In this paper, a new optimization technique namely JAYA is proposed to optimize the coefficients of proportional plus integral controller and filter parameters of photovoltaic fed distributed static compensator (PV-DSTATCOM). The JAYA is a new optimization tool whose performance is independent of the algorithm-specific control parameters. It overcomes the limitations of others in terms of attaining global optima with reduced computational effort. From the obtained simulation and experimental results, the performance of JAYA optimized PV-DSTATCOM has been found quite satisfactory and stimulating as compared to grenade explosion method and teaching-learning based optimized PV-DSTATCOM.

This study investigated the problem of controlling a three-phase three-wire photovoltaic (PV)-type distribution static compensator (DSTATCOM). In order to model, simulate, and control the system, the MATLAB/SIMULINK tool was used. Different controllers were applied to create switching pulses for the IGBT-based voltage source converter (VSC) for the mitigation of various power quality issues in the PV-DSTATCOM. Traditional control algorithms guarantee faultless execution or outcomes only for a restricted range of operating situations due to their present design. Alternative regulators depend on more resilient neural network and fuzzy logic algorithms that may be programmed to operate in a variety of settings. In this study, an adaptive linear neural network (ADALINE) was proposed to solve the control problem more efficiently than the existing methods. The ADALINE method was simulated and the results were compared with the results of the synchronous reference frame theory (SRFT), improved linear sinusoidal tracer (ILST), and backpropagation (BP) algorithms. The simulation results showed that the proposed ADALINE method outperformed the compared algorithms. In addition, the total harmonic distortions (THDs) of the source current were estimated under ideal grid voltage conditions based on IEEE-929 and IEEE-519 guidelines.

Critical Loads at the consumer end has increased the concerns of researchers to find a better solution for mitigation of the power quality issues. Present paper shows motivation towards the development of present and future grid connected Photovoltaic systems. Photovoltaic system is connected to the grid by the DC-link capacitance of the Unified Power Quality Conditioner which has the capability to overcome the voltage and current power quality issues. In this paper mitigation of voltage sags and swells elimination perfectly done as well as voltage harmonics. However PV fed UPQC has the capability to maintain the load voltage even at the time of interruption from the source grid Control algorithm has been implemented for both series and shunt part of the UPQC. Simulation results are verified through development of Laboratory prototype.

This paper presents a new time-domain multi-objective function approach for solving load frequency control issue in an interconnected power system. The performance of interconnected power system in each area is validated for overshoot and settling time values of frequency change and tie-line power exchange. An objective function is created with the goal of enhancing proportional integral derivative (PID) controller settings by reducing overshoot and achieving faster time-domain settling times. The efficiency of the proposed time-domain multi-objective function is evaluated in a two-area thermal power plant using a nature-inspired cuckoo search optimization (CSA) technique. By comparing the time-domain simulation results of the test system with the existing integral error-based objective functions IAE, ISE, ITAE, and ITSE, the proposed objective function is validated. Further, a sensitivity analysis were carried out to analyze the robustness of the proposed multi-objective function under various uncertain conditions.