OPTIMIZATION BASED ON AN OPEN-SOURCE SOLVER FOR A MICROGRID WITH A PHOTOVOLTAIC SOLAR SYSTEM AND HYBRID ENERGY STORAGE

Abstract

The use of python-based solvers is increasingly used to formulate and solve optimization problems in the different areas of applied science. Open source tools like Pyomo are flexible in incorporating new syntaxes, allowing contributions, improving their functions, and correcting errors. In this article, we propose to use the MINLP convex solvers (MINLP-BB, KNITRO, BONMIN, and FIlMINT) connected to the PYOMO-NEOS server. Numerical comparisons are made, and an optimization problem is solved for a grid-connected photovoltaic microgrid with hybrid storage (lead-acid battery and Supercapacitor) to reduce the consumption of energy absorbed from the electricity grid, but also the bill paid by the consumer in the northern region of Colombia. The numerical results obtained demonstrate the potential of the Python-based solver and its application in optimization problems of hybrid renewable energy systems.