Published Papers

Volume 31 - Issue 2 (ICEE Special Issue)
Special Issue Papers

Adaptive MPC-based load frequency control for microgrids with renewable energy

Weichao Wang, Yutaka Sasaki, Yoshifumi Zoka, Naoto Yorino, Ahmed Bedawy and Seiji Kawauchi
Pages: 1-10Published: 04 Feb 2025
DOI: 10.33430/V31N2ICEE23-JY103
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Wang WC, Sasaki Y, Zoka Y, Yorino N, Bedawy A and Kawauchi S, Adaptive MPC-based load frequency control for microgrids with renewable energy, HKIE Transactions, Vol. 31, No. 2 (ICEE Special Issue), Article ICEE23-JY103, 2025, 10.33430/V31N2ICEE23-JY103

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Abstract:

In this paper, a novel load frequency control (LFC) approach based on adaptive model predictive control (AMPC) is proposed for a microgrid system (MG) with distributed energy resources. A simplified internal prediction model (firstlag system consisting of a gain and a time constant) is applied to online state estimation of the AMPC. The parameters are updated iteratively using unscented Kalman filter (UKF). The MG model with high penetration of renewable energy sources (RESs), such as photovoltaic (PV) and wind turbine (WT) power generations, is carried out to verify the effectiveness of the proposed approach. The simulation results show that the proposed AMPC approach can effectively cope with the frequency stability problem due to the disturbances of the PVs, WTs, and load. In addition, the authors indicate that the control performance of the proposed method is better than the tuned proportional-integral (PI) controller.

Keywords:

Microgrid; load frequency control; model predictive control; renewable energy sources; unscented Kalman filter

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