Microgrids (MGs) and energy communities have been widely implemented, leading to the participation of multiple stakeholders in distribution networks. Insufficient information infrastructure, particularly in rural distribution networks, is leading to a growing number of operational blind areas in distribution networks. An optimization challenge is addressed in multi-feeder microgrid systems to handle load sharing and voltage management by implementing a backward neural network (BNN) as a robust control approach. The control technique consists of a neural network that optimizes the control strategy to calculate the operating directions for each distributed generating point. Neural networks improve control during communication connectivity issues to ensure the computation of operational directions. Traditional control of DC microgrids is susceptible to communication link delays. The proposed BNN technique can be expanded to encompass the entire multi-feeder network for precise load distribution and voltage management. The BNN results are achieved through mathematical analysis of different load conditions and uncertain line characteristics in a radial network of a multi-feeder microgrid, demonstrating the effectiveness of the proposed approach. The proposed BNN technique is more effective than conventional control in accurately distributing the load and regulating the feeder voltage, especially during communication failure.

Applied Science Research Center Applied Science Private University Amman 11931 Jordan

Department of Electrical and Bio medical Engineering Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan Pakistan

Department of Electrical and Electronics Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal 576104 India

Department of Electrical Engineering Sukkur IBA University Sukkur 65200 Pakistan

Department of Industrial Engineering College of Engineering University of Business and Technology Jeddah 21448 Saudi Arabia

Energy Processes Environment and Electrical Systems Unit National Engineering School of Gabes University of Gabes Gabès 6029 Tunis Tunisia

ENET Centre VSB Technical University of Ostrava 708 00 Ostrava Czech Republic

Institute of Mathematics Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan Pakistan

MEU Research Unit Middle East University Amman 11831 Jordan

Private Higher School of Applied Sciences and Technology of Gabes University of Gabes Gabès 6029 Tunisia

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