Renewable-Based Hybrid Charging Infrastructure for Isolated Microgrids: Enhancing Power Quality and Supporting EV Integration

Apart from the breaking and transferring devices, all other power quality (PQ) enhancement devices like DSTATCOM, DVR, UPQC etc. are based on power converters. Furthermore modern FACTS devices like STATCOM, SSSC, UPFC etc. also employ power converters. However, FACTS devices have much higher power rating than PQ enhancement devices since they are used in bulk power transmission systems. Moreover, their operation philosophy is also different as they are assumed to work under balanced sinusoidal conditions. As a consequence, the control strategies of FACTS devices are different from the PQ enhancement or Custom Power devices. Since power converters have an important role to play in modern power systems, we discuss their topologies and control strategies in this chapter. For the background materials in the area of Power Electronics, there are numerous excellent textbooks, e.g., [1, 2, 3].

To enhance electrical clout's quality, FACTS and ritual energy sources are supplementary to the wiring. Active Filtration Systems, DVRs, DSTATCOMs, UPQC and other devices are used to augment the voltage and current's clout eminence. By lessen the issues associated amid clout eminence with the aid of these technologies. While any device can enhance power quality, UPQC is the main focus here. Utilizing universal power quality conditioners, a strategy to control congestion based primarily on optimal power flow creation is being envisaged (UPQC).The main goal is to use Simulated Teaching Learning based Optimization (TLBO) to find the best site for FACTS controllers within a fourteen-bus infrastructure. Insufficient collaboration amongst both power and transmission firms may result in bottleneck in cabling. As a result, there may be equipment breakdowns, sudden increases in load demand, or generation outages. These events can be avoided by employing universal power quality conditioners (UPQC). MATLAB/SIMULINK was utilized to simulate the validation scheme and obtain the output for the effectiveness of the process.

Power Quality voltage problems in a power system may be either at system frequency or due to transient surges with higher frequency components. These are called switching types overvoltages which can be produced during opening or closing a switch and they may be severe in certain cases. The paper presents a low cost FACTS based dynamic capacitor scheme for voltage compensation and power quality enhancement. The FACTS dynamic compensator is a member of a family of smart power low cost compensators developed by the First Author.

Distributed energy resource systems offer improved energy utilization and reduced transmission losses by decentralizing power generation and load management. However, the power quality is often compromised by inefficient customer-side equipment, such as single-phase induction motors, which suffer from low efficiency and poor power factor. To address this issue, this paper proposes a permanent magnet retrofitting method for single-phase induction motors, which replaces the squirrel-cage rotor with a permanent magnet rotor while preserving the original stator and winding structure. The proposed method aims to enhance motor performance without significant structural changes. A single-phase induction motor was retrofitted using the proposed method, and its performance was evaluated through finite element simulations to verify the effectiveness of the design approach. This study also investigated the key factors influencing motor starting performance after the introduction of permanent magnets. This study presents a practical and effective method for the permanent magnet retrofitting of single-phase induction motors, which contributes to improving motor efficiency and enhancing power quality in distributed energy resource systems.

Multilevel inverters play a critical role in renewable energy systems by enabling efficient power conversion and enhancing power quality. With the increasing integration of renewable energy sources, such as solar photovoltaic (PV) and wind, there is a growing need for advanced control strategies to ensure reliable operation and minimize harmonic distortion. This paper explores various control techniques for multilevel inverters, focusing on improving the quality of power delivered to the grid and reducing energy losses. The proposed strategies include the use of pulse width modulation (PWM) schemes, artificial intelligence (AI)-based controllers, and hybrid control algorithms to enhance the performance of multilevel inverters. Simulation results demonstrate that these advanced control strategies effectively improve the power quality and overall efficiency of renewable energy systems. This research provides insights into optimizing multilevel inverter design for better performance in modern renewable energy applications.

The aim of this research is a comprehensive analysis of power quality (PQ) issues in industrial power networks, as well as the development and systematization of methods for monitoring, diagnosing, and improving key PQ parameters, such as harmonic distortions, flicker, voltage sags, phase unbalance, and reactive power. The methods. The study employs a combination of theoretical analysis, review of relevant standards (IEC 61000-4-30, EN 50160, IEEE 519), and practical experience in the implementation of modern digital PQ analyzers. The use of filters, compensators, and intelligent systems is analyzed, including DVR, STATCOM, hybrid active filters, and machine learning algorithms for classifying PQ events. Findings. The research outlines the main PQ indicators and presents methods for their measurement, diagnosis, and compensation. Examples of implemented technical solutions for improving power quality are provided, including passive and active harmonic filters, SVC and STATCOM for flicker mitigation, methods for reducing phase unbalance, and protection against short-term voltage disturbances. The originality. The study proposes a concept of distributed power quality compensation using smart inverters and charging stations. The application of neural networks and S-transforms for real-time identification of disturbance sources is discussed. The advantages of integrated approaches to both local and centralized PQ correction are substantiated. Practical implementation. The results can be used by energy management engineers and enterprise personnel to build monitoring systems, protect critical equipment, and enhance energy efficiency. The proposed solutions reduce failure rates, energy losses, and maintenance costs, ensuring compliance with modern sustainable development standards.

Injection of power generated by the wind turbine system into an electric grid mainly effects the power quality. The performance of this wind turbine and its power quality is determined on the basis of its measurement of power ratings as per Institute of Electrical and Electronics Engineers (IEEE) standards. The influence of the wind turbine in the grid system concerning the power quality measurements are the active power, reactive power, variation of voltage, flicker, harmonics, and electrical behavior of switching operation. To mitigate the power quality problems this paper proposes the shunt compensator techniques. Here, the proposed system is verified experimentally using both Static Synchronous Compensator (STATCOM) and Thyristor Switched Capacitor (TSC) compensators. This control schemes for grid connected wind energy system is simulated using Matlab/Simulink.

The power quality domain in power system networks has received more attention recently because of the increase in sensitive equipment, non-linear load disturbances, and the utilization of Renewable Energy Sources (RES). In case of distributed generation, which could occur from consumers to utilities, power quality quantifies the suitability of electric power supplied from the utilities to the commercial, industrial, and residential users. A minimum of half of the total disruptions to power quality are related to voltage quality. This research concentrated an amplitude-frequency estimation based methods, Power quality Disturbance Classification and Filtering techniques for harmonic mitigation. The enhancement of power quality in a three-phase nonlinear load power system is the subject of this research. Shunt Active Power Filter (SAPF) is used in real-time applications for fault detection and harmonic suppression. The suggested work uses a digital signal processor (DSP) (28335) and a shunt active power filter (SAPF) to achieve power quality disturbance detection and harmonic reduction on hardware system. In addition to applying shunt compensation devices for harmonic detection, the designed hardware model is tested for power quality disturbance categorization of voltage sag, harmonics, and interruption and Total Harmonic Distortion (THD) is 4.3% in this case. The overall implementation of the hardware using -Fuzzy algorithm is found to be satisfactory.

In the paper, a hybrid technique is proposed for analysing and controlling PQ issues in SG. Initially, the normal behaviour of SG system is analysed. After that, some disturbance is created in the SG system and determined the abnormal behaviours. The first phase of proposed methodology is utilisation of wavelet transformation algorithms for processing the inputs. Here, multi-wavelet transform (MWT) is utilised to extract the features of inputs for classification. The hybrid technique is a combination of hybrid ANFIS and FA, which is utilised to maintain the DC-link voltage of the UPQC. The hybrid ANFIS means, FA is used to select the optimal dataset for training the ANFIS. The main objective of the proposed technique is detecting and controlling the PQ issues in SG. The proposed method is implemented in MATLAB/Simulink platform. In order to analyse the effectiveness of the proposed method, various types of issues are analysed and tested with the existing methods such as, UPQC with ANFIS, UPQC with artificial neural network (ANN) technique and UPQC with gravitational search algorithm (GSA).

Presently, there exists a multitude of applications reliant on superconducting magnetic energy storage (SMES), categorized into two groups. The first pertains to power quality enhancement, while the second focuses on improving power system stability. Nonetheless, the integration of these dual functionalities into a singular apparatus poses a persistent challenge. Considering this, this paper proposes a multi-functional device based on SMES, encompassing both power quality enhancement and power system stability improvement capabilities. It incorporates power quality enhancement features such as current harmonic filtering, active power smoothing, reactive power compensation, and critical load protection, while also furnishing virtual inertia to bolster grid frequency. Simulation results validate the effectiveness of the proposed methodologies.

Renewable energy sources have been expected to be promising alternative energy sources in the future. Renewable energy sources can bring new challenges and problems when connected to the power grid. The basic elements of the PV– wind generating system are the DC–DC Boost Converter and the three-phase inverter whose role is to convert DC into AC having the same amplitude, frequency, and phase of the grid, to which it will be connected. Also, the injected power into an electric grid affects the power quality. Consequently, the impact of the integration of renewable power plants into the electric network corresponding to the level of harmonics and its propagation, besides the initial harmonics resulting from the nonlinear loads itself, has been presented in this paper. Firstly, the size of the distributed generators (DG) has been determined using the Salp Swarm algorithm (SSA) in order to improve the voltage profile and reduce the lack of generation. In addition, a techno-economic feasibility study of PV and wind power plant was evaluated using RETScreen program. Secondly, Active Power Filter (APF) has been used for power quality (PQ) improvement, where the controller for APF has been designed to improve the voltage profile and compensate reactive power and harmonics. Optimal parameters of APF (L-C) are determined using particle swarm optimization (PSO) to minimize the total harmonics distortion (THD) in the studied system. Furthermore, a comprehensive comparison of the photovoltaic and wind generation with a nonlinear load in both cases with and without the APF is presented.

Providing high-quality, reliable, and continuous power to consumers is crucial in today's power systems. However, the increasing demand and widespread use of power electronic devices have introduced various power quality issues, including voltage sags, swells, and harmonics. To mitigate these issues, advanced power electronic devices have been employed. This project focuses on utilizing a Unified Power Quality Conditioner (UPQC) integrated with a solar PV array to maintain optimal power quality. The UPQC combines series and shunt compensators, enabling it to perform multiple tasks and improve power quality. The series converter addresses grid-side power quality problems, such as voltage sags and swells, while regulating the load voltage and PCC voltage. Meanwhile, the shunt compensator mitigates current harmonics caused by nonlinear loads, leveraging power from the PV array. A synchronous reference frame control strategy based on a moving average filter generates the reference signal. The UPQC model is developed and simulated using MATLAB/SIMULINK software to evaluate its performance. Keywords: Solar PV, UPQC, Power Quality.

The wind power generation is rapidly growing and the use of wind farms and other distributed power generation systems have drastically increased. According to IEC standard, the power quality is determined from the performance of wind generators. In this paper using a FACTS controller device the power quality enhanced when the wind generators are connected to the grid system. The power quality becomes an issue when wind generators are connected to the grid, due to the interaction between the grid and the wind turbines. The main impact on the grid by the wind generators, regarding power quality, is related to voltage sag, reactive power, harmonics, power peaks and flickers. The power quality problem arises when the wind generators are equipped with the grid, can be improved by connecting a FACTS controller at a point of common coupling. In this paper, UPFC (UNIFIED POWER FLOW CONTROLLER) control scheme for the wind generators connected grid is used to improve the power quality using MATLAB/SIMULINK in power system block set. Also this UPFC control system that includes both the shunt converter and the series converter has been simulated. In this proposed model, the real and reactive power compensation is the main concern.

Electric spring (ES) is an innovative design that can regulate voltage abnormalities developed by intermittent nonconventional power sources (NCPS) connected with smart grid. Renewable power sources are employed nowadays in contemporary power systems worldwide to overcome the fast depletion of fossil fuels. Nonetheless, the infiltration of these NCPS into the power system produces an adverse effect on the power system stability and quality. This research recommends various control schemes and offers a potent approach called as ES which regulates the mains voltage in spite of changes caused by the intermittent NCPS in the DC microgrid (MG) environment. This investigation analyses a Model Predictive Controller (MPC) which is enforced to a DC-DC converter to help in the examination the power quality issues like harmonics reduction, voltage regulation and voltage ripple. In addition, the paper also addresses the battery’s lifetime by lessening its storage capacity. The suggested system is simulated using Matlab/Simulink software. The performance specifications of the system are achieved by the MPC controller and the parameters are studied and correlated with the artificial neural network (ANN) based intelligent controller and the conventional PI controller results. The suitability and cogency of the control scheme are affirmed, simulation studies are carried out on the sample test systems, and the simulation results are reported.

The rapid advancement of power system technologies has significantly transformed the way electrical power quality (PQ) is monitored, managed, and improved. The increasing penetration of non-linear loads, automation systems, and renewable energy sources has intensified power quality challenges, including harmonic distortion, voltage sags, voltage fluctuations, and transient disturbances. This study aims to analyze the impact of modern technological approaches on power quality enhancement in contemporary power systems. A descriptive-analytical research methodology was employed through a systematic review of recent scientific literature, international standards, and technical reports related to power quality management. The collected data were analyzed using qualitative content analysis and comparative evaluation to assess the effectiveness of automation, machine learning, Internet of Things (IoT)-based monitoring systems, and power electronic mitigation devices. The results indicate that integrated technological solutions significantly improve power quality performance compared to conventional approaches. Machine learning techniques, particularly Artificial Neural Networks, demonstrate high accuracy in disturbance classification and adaptive control, while IoT-based systems enable real-time monitoring and rapid response to power quality deviations. Furthermore, power electronic devices such as Active Power Filters, Static Var Compensators, and Dynamic Voltage Restorers effectively mitigate harmonics and stabilize voltage. However, challenges related to implementation cost, system complexity, cybersecurity, and regulatory inconsistency remain. The study concludes that an integrated, intelligent, and data-driven framework is essential for sustainable power quality management in modern power systems.