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.

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^®.

This work proposed a frequency control approach in a hybrid power system, which include Wind Generation(WG), Photovoltaic Generation(PV), Diesel Generation and storage battery. Proportional Integral Derivative(PID) controller was designed for the blade pitch system of wind turbine to improve the system dynamic performance. In addition, to minimize the oscillation of system, (Super-conducting Magnetic Energy Storage(SMES) with first order lead-lag controller was implemented, it would supply and absorb active power quickly to reach power generation/demand balance and thereby control system frequency. Minimization issues of frequency and wind output power deviations are considered as two objective function of PID controller of wind turbine. Also, frequency and diesel output power deviations are present as two objective functions of lead-lag controller of SMES. modified version of Non-dominated Sorting Genetic Algorithm(NSGA-II), was used to tune the parameters of controller. The robustness and effectiveness of the proposed method was verified by simulation using $\mathrm{M}\mathrm{a}\mathrm{t}\mathrm{l}\mathrm{a}\mathrm{b}^{\mathrm{o}}/\mathrm{S}\mathrm{i}\mathrm{m}\mathrm{u}\mathrm{l}\mathrm{i}\mathrm{n}\mathrm{k}^{\mathrm{o}}$ From simulation results we examined the ability of the controllers to damp all frequency and output powers fluctuations and enhance the stability and reliability of system.