Modeling and Energy Management of a Microgrid Based on Predictive Control Strategies

This work presents the modeling and energy management of a microgrid through models developed based on physical equations for its optimal control. The microgrid’s system was built with one most popular control algorithms in systems: model predictive strategy aims to satisfy load demand an office located CIESOL bioclimatic building, which placed University Almería, using quadratic cost function. simulation scenarios took into account real parameters provided by building. For case studies five days, optimization aimed at minimizing input flows difference between generated demanded load, subject series constraints both outputs inputs. results this show how, correct tuning strategy, building is covered available sources, reducing consumption public grid, regarding wrong controller, 1 kWh per day first scenario 7 last.