Abstract
An Isolated Microgrid (IMG) is an electrical distribution network combined with modern information technologies aiming at reducing costs and pollution to the environment. In this article, we implement the Bacterial Foraging Optimization Algorithm (BFOA) to optimize an IMG model, which includes renewable energy sources, such as wind and solar, as well as a conventional generation unit based on diesel fuel. Two novel versions of the BFOA were implemented and tested: Two-Swim Modified BFOA (TS-MBFOA), and Normalized TS-MBFOA (NTS-MBFOA). In a first experiment, the TS-MBFOA parameters were calibrated through a set of 87 independent runs. In a second experiment, 30 independent runs of both TS-MBFOA and NTS-MBFOA were conducted to compare their performance on minimizing the IMG using the best parameter tuning. Results showed that TS-MBFOA obtained better numerical solutions compared to NTS-MBFOA and LSHADE-CV, an Evolutionary Algorithm, found in the literature. However, the best solution found by NTS-MBFOA is better from a mechatronic point of view because it favors the lifetime of the IMG, resulting in economic savings in the long term.
Highlights
One of the most critical issues is the efficient use of available energy sources
We noticed that the higher the number of bacteria and chemotaxis cycles, the execution time of both algorithms increased from an order of seconds to minutes, due to the number of evaluations needed, which is calculated by Sb × Nc × GMAX
An Isolated Microgrid (IMG) is an intelligent energy network that uses distributed generators allowing the exploitation of renewable energy sources, such as wind and solar, as well as fuels
Summary
One of the most critical issues is the efficient use of available energy sources. In rural or remote geographic locations, the generation and distribution of energy is a significant challenge for many areas of engineering such as control, power electronics or planning, among others. Microgrids (MGs) have been a reliable solution for the power supply in separate areas, provided that there is adequate operational planning of the MG energy sources [1]. An MG is composed of energy storage systems (ESS),hybrid power generation systems (HPGS) from renewable energy sources (RES) and conventional generation systems (CGS); with all elements working in a coordinated way for the power generation. CGSs have a high operating cost due to the materials and transportation logistics. ESSs are integrated by costly devices requiring a safe manner operation, guaranteeing a long service life
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