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Renewable energy optimization in isolated microgrids: A Python-based tool for cost-effective solutions using genetic algorithms
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DOI：10.1016/j.ecmx.2026.101709.png)
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Abstract
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• Developed a modular Python code for fast techno-economic optimization in microgrids. • Implemented an automated dispatch strategy for diesel generators using efficiency criteria. • Enabled reading input data with varying time steps and operating accordingly. • Executed bi-objective optimization using a genetic algorithm. • Analyze multiple diesel generators and other sources simultaneously.
Keywords:
Isolated microgrids
Genetic algorithm
Levelized cost of energy
Diesel displacement
Python
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