Power systems
Farhad Amiri; Mohammad Hassan Moradi
Abstract
: In the context of frequency stability in a two-area microgrid, it is crucial to address the fluctuations in frequency caused by load disturbances. To achieve this, an effective load-frequency control (LFC) system, which serves as the secondary control, must be implemented. However, the presence of ...
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: In the context of frequency stability in a two-area microgrid, it is crucial to address the fluctuations in frequency caused by load disturbances. To achieve this, an effective load-frequency control (LFC) system, which serves as the secondary control, must be implemented. However, the presence of renewable energy sources such as wind turbines and photovoltaic systems adds complexity to the operation of the LFC system due to their inherent uncertainty. To enhance the performance of the LFC system in the two-area microgrid, this paper proposes a reduction in the number of controllers employed, aiming for a less complex structure. Specifically, Model Predictive Control (MPC) is utilized for LFC, and the weight parameters of the MPC controller are determined using Craziness-based Particle Swarm Optimization (CRPSO). The proposed method is compared with alternative approaches, including PID controller optimized with Social Spider Optimization (SSO), Fractional Order Fuzzy PI (FOFPI), and conventional MPC. The effectiveness of the proposed method is evaluated in various scenarios, considering load variations and the presence of distributed microgrid generation resources. The results demonstrate that the proposed method outperforms the other controllers in terms of speed of response, reduction of overshoot and undershoot, and overall complexity. Importantly, the proposed method significantly improves the frequency stability of the two-area microgrid. The simulation and analysis are conducted using MATLAB software, providing a comprehensive understanding of the system dynamics and the performance of the proposed controller.
Industrial Electronics
Mohsen Ehsani; Masood Saeidi; Hamid Radmanesh; Adib Abrishamifar
Abstract
In this paper, the linear state-space model of the multi-input DC-DC boost converter is obtained and based on, a linear SISO model is calculated. Model predictive control (MPC) offers a novel method of designing in the power electronic converters. The application to DC-DC converters offers real benefits ...
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In this paper, the linear state-space model of the multi-input DC-DC boost converter is obtained and based on, a linear SISO model is calculated. Model predictive control (MPC) offers a novel method of designing in the power electronic converters. The application to DC-DC converters offers real benefits because of having simple tuning technique and analytical guaranteed stability. The weakness of this converter is non minimum phase behavior. One of the methods of implementation MPC controller is Generalized Predictive Control (GPC) which is compatible with non-minimum phase systems but due to simple implementation, using of the linear controller is more popular in power electronics control system. GPC has some advantage such as fast dynamic and robustness in the nonlinear system however main advantage of linear controllers is its low steady state error. The main idea of this paper is the investigation performance of GPC and linear controller in the multi-input DC-DC boost converter and camper with PI controller in term of dynamic, steady-state error, and robustness and run time in a microcontroller. The resulting of this comparison is critically assessed in simulation and algorithms ruining time has been compared in microcontroller hardware.
