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Optimal size and location of dispatchable distributed generators in an autonomous microgrid using Honey Badger algorithm

Nguyen Tham X., Lis Robert

Archives of Electrical Engineering

2023

Vol. 72, nr 4

871--893

The paper presents a honey badger algorithm (HB) based on a modified backward- forward sweep power flow method to determine the optimal placement of droop-controlled dispatchable distributed generations (DDG) corresponding to their sizes in an autonomous microgrid (AMG). The objectives are to minimise active power loss while considering the reduction of reactive power loss and total bus voltage deviation, and the maximisation of the voltage stability index. The proposed HB algorithm has been tested on a modified IEEE 33-bus AMG under four scenarios of the load profile at 40%, 60%, 80%, and 100% of the rated load. The analysis of the results indicates that Scenario 4, where the HB algorithm is used to optimise droop gains, the positioning of DDGs, and their reference voltage magnitudes within a permissible range, is more effective in mitigating transmission line losses than the other scenarios. Specifically, the active and reactive power losses in Scenario 4 with the HB algorithm are only 0.184% and 0.271% of the total investigated load demands, respectively. Compared to the base scenario (rated load), Scenario 4 using the HB algorithm also reduces active and reactive power losses by 41.86% and 31.54%, respectively. Furthermore, the proposed HB algorithm outperforms the differential evolution algorithm when comparing power losses for scenarios at the total investigated load and the rated load. The results obtained demonstrate that the proposed algorithm is effective in reducing power losses for the problem of optimal placement and size of DDGs in the AMG.

A Novel TVA-REPSO Technique in Solving Generators Sizing Problems for South Sulawesi Network

Jamian J. J., Mohd Zin A. A., Saini M., Mustafa M. W., Mokhlis H.

Przegląd Elektrotechniczny

2013

R. 89, nr 2a

170--174

This paper present a novel optimization method, Time Varying Acceleration – Rank Evolutionary Particle Swarm Optimization (TVAREPSO) in solving optimum generator sizing for minimising power losses in the transmission system of South Sulawesi, Indonesia. A comparison between the proposed method and three other methods was done in order to find the best method to optimize the generators’ output size. The results show that the TVA-REPSO algorithm can obtain the same performance as PSO but it only required shorter computing time and can converges faster than the original PSO.

W artykule przedstawiono matematyczną metodę rozwiązania zagadnienia znalezienia optymalnego rozmiaru generatora, w celu minimalizacji strat w elektroenergetycznym systemie przesyłowym Południowej Sulawesi w Indonezji. W algorytmie wykorzystano optymalizację roju cząstek ze zmiennym w czasie przyspieszeniem (ang. TVA-REPSO). Dokonano porównania z innymi metodami, pokazało, że opracowana metoda ma skuteczność podobną do klasycznej metody PSO, lecz krótszy czas obliczeń.