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IJEETC 2024 Vol.13(2): 112-124
doi: 10.18178/ijeetc.13.2.112-124

Intelligent ANFIS-Based Distributed Generators Energy Control and Power Dispatch of Grid- Connected Microgrids Integrated into Distribution Network

Ebenezer Narh Odonkor1,*, Peter Musau Moses2, and Aloys Oriedi Akumu3
1. Pan African University Institute for Basic Sciences, Technology and Innovation (PAUSTI), Kenya
2. Department of Electrical, Electronic and Information Engineering, South Eastern Kenya University, Kenya
3. Department of Electrical Engineering, Tshwane University of Technology, South Africa
Email: ebenezer.narh.odonkor@ttu.edu.gh (E.N.O.), pemosmusa@gmail.com (P.M.M.), akumuao@tut.ac.za (A.O.A.)
*Corresponding author

Manuscript received November 8, 2023; revised January 1, 2024; accepted January 9, 2024.

Abstract—Power supply management is a critical problem in the operation of a distribution network, considering the causes of large power losses and interruptions in the main grid caused by the unknown connection of loads and DGs that affect power delivery to customers downstream of a distribution network. The above-mentioned problems can be reduced by the integration of microgrids close to load centers and developing a controller using adaptive control techniques to enhance reliable power supply. For this reason, this paper presents an intelligent method for distributed generators' energy control and power dispatch of microgrids integrated into a distribution network employing an Adaptive Neuro- Fuzzy Inference System (ANFIS). The aim is to control distributed generators energy sources, loads, and power dispatch of grid-connected microgrids among multiconnected power sources to maintain a stable power supply without using any optimization techniques. The proposed intelligent ANFIS system is trained for power-sharing purposes and applied to the microgrid controllers. The mathematical modeling of distributed generators, system design, simulation, and testing of the proposed method were done using MATLAB/Simulink software. The results show that the proposed controller is capable of power dispatch and controls the energy harvest of distributed generators. Additionally, it can assign microgrid power source(s) to additional load(s) connected to the active distribution network without interruptions of power flow. The obtained results outperform similar works that used hybrid ANFISPID (Adaptive Neural Fuzzy Inference System-Proportional- Integral-Derivative), PSO-ANFIS (Particle Swarm Optimization-Adaptive Neural Fuzzy Inference System), and GA-ANFIS (Genetic Algorithm-Adaptive Neuro-Fuzzy Inference System) by automatically connecting and controlling distributed generators energy sources with effective power dispatch in mitigating downtime of grid power operations.

Index Terms—Adaptive Neuro-Fuzzy Inference System (ANFIS) controller, distributed energy resources, distribution network, microgrids, power dispatch

Cite: Ebenezer Narh Odonkor, Peter Musau Moses, and Aloys Oriedi Akumu, "Intelligent ANFIS-Based Distributed Generators Energy Control and Power Dispatch of Grid- Connected Microgrids Integrated into Distribution Network," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 13, No. 2, pp. 112-124, 2024. doi: 10.18178/ijeetc.13.2.112-124

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.