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Renewable energy sources (RESs), as clean, abundant, and inexhaustible source of energy, have developed quickly in recent years and played more and more important roles around the world. However, RESs also have some disadvantages, such as the weakness of stability, and by the the estimated increase of utilizing RESs in the near future, researchers began to give more attention to these issues. This paper presents a novel output power fluctuate compensation scheme in the small-scale power system, verifying the effect of output power control using storage battery, demand-response and RESs. Four scenarios are considered in the proposed approach: real-time pricing demand-response employment, RESs output control use and both of demand-response and RESs output control implementation. The performance of the proposed control technique is investigated using the real 10-bus power system model of Okinawa island, Japan. Moreover, the system stability is checked using the pole-zero maps for all of the control loops associated with the proposed scheme. The robustness and effectiveness of the proposed method was verified by simulation using Matlab ® /Simulink ® .
Lei Liu; Hidehito Matayoshi; Mohammed Elsayed Lotfy; Manoj Datta; Tomonobu Senjyu. Load Frequency Control Using Demand Response and Storage Battery by Considering Renewable Energy Sources. Energies 2018, 11, 3412 .
AMA StyleLei Liu, Hidehito Matayoshi, Mohammed Elsayed Lotfy, Manoj Datta, Tomonobu Senjyu. Load Frequency Control Using Demand Response and Storage Battery by Considering Renewable Energy Sources. Energies. 2018; 11 (12):3412.
Chicago/Turabian StyleLei Liu; Hidehito Matayoshi; Mohammed Elsayed Lotfy; Manoj Datta; Tomonobu Senjyu. 2018. "Load Frequency Control Using Demand Response and Storage Battery by Considering Renewable Energy Sources." Energies 11, no. 12: 3412.
Robust control methodology for two-area load frequency control model is proposed in this paper. The paper presents a comparative study between the performance of model predictive controller (MPC) and optimized proportional–integral–derivative (PID) controller on different systems. An objective function derived from settling time, percentage overshoot and percentage undershoot is minimized to obtain the gains of the PID controller. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to tune the parameters of the PID controller through performance optimization of the system. System performance characteristics were compared to another controller designed based on MPC. Detailed comparison was performed between the performances of the MPC and optimized PID. The effectiveness and robustness of the proposed schemes were verified by the numerical simulation in MATLAB environment under different scenarios such as load and parameters variations. Moreover, the pole-zero map of each proposed approach is presented to investigate their stability.
Komboigo Charles; Naomitsu Urasaki; Tomonobu Senjyu; Mohammed Elsayed Lotfy; Lei Liu. Robust Load Frequency Control Schemes in Power System Using Optimized PID and Model Predictive Controllers. Energies 2018, 11, 3070 .
AMA StyleKomboigo Charles, Naomitsu Urasaki, Tomonobu Senjyu, Mohammed Elsayed Lotfy, Lei Liu. Robust Load Frequency Control Schemes in Power System Using Optimized PID and Model Predictive Controllers. Energies. 2018; 11 (11):3070.
Chicago/Turabian StyleKomboigo Charles; Naomitsu Urasaki; Tomonobu Senjyu; Mohammed Elsayed Lotfy; Lei Liu. 2018. "Robust Load Frequency Control Schemes in Power System Using Optimized PID and Model Predictive Controllers." Energies 11, no. 11: 3070.