Abstract
In this paper, an adaptive artificial fuzzy Mamdani-based model predictive approach for load frequency regulation of an isolated microgrid (IMG) is presented. A generalized state-space representation of an IMG comprising power sources is derived and exploited to predict the future behavior and control inputs for the IMG in order to regulate the frequency. The considered adaptive MPC is on the basis of a conventional model predictive approach that is equipped by a fuzzy logic tuning mechanism. A rule-based fuzzy logic is considered to tune the weight of the cost function in the model predictive controller (MPC), which highly impacts the minimization of the frequency deviation in the system. To show the advantages of the fuzzy adaptive MPC, it is compared with a conventional MPC in which the weights of the cost function is chosen by trial and error and fixed during the simulation. OPAL Real-time (RT) results show that the closed-loop system response performance based on the suggested fuzzy MPC is enhanced for different scenarios of the IMG load frequency system.
Original language | English |
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Title of host publication | Proceedings of 2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems |
Publisher | IEEE |
Publication date | 2020 |
Pages | 7-12 |
ISBN (Print) | 9781728169897 |
DOIs | |
Publication status | Published - 2020 |
Event | 2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems - Virtual event, Dubrovnik, Croatia Duration: 28 Sept 2020 → 1 Oct 2020 https://ieeexplore.ieee.org/xpl/conhome/9244275/proceeding |
Conference
Conference | 2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems |
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Location | Virtual event |
Country/Territory | Croatia |
City | Dubrovnik |
Period | 28/09/2020 → 01/10/2020 |
Internet address |
Keywords
- Load frequency control (LFC)
- Model predictive control (MPC)
- Fuzzy logic
- Online cost function tuning
- Isolated microgrid