Backward Forward Sweep

Meriem M'dioud, Rachid Bannari, Ismail Elkafazi

2021

Abstract

Reconfiguration of the electrical network is a famous tool still used to reduce losses. This method focused on the changing of the topological state of the switching lines in the system. In this paper, the aim is to restore the active power loss and upgrade the voltage profile at each node. This problem will be solved for the case of the network without distribution generation units (DGs) and the case of the network with the presence of the DGs because the injection of this last one at a non-optimal node gives rise to unnecessary losses and the violation of the voltage out of the range limits. This reconfiguration will be done by using the prim’s algorithm. Next, we apply the Backward Forward Sweep approach (BFS), aiming to check our proposed constraints. By selecting the algorithm, total losses were chosen as an objective function by considering the resistance of the edges as the weight of lines. The electrical network of 33 nodes with and without DGs was presented to prove the efficiency of our proposed method. The simulation results prove that this algorithm is perfect for finding good results (reduce losses, and improve voltage).

Paper Citation

in Harvard Style

M'dioud M., Bannari R. and Elkafazi I. (2021). Restore Power Losses using the Hybrid of the Minimum Spanning Tree and Backward Forward Sweep. In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML, ISBN 978-989-758-559-3, pages 108-118. DOI: 10.5220/0010729400003101

in Bibtex Style

@conference{bml21,
author={Meriem M'dioud and Rachid Bannari and Ismail Elkafazi},
title={Restore Power Losses using the Hybrid of the Minimum Spanning Tree and Backward Forward Sweep},
booktitle={Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,},
year={2021},
pages={108-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010729400003101},
isbn={978-989-758-559-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,
TI - Restore Power Losses using the Hybrid of the Minimum Spanning Tree and Backward Forward Sweep
SN - 978-989-758-559-3
AU - M'dioud M.
AU - Bannari R.
AU - Elkafazi I.
PY - 2021
SP - 108
EP - 118
DO - 10.5220/0010729400003101