Power Loss Reduction Using MOALO Technique: Enhancing Power System

This research focuses on minimizing power losses in distribution networks by integrating renewable energy sources through AI techniques. Distribution networks often experience significant losses due to factors such as line resistance, unbalanced loads, and inefficient power distribution. The study aims to develop an AI-based approach, specifically using the MOALO, to identify high-loss areas within the distribution network and optimize the bus system by injecting the renewable energy sources. The proposed methodology involves utilizing solar power to reduce the total power loss and MOALO will optimize the bus network. By employing MOALO, the research considers multiple objectives, such as power losses and voltage stability, to enhance renewable energy integration. Through extensive data collection and simulation, the study evaluates the effectiveness of the AI technique in reducing power losses. Key metrics include power loss reduction, voltage stability improvement, and renewable energy utilization efficiency. The findings of this research contribute to the advancement of sustainable energy systems by providing strategies for optimizing renewable energy integration and mitigating power losses in distribution networks. Overall, this study provides valuable insights into the potential of AI techniques to enhance the efficiency and sustain ability of electrical distribution networks.

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Publication Details

Published
2024-09-02
DOI
https://doi.org/10.1109/upec61344.2024.10892430
Primary Topic
Energy Load and Power Forecasting
Type
article
Field-Weighted Citation Impact
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article

Power Loss Reduction Using MOALO Technique: Enhancing Power System

Aripriharta Aripriharta, Ahmad Asri Abd Samat, Stephen Robson, W Widjonarko et al.
Energy Load and Power Forecasting
article

Power Loss Reduction Using MOALO Technique: Enhancing Power System

Aripriharta Aripriharta, Ahmad Asri Abd Samat, Stephen Robson, W Widjonarko, Miszaina Osman, Saodah Omar
article en

Abstract

This research focuses on minimizing power losses in distribution networks by integrating renewable energy sources through AI techniques. Distribution networks often experience significant losses due to factors such as line resistance, unbalanced loads, and inefficient power distribution. The study aims to develop an AI-based approach, specifically using the MOALO, to identify high-loss areas within the distribution network and optimize the bus system by injecting the renewable energy sources. The proposed methodology involves utilizing solar power to reduce the total power loss and MOALO will optimize the bus network. By employing MOALO, the research considers multiple objectives, such as power losses and voltage stability, to enhance renewable energy integration. Through extensive data collection and simulation, the study evaluates the effectiveness of the AI technique in reducing power losses. Key metrics include power loss reduction, voltage stability improvement, and renewable energy utilization efficiency. The findings of this research contribute to the advancement of sustainable energy systems by providing strategies for optimizing renewable energy integration and mitigating power losses in distribution networks. Overall, this study provides valuable insights into the potential of AI techniques to enhance the efficiency and sustain ability of electrical distribution networks.

State University of Malang (ID), Hospital Pulau Pinang (MY), Universitas Jember (ID), Cardiff University (GB), Universiti Teknologi MARA (MY)
Affordable and clean energy
Openalex Percentile: Top 74%
Energy Load and Power Forecasting
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