Conventional Energy Resources (CER) are being rapidly replaced by Renewable Energy Resources (RER) due to their abundant, environmentally friendly, clean, and inexhaustible nature. In recent years, Solar Photovoltaic (SPV) energy installation is booming at a rapid rate among various RER. Grid-Connected PVS required advance DC-link controllers to overcome second harmonic ripple and current controllers to feed-in high-quality current to the grid. This paper successfully presents the design of a Fuzzy-Logic Based PI (F-PI) and Fuzzy-Logic based Sliding Mode Controller (F-SMC) for the DC-link voltage controller and Proportional Resonant (PR) with Resonant Harmonic Compensator (RHC) as a current controller for a Single-Phase Two-Stages Grid-connected Transformerless (STGT) Photovoltaic (PV) Inverter. The current controller is designed with and without a feedforward PV power loop to improve dynamics and control. A Second Order General Integral (SOGI)-based Phase Lock Loop (PLL) is also designed that has a fast-dynamic response, fast-tracking accuracy, and harmonic immunity. A 3 kW STGT-PV system is used for simulation in Matlab/Simulink. A comparative assessment of designed controllers is carried out with a conventionally well-tuned PI controller. The designed controllers improve the steady-state and dynamic performance of the grid-connected PV system. In addition, the results, performance measure analysis, and harmonics contents authenticate the robustness, fastness, and effectiveness of the designed controllers, related to former works.

The modular multilevel converter (MMC) has been prominently used in medium- and high-power applications. This paper presents the control of output and circulating current of MMC using sliding mode control (SMC). The design of the proposed controller and the relation between control parameters and validity condition are based on the system dynamics. The proposed designed controller enables the system to track its reference values. The controller is designed to control both output current and circulating current along with suppression of second harmonics contents in circulating current. Furthermore, the capacitor voltage and energy of the converter are also regulated. The control of output current is carried out in $dq$ -axis as well as in $\alpha \beta -axis$ with first-order switching law. However, a second-order switching law-based super twisting algorithm is used for controlling circulating current and suppression of its second harmonics contents. The stability of the controlled system is numerically calculated and verified by Lyapunov stability conditions. Moreover, the simulation results of the proposed controller are critically compared with the conventional proportional resonant (PR) controller to verify the effectiveness of the proposed control strategy. The proposed controller attains faster dynamic response and minimizes steady-state error comparatively. The simulation of the MMC model is carried out in MATLAB/Simulink.

High penetration of large capacity wind turbines into power grid has led to serious concern about its influence on the dynamic behaviors of the power system. Unbalanced grid voltage causing DC-voltage fluctuations and DC-link capacitor large harmonic current which results in degrading reliability and lifespan of capacitor used in voltage source converter. Furthermore, due to magnetic saturation in the generator and non-linear loads distorted active and reactive power delivered to the grid, violating grid code. This paper provides a detailed investigation of dynamic behavior and transient characteristics of Doubly Fed Induction Generator (DFIG) during grid faults and voltage sags. It also presents novel grid side controllers, Adaptive Proportional Integral Controller (API) and Proportional Resonant with Resonant Harmonic Compensator (PR+RHC) which eliminate the negative impact of unbalanced grid voltage on the DC-capacitor as well as achieving harmonic filtering by compensating harmonics which improve power quality. Proposed algorithm focuses on mitigation of harmonic currents and voltage fluctuation in DC-capacitor making capacitor more reliable under transient grid conditions as well as distorted active and reactive power delivered to the electric grid. MATLAB/Simulink simulation of 2 MW DFIG model with 1150 V DC-linked voltage has been considered for validating the effectiveness of proposed control algorithms. The proposed controllers performance authenticates robust, ripples free, and fault-tolerant capability. In addition, performance indices and Total Harmonic Distortions (THD) are also calculated to verify the robustness of the designed controller.

This paper emphasizes the design and investigation of a new optimization scheme for a grid-connected photovoltaic system (PVS) under unbalance faults. The proposed scheme includes fuzzy logic controller (FLC) based on the Levenberg–Marquardt (LM) optimization technique in coordination with bridge-type-fault-current limiter (BFCL) as the fault ride through (FRT) Strategy. The LM optimization-based control is an iterative process with a fast and robust response and is always convergent. The BFCL reduces the fault currents to rated values without compromising at ripples. A keen and critical comparison of the designed strategy is carried out with a conventionally tuned proportional-integral (PI) controller in coordination with the crowbar FRT strategy. A 100kW MATLAB/Simulink model of a photovoltaic system is used for simulation and analysis of unbalance faults at the point of common-coupling (PCC) and at 5 km away from PCC. It is found that grid-connected PVS is highly influenced by the fault type and less effected by the distribution line length. The simulation results authenticated smooth, stable, ripples with free, robust, and fault-tolerant behavior of the proposed scheme.

The modular multilevel converter (MMC) has significant applications in power systems due to its promising features, such as modularity, reliability, scalability, and low harmonic distortion. One of the challenges in the operation of MMC is to regulate the circulating current in its phase leg and sub module (SM) capacitor voltage. This paper presents the control of internal dynamics, i.e., circulating current and submodule capacitor voltage, of the MMC using an integral backstepping algorithm. The design of the controller is based on Lyapunov stability function. The backstepping control ensures the convergence of the error signal to zero. Additionally, the integral action in the control law increases the robustness and reliability of the system against the external disturbances and model uncertainties. Moreover, the integral term in the controller eliminates the residual steady-state error. The Lyapunov function-based design of the backstepping controller guarantees the convergence of circulating current as well as submodule capacitor voltage for any possible initial condition. Moreover, the performance of the proposed integral backstepping controller is compared with the proportional resonant (PR) controller. The proposed backstepping control scheme for three-phase MMC has been implemented in MATLAB/Simulink.

In this paper, a model reference controller (MRC) based on a neural network (NN) is proposed for damping oscillations in electric power systems. Variation in reactive load, internal or external perturbation/faults, and asynchronization of the connected machine cause oscillations in power systems. If the oscillation is not damped properly, it will lead to a complete collapse of the power system. An MRC base unified power flow controller (UPFC) is proposed to mitigate the oscillations in 2-area, 4-machine interconnected power systems. The MRC controller is using the NN for training, as well as for plant identification. The proposed NN-based MRC controller is capable of damping power oscillations; hence, the system acquires a stable condition. The response of the proposed MRC is compared with the traditionally used proportional integral (PI) controller to validate its performance. The key performance indicator integral square error (ISE) and integral absolute error (IAE) of both controllers is calculated for single phase, two phase, and three phase faults. MATLAB/Simulink is used to implement and simulate the 2-area, 4-machine power system.