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Massive growth in global electrical energy demand has necessitated a genuine exploration and integration of solar and wind energy into the electrical power mix. This incorporation goes a long way in improving the cumulative generated power capacity of the power system. However, wind and solar photovoltaic (PV) are intermittent in nature, making the provisioning of a good maximum power tracking (MPPT) scheme necessary. Furthermore, the integration is characterized by synchronization challenges and introduces various modes of power system oscillations as it is converter-driven. This greatly affects the overall stability of the integrated power mix. Consequently, various technological models have been designed to address these challenges ranging from MPPT schemes, phase-lock loop (PLL), virtual synchronous generator (VSG), power system stabilizers (PSS), flexible AC transmission system (FACTS), coordinated control and artificial intelligence (AI). In this work, a multi-machine power system model is reviewed for integration stability studies. Various technical solutions associated with the integration are also reviewed. MPPT, PLL, VSG, PSS, FACTS, coordinated control, and various optimization technique schemes used for damping controller design are discussed. Published version This work was supported by Advanced Lightning and Power Energy System, Universiti Putra Malaysia under UPM Grant No. 9630000.

In this study, the design of proportional integral derivative (PID) PSS (PIDPSS) is proposed for damping oscillations in single machine infinite bus (SMIB) power system in MATLAB/SIMULINK. A new metaheuristics method called Farmland Fertility Algorithm (FFA) inspired by nature is proposed to optimize the PIDPSS parameters via minimizing robust time domain performance indices called Integral of Squared Time multiplied by Squared Error (ISTSE) objective function. The robustness of the ISTSE index was tested by comparing it with four common time integral indices, also, the FFA PIDPSS was compare with Conventional PIDPSS (CPIDPSS) and Invasive Weed Optimization (IWO) algorithm for plausible application in. The phasor simulation results shows that the proposed ISTSE, the speed deviation SMIB transient response in terms of rise time, settling time, peak time were all remarkably improved by an amount of 35.16%, 40.57%, 77.1% and 1% respectively by the proposed FFA method compare to the IWO method.

This paper proposes the implementation of digital controlled single phase voltage source inverter (VSI) shunt active power filter (APF) proto type which adopts the combination of dual digital control algorithms in line current harmonics suppression and power factor (PF) improvement. The proposed VSI shunt APF proto type results in reducing the line current harmonics and forces it to be pure sine wave and in phase with its voltage. The dual digital controllers proposed are: a mathematically simplified and concise artificial neural network (ANN) technique using an improved delta rule learning algorithm for extracting the harmonic components and a bandless digital hysteresis switching architecture. A digital signal processor (DSP) microcontroller (TMS320F28335) verifies the proposed VSI shunt APF proto type implementation which harnessed the proposed algorithms interaction effectively. Experimental results validates the MATLAB/SIMULINK simulation results which found to conform to IEEE 519-1992 harmonic norms.

A novel nature inspired population-based Harris Hawk Optimization (HHO) method for solving optimal power flow (OPF) problem is proposed in this paper. OPF is a non-linear, highly coupled non-convex constrained optimization problem that minimizes the objective function considering both equality and inequality constraints of the system. In this work, HHO is employed as the main optimizer to adjust the control variables namely real power dispatch by minimizing the fitness function. The proffered method is a single objective approach that aims to minimize the selective objective such as fuel cost or losses of the system by meeting the growing electric demands. Thus, the dynamic nature of chasing pattern of hawks and escaping pattern of prey, results in the global optimal solution. The proposed method is coded using MATLAB software and the effectiveness of method is tested in standard IEEE-30 bus system. The results obtained under selective objective shows that the fuel cost and losses of the system are minimized compared to other well-known intelligence algorithms such as Bat, Butter-Fly (BF), Ant-Lion Optimizer (ALO), Whale Optimization Algorithm (WOA), Salp Swarm Algorithm (SSA), Moth Flame (MF) and Glow Warm Optimization (GWO). It is inferred that the proposed method outperforms in terms of global search ability and convergence property.

The Phasor Measurement Unit (PMU) is the heart of smart grid system as it provides the data such as voltage and phase angle measurements of all buses of the system and thereby maintaining the system observability. In this context, this paper summarizes the various research based on PMU for complete observability and monitoring of integrated power system. The survey indicates that most of the recent researches are focusing on optimal PMU placement (OPP) rather than design and modeling of PMU considering various cases. Moreover, the state estimation using synchrophasor technology are also presented as addition objective to obtain the optimal number of PMU that need to be installed in the system for power system analysis and economic benefits of the system. The trend of research based on synchrophasor technology are evolving for real-time power system monitoring application where it also covers for dynamic power system assessment.

Today's power system grids are massively interconnected with newer technologies and control devices integrated into the system all for enhanced efficiency and economic benefits in operation. This property makes the grid highly dynamic and diverse thus, concluding it as the biggest artificial living network on earth. To observe the power system security requirements, planning and safe operation of today's system becomes imperatively necessary. If the power system security criterion is ignored, then power blackouts will be born and the system response will distribute severe socio-economic impact, therefore, it is essential to know the dynamic security assessment (DSA) for the systems and allow it to remain in a stable state. This paper will execute a comparison of each method of transient stability index (TSI) and transient stability assessment (TSA) and how the classes of these methods are implemented. The classifications will highlight the difference between the methods and show the individual benefits and setbacks when applied on a practical large sized power system. This review paper can deliver an in-depth knowledge into the development of a rapid and reliable rotor angle transient instabilities technique towards improving DSA of a practical large-sized power system.

In this research, an effective application and performance assessment of the Neuro-Fuzzy Controller (NFC) damping controller is designed to replace a single machine infinite bus (SMIB) power system stabilizer (PSS), and coordinated multi PSSs in large interconnected power systems are presented. The limitation of the conventional PSSs on SMIB and interconnected multi-machine test power systems are exposed and disclosed by the proposed NFC stabilizer. The NFC is a nonlinear robust controller which does not require a mathematical model of the test power system to be controlled, unlike the conventional PSSs&rsquo, damping controller. The Proposed NFC is designed to improve the stability of SMIB, an interconnected IEEE 3-machine, 9-bus power system, and an interconnected two-area 10-machine system of 39-bus New England IEEE test power system under multiple operating conditions. The proposed NFC damping controller performance is compared with the conventional PSS damping controller to confirm the capability of the proposed stabilizer and realize an improved system stability enhancement. The conventional PSSs&rsquo, design problem is transformed into an optimization problem where an eigenvalue-based objective function is developed and applied to design the SMIB-PSS and the interconnected multi-machine PSSs. The time-domain phasor simulation was done in the SIMULINK domain, and the simulation results show that the transient responses of the system rise time, settling time, peak time, and peak magnitude were all impressively improved by an acceptable amount for all the test system with the proposed NFC stabilizer. Thus, the NFC was able to effectively control the LFOs and produce an enhanced performance compared to the conventional PSS damping controller. Similarly, the result validates the effectiveness of the proposed NFC damping controller for LFO control, which demonstrates more robustness and efficiency than the classical PSS damping controller. Therefore, the application and performance of the NFC has appeared as a promising method and can be considered as a remarkable method for the optimal design damping stabilizer for small and large power systems.

Proliferation of nonlinear loads /devices in power systems generates a major concern to power system engineers, courtesy of its severe contamination effects (polluting the distribution networks with current harmonics). This paper depicts artificial intelligence (AI) application on resolving the power quality problem mentioned above by using the parallel active power filter (APF) strategy in two-wire distribution systems. The proposed AI adopted is an artificial neural network (ANN) responsible to detect current harmonics for the active power filtering process. The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. The proposed scheme is achieved via simulation studies (under MATLAB SIMULINK environment) and results obtained are discussed to verify its performance.

Suppliers of electricity and their consumers have attained a peak stage of concern regarding the quality of electric power nowadays, with current harmonics concise injection activities looms the power networks as certain loads (principally nonlinear loads) are applied on to it. With active power filter (APF) wide knowledge and sophistication in this regard, a high performance extraction algorithm coupled with a fast switching technique must be developed in utilizing this device optimum potential. This paper introduces a new effective algorithms for the compensation of this ill effects in the power networks namely the digital hysteresis algorithm with a modification by bandwidth absence in the switching analysis (called bandless digital hysteresis algorithm) and a modified artificial neural network responsible to detect and generate the necessary compensation signal injected on to the power networks by the harmonic agents. The proposed scheme is achieved via simulation studies (under MATLAB SIMULINK environment) and effectives results obtained are discussed to verify its performance.