The technology has proceeded so much that the power system should be substantial and explicit to give optimal results. Ever-increasing complexities of the power system and load disparity cause frequency fluctuations leading to efficiency degradation of the power system. In order to give a suitable real power output, the system entails an extremely perceptive control technique. Consequently, an advanced control method, that is, an adaptive model predictive controller (AMPC), is suggested for load frequency control (LFC) of the series power system which comprises photovoltaic (PV), wind, and thermal power. The suggested method is considered to enhance the power system execution as well as to decrease the oscillations due to a discrepancy in the system parameters and load disturbance under a multi-area power system network. The AMPC design verifies the constant frequency by maintaining a minimum steady state error under varying load conditions. The proposed control approach pledge that the steady-state error of frequencies and interchange of tie line powers is maintained in a given tolerance constraint. The effectiveness of the proposed controller is scrutinized by conventional controllers like genetic algorithm-tuned PI (GA-PI), firefly algorithm-tuned PI (FA-PI), and model predictive controller (MPC) to show the competence of the proposed method.

This paper presents a new modified variable step size Fractional Order Incremental Conductance (FOIC) with maximum power point tracking using Fractional Order PID controller tuned by bio-inspired Particle Swarm Optimization (PSO) to find optimal gain values of fractional integrator order (λ) and fractional derivative order (μ). The classical incremental conductance and FOIC show drawbacks under changing irradiance, oscillation around maximum power point (MPP) which decreases its convergence speed. To resolve these prone a variable step size FOIC is proposed to achieve an adaptive duty cycle via tuning of FOPID through PSO. The robustness of the proposed technique is judged by its steady-state and dynamic response with fast converges, less response time, overshoot, and ripples under changing environmental conditions. Furthermore, the performance of the proposed technique is evaluated by comparing it with a fixed step size conventional incremental conductance algorithm and FOIC.

This paper presents a load frequency control (LFC) design using the variable structure model predictive controller (VSMPC) for gain scheduling (GS) of PI controller in PV connected thermal for multi-area system. Due to the increasing impact of renewable energy sources into the grid system, the system frequency deteriorates. The proposed PV connected thermal system is evaluated under varying load conditions under increased penetration of the PV source.The combination of renewable energy into the thermal power system aggravates the frequency and it is indispensable to mitigate such a problem by introducing an optimal controller. Perturbation in load greatly affects the system frequency and this problem is addressed by using VSMPC based gain scheduling knowing the effect of proportional and integral in transient and steadystate conditions. The oscillations in frequency are controlled by a proposed controller and the impact of frequency under penetration of PV is monitored.Further verification of the proposed technique is accomplished through communication delay in the governor and turbine. The Hardware in the loop (HIL) which validates the accuracy and real time performance of the controller. Finally, the validation of the proposed controller is compared with MPC to tune PI controller and renowned evolutionary tuned techniques like particle swarm optimization (PSO), genetic algorithm (GA) and firefly algorithm (FA) to optimize PI controller. The VSMPC with GS of PI controller shows promising results.

Photovoltaic (P.V.) systems have become an emerging field for power generation by using renewable energy (RE) sources to overcome the usage of conventional combustible fuels and the massive release of dangerous gases. The efficient operation of the PV system is vital to extracting the maximum power from the PV source. For this, a maximum power point tracking (MPPT) algorithm works with a DC–DC converter to extract maximum power from the P.V. system. Two main issues may arise with the involvement of a converter: (1) to locate M.P.P and (2) the performance of the PV model in varying weather conditions. Therefore, designing any converter gain has the utmost significance; thus, the proposed work is on non-isolated boost converters. To calculate the values of specific parameters such as input capacitor, output capacitor, and inductor, the averaging state-space modeling typically uses governing equations. In this research, the formula of the input capacitor is derived through the average state-space modeling of the boost converter, which signifies the relation between input and output capacitors. From the results, it has been proven that the input capacitor efficiently performs when the input capacitor is half of the output capacitor. At an irradiance level of 1000 W/m2, the system shows stable behavior with a fast convergence speed of 0.00745 s until the irradiance falls to a value of 400 W/m2. The system is less stable during the morning and the evening when irradiance falls are very low.

Photovoltaic (PV) system is a rapidly flourishing area for the implementation of renewable energy (RE) based power generation systems and their development is specifically owed to minimize the consumption of conventional fossil fuel thus minimizing immense emissions of harmful greenhouse gases. In order to harvest maximum power from PV arrays, MPPT techniques work in-cooperation with DC-DC converter. With the involvement of converter, two major issues rise: 1) convergence speed to detect the MPP as the sampling rate of PV system depends upon the converter system element parameters and 2) the stability of PV system under varying ambient conditions. Thus the designing of a DC-DC converter, gains a paramount importance. The research work in this paper revolves around the non-isolated boost converters. The averaging state-space model is utilized to derive the governing equations of the converter with respect to PV array and relations are provided to calculate the values of inductor, input capacitor and output capacitor. Several simulations are conducted in Matlab/Simulink and comparative analysis with the *(existing converter design) past-proposed converters have been presented. It has been proved that the performance of proposed DC-DC converter has superior performance.