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

Abstract

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

Uso de algoritmo genético para gestionar la demanda energética en microrredes mediante descomposición poligonal

“…Éstas gestionan las cargas locales, fuentes de energia renovables (FER), fuentes de energia fósil (FEF), y están equipadas con sistemas de almacenamiento de energía (SAE) Maślak and Orłowski, 2022). De esta forma, una MR se define como una red de energía que puede ser autosuficiente o formar parte de un sistema global de generación de energía, y que garantiza un flujo de energía bidireccional e información cliente/proveedor (Sarker et al, 2021;Topa Gavilema et al, 2023). Por lo tanto, es indispensable un sistema de gestión de energía (SGE) que garantice, tanto la energía demandada como la comercialización de energía.…”