An adaptive fuzzy logic (FL)-based new maximum power point (MPP) tracking (MPPT) methodology for controlling photovoltaic (PV) systems is proposed, designed, and implemented in this paper. The existing methods for implementing FL-based MPPTs lack for adaptivity with the operating point, which varies in wide range in practical PV systems with operating irradiance and ambient temperature. The new proposed adaptive FL-based MPPT (AFL-MPPT) algorithm is simple, accurate, and provides faster convergence to optimal operating point. The effectiveness and feasibility verifications of the proposed AFL-MPPT methodology are validated with considering various operating conditions at slow and fast change of solar radiation. In addition, the simplified implementation of the proposed algorithm is carried out using C-block in PSIM software environment, wherein the proposed algorithm and system are simulated. Additionally, experimental results are performed using a floating-point digital signal processing (DSP) controller (TMS320F28335) for verifying the feasibility of the proposed AFL-MPPT methodology. The results of simulations and experimental prototypes show great consistency and prove the capability of the new AFL-MPPT methodology to extract MPPT rapidly and precisely. The new proposed AFL-MPPT method achieves accurate output power of the PV system with smooth and low ripple. In addition, the new proposed AFL-MPPT method benefits fast dynamics and it reaches steady state within 0.01 s.

Multi-area power systems inhere complicated nonlinear response, which results in degraded performance due to the insufficient damping. The main causes of the damping problems are the stochastic behavior of the renewable energy sources, loading conditions, and the variations of system parameters. The load frequency control (LFC) represents an essential element for controlling multi-area power systems. Therefore, the proper design of the controllers is mandatory for preserving reliable, stable and high-quality electrical power. The controller has to suppress the deviations of the area frequency in addition to the tie-line power. Therefore, this paper proposes a new frequency regulation method based on employing the hybrid fractional order controller for the LFC side in coordination with the fractional order proportional integral derivative (FOPID) controller for the superconducting energy storage system (SMES) side. The hybrid controller is designed based on combining the FOPID and the tilt integral derivative (TID) controllers. In addition, the controller parameters are optimized through a new application of the manta ray foraging optimization algorithm (MRFO) for determining the optimum parameters of the LFC system and the SMES controllers. The optimally-designed controllers have operated cooperatively and hence the deviations of the area frequency and tie-line power are efficiently suppressed. The robustness of the proposed controllers is investigated against the variation of the power system parameters in addition to the location and/or magnitude of random/step load disturbances.

Several issues have been risen due to the recent vast installations of renewable energy sources (RESs) instead of fossil fuel sources in addition to the replacement of electric vehicles (EVs) for fuel-powered vehicles. Mitigating frequency deviations and tie-line power fluctuations has become driving challenge for the control design of interconnected power systems. RESs represent continuously varying power generators due to their nature and dependency on the environmental conditions. In this context, this article presents a new modified hybrid fractional order controller for load frequency and EVs control in interconnected power systems. The new controller combines the benefits of two widely employed fractional order controllers, including the FOPID and TID controllers. In addition, a new practical application of recent artificial ecosystem optimization (AEO) method has been proposed in this article for determining simultaneously the optimum controller parameters. The proposed controller and optimization method are validated on two areas interconnected power system with different types of RESs and with considering the natural characteristics of sources, EVs and load variations. Obtained simulation results verify the superior performance of the proposed controller and optimization method for achieving high mitigation of frequency fluctuations and tie-line power deviations, increased robustness, enhanced system stability over a wide range of parameters uncertainty and fast response during transients.

Reliability of power inverters is of dominant importance in various applications including industrial, military, aerospace, and commercial applications. Therefore, developing fault tolerant (FT) power inverters is extremely needed from the viewpoint of system availability and avoiding harmful consequences. Tolerating various types of faults, preserving full output ratings after the fault, and being cost effective represent the main challenges for most of existing FT solutions. In this paper, a new FT single phase five-level inverter topology is proposed. The proposed topology can effectively tolerate both of single or multiple switches faults, whether they are of open or short circuit fault types. Moreover, the proposed topology does not deteriorate system efficiency in post fault operation compared to the previously developed FT solutions. Evaluation of the effectiveness and robustness of the proposed topology is verified in both of simulation and experimental environments. Different case studies are investigated in order to cover various types and locations of switch faults. Moreover, comprehensive comparisons are provided to validate the superiority of the proposed topology over the previously addressed techniques.

The low system inertia and the high sensitivity to load and generation fluctuations represent the main challenges for future ambitious plans of modern power systems accompanied by high penetrations levels of the renewable energy sources (RESs). Therefore, this paper presents a new approach for solving the load frequency control (LFC) in addition to the virtual inertia control (VIC) in interconnected RESs penetrated power systems using cooperative tilt-based controllers and a hybrid modified particle swarm optimization with genetic algorithm (MPSOGA). The VIC system is adopted using superconducting magnetic energy storage (SMES) to provide sufficient inertial energy for system stability. Two tilt-based controllers are employed in each area using the tilt-integral-derivative (TID) controller for the SMES and TID with filter (TIDF) for the LFC function. The cooperative optimum design of the TID/TIDF controllers leads to the enhancement of frequency stability in studied two-area power systems. The formulated optimization process aims to minimize the frequency nadir settling time during abrupt changes of RESs and/or load changes, considering the cooperative control of LFC and VIC. The proposed approach has been applied to a case study consisting of two-area power systems, connected via hybrid high voltage DC/AC (hybrid HVAC/HVDC) tie-line, integrated with distributed conventional generations, photovoltaic (PV), and wind generation systems. Performance analysis has been conducted to demonstrate the effectiveness of the proposed method is compared to the genetic algorithm (GA) and particle-swarm optimization (PSO) using high fluctuations of renewable generations under extreme changes in loading conditions and physical parameters variation. The obtained results show the superiority of MPSOGA approach on the other competitive optimization techniques.