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.
Funder
the State Research Agency
Reference41 articles.
1. Forecasting electricity demand of electric vehicles by analyzing consumers’ charging patterns;Moon;Transp. Res. Part Transp. Environ.,2018
2. Are Carbon Prices Redundant in the 2030 EU Climate and Energy Policy Package?;Aune;Energy J.,2021
3. A stochastic MPC based approach to integrated energy management in microgrids;Zhang;Sustain. Cities Soc.,2018
4. A review from design to control of solar systems for supplying heat in industrial process applications;Gil;Renew. Sustain. Energy Rev.,2022
5. Topa Gavilema, Á.O., Álvarez, J.D., Torres Moreno, J.L., and García, M.P. (2021). Towards Optimal Management in Microgrids: An Overview. Energies, 14.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献