Grid-integrated System Research Articles

Reliability modelling of a grid integration system with dual operational and quintuple critical systems

Reliability modelling of a grid integration system with dual operational and quintuple critical systems

A novel hybrid-fuzzy logic based UVC technique for solar-PV/grid integrated water-pumping system

The continual depletion of fossil fuels and increased green-house emissions are persuading the consumers to install micro-renewable energy sources-based water pumping system. Among numerous energy sources, the solar-PV plays a significant role in water pumping application due to its virtuous, environment friendly, noise-free and abundant nature, so on. Along with solar-PV, the grid integrated system enables the continuous operation of water pumping system during varying temperature and irradiance conditions, and also delivers available solar-PV energy to grid during non-functional of pumping system. The above operations are carried by using bidirectional inverter which is controlled by using unit-vector control (UVC) technique. It consists of proportional-integral controller, which is not suited for regulation of DC-link voltage at desired level because of improper selection of gain values. In this work, an intelligent hybrid-fuzzy logic based UVC technique evidences the intelligent knowledge base for better regulation of DC-link voltage and power-flow of bidirectional inverter. The performance and operation of proposed hybrid-fuzzy logic control UVC technique for solar-PV/Grid integrated water-pumping system is evaluated under various operating cases by using MATLAB/Simulink tool; simulated results are conferred with superlative comparisons.

Development of Grid-Forming and Grid-Following Inverter Control in Microgrid Network Ensuring Grid Stability and Frequency Response

This paper proposes a control strategy for grid-following inverter control and grid-forming inverter control developed for a Solar Photovoltaic (PV)–battery-integrated microgrid network. A grid-following (GFL) inverter with real and reactive power control in a solar PV-fed system is developed; it uses a Phase Lock Loop (PLL) to track the phase angle of the voltages at the PCC and adopts a vector control strategy to adjust the active and reactive currents that are injected into the power grid. The drawback of a GFL inverter is that it lacks the capability to operate independently when the utility grid is down due to outages or disturbances. The proposed grid-forming (GFM) inverter control with a virtual synchronous machine provides inertia to the grid, generates a stable grid-like voltage and frequency and enables the integration of the grid. The proposed system incorporates a battery energy storage system (BESS) which has inherent energy storage capability and is independent of geographical areas. The GFM control includes voltage and frequency control, enhanced islanding and black start capability and the maintenance of the stability of the grid-integrated system. The proposed model is validated under varying irradiance conditions, load switching, grid outages and temporary faults with fault ride-through (FRT) capability, and fast frequency response and stability are achieved. The proposed model is validated under varying irradiance conditions, load switching, grid outages and line faults incorporating fault ride-through capability in GFM-based control. The proposed controller was simulated in a 100 MW solar PV system and 60 MW BESS using the MATLAB/Simulink 2023 tool, and the experimental setup was validated in a 1 kW grid-connected system. The percentage improvement of the system frequency and voltage with FRT-capable GFM control is 69.3% and 70%, respectively, and the percentage improvement is only 3% for system frequency and 52% for grid voltage in the case of an FRT-capable GFL controller. The simulation and experimental results prove that GFM-based inverter control achieves fast frequency response, and grid stability is also ensured.

Wind power forecasting technologies: A review

This study addresses the critical role of wind power forecasting in ensuring stable and reliable power system operations. Wind Power Forecasting is critical for the efficient operation of plant, time scheduling, and it’s balancing of power generation with grid integration systems. Due to its dependency on dynamic climatic conditions and associated factors, accurate wind power forecasting is challenging. The research delves into various aspects, including input data, input selection techniques, data pre-processing, and forecasting methods, with the aim of motivating researchers to design highly efficient online/offline models on weather-based data. The overarching goal is to enhance the reliability and stability of power systems while optimizing energy resource utilization. The analysis reveals that hybrid models offer more accurate results, highlighting their significance in the current era. This study investigates different Wind Power Forecasting (WPF) models from existing literature, focusing on input variables, time horizons, climatic conditions, pre-processing techniques, and sample sizes that affect model accuracy. It covers statistical models like ARMA and ARIMA, along with AI techniques including Deep Learning (DL), Machine Learning (ML), and neural networks, to estimate wind power.

Structures, Submodule Topologies and Control Strategies for Modular Multilevel Converter

Global energy demand is rapidly increasing, and the limitations and disadvantages of traditional energy sources are becoming more evident. Traditional energy sources are finite, and their sustainability is facing significant challenges. Compared to traditional multi-level converters, modular multi-level converters (MMC) adopt a modular design that divides the entire converter system into several independent sub-modules, each responsible for converting specific voltage levels. This article provides an overview of the theoretical aspects, topology structures, basic operation principles, and output characteristics of multi-level converters. This paper reviews the characteristics and application ranges of different topology structures, highlighting the differences in response speed, output quality, and control complexity. This paper also discusses the advantages and limitations of multi-level converters in various application scenarios. Explored the application of multi-level converters in wind power grid integration and electric vehicle charging systems, emphasizing their energy-saving and environmentally friendly features. In conclusion, this paper emphasizes the critical role of multi-level converters in power systems and future energy applications, stressing the importance of their reliability and promising future developments.

Assessment Criteria of Solar Hydrogen Production Plant Based on Fuzzy Multi-Criteria Decision-Making Methodology

This study presents a comprehensive solar hydrogen production plant assessment, focusing on evaluating its technological efficiency, economic viability, environmental impact, and operational reliability. Leveraging solar photovoltaic technology and electrolysis processes, the plant converts abundant solar energy into hydrogen, offering a sustainable pathway towards clean energy production. The assessment encompasses a detailed analysis of solar panel efficiency, electrolyze performance, cost-effectiveness, lifecycle emissions, and operational considerations. Findings reveal that while technological advancements drive enhanced efficiency and reliability, economic viability remains challenging due to high initial capital costs. However, the environmental benefits, including reduced carbon footprint and water usage, underscore the plant's potential contribution to a low-carbon future. Operational assessments highlight the need for scalable, grid-integrated systems with robust safety measures. Overall, the evaluation provides critical insights into the opportunities and challenges of solar-driven hydrogen production, offering recommendations to optimize plant efficiency, reduce costs, and promote its widespread adoption. We used the multi-criteria decision-making (MCDM) concept for various criteria. The SWARA method is used to compute the weights of criteria. The SWARA method is integrated with fuzzy numbers to overcome the uncertainty data. The main results show that solar production has the highest rank.

Finite Control Set Model Predictive Control (FCS-MPC) for Enhancing the Performance of a Single-Phase Inverter in a Renewable Energy System (RES)

A single-phase five-level T-type topology has been investigated in this article. This topology has emerged as a viable option for renewable energy systems (RES) due to its inherent benefits. The finite control set model predictive control (FCS-MPC) strategy has been implemented to this topology in order to improve the performance and overall reliability of the system. This control strategy empowers the inverter to predict future behavior based on a discrete set of control signals, enabling precise modulation and high-speed response to system dynamics. In the realm of RES, integration of FCS-MPC with multilevel inverters (MLIs) holds great potential to enhance energy conversion efficiency, grid integration, and overall system reliability. The article is structured to present an overview of the evolving landscape of power electronic systems, and the advantages of FCS-MPC. This paper provides a comprehensive analysis of the FCS-MPC control strategy applied to the single-phase five-level T-type topology. The study covers various aspects including the theoretical framework, hardware development, and experimental evaluation. It is obvious from the analysis that this inverter topology is reliable. Several redundant states make it fault-tolerant which helps in maintaining the output voltage at the same level even in the fault conditions. Additionally, the results show that the output load voltage is maintained at the same level irrespective of load change. Also, output load voltage has maintained the high-quality sinusoidal characteristics as the total harmonic distortion (THD) is very low. With all these features, this system is suitable within the framework of RES.

Investigation of a grid-integrated hybrid energy system for residential and electric vehicle (3-wheeler) loads under schedule grid outage

Due to the global energy crisis and the limited availability of conventional fuels and their reserves in certain areas, the utilization of renewable energy resources is significantly paramount for sustainable development. Grid disruptions have been discovered in areas where demand for electricity has surpassed supply. The purpose of this work is to size a grid-integrated hybrid renewable energy system (HRES) during a scheduled power outage. The HRES model was created to meet the requirements for residential load as well as EV charging load at midnight when the residential load is lower. Using the HOMER Pro software tool, the HRES system is developed to satisfy the residentialload demand of 1940 kWh/day and the electric vehicle (3-wheeler) charging load requirement of 645 kWh/day, respectively. This study examined the effects of grid purchasing capacity and grid scheduling outages on techno-economic and environmental performance. The results show that the most optimal configuration among the various configurations is the PV/WT/Batt with grid-integrated system, which has a COE of 0.0714 $/kWh, an NPC of $1,822,653, and emits 164,812 kg/yr of CO2 into the environment. The optimized system consists of a 377 kW PV module, a 2 kW wind turbine, an 836 kWh battery bank, and a 237 kW inverter. In addition, the impacts of sensitivity of the grid purchase and selling capacity, and the different tariffs on the techno-economic indicators of the HRES have been investigated. The daytime grid outage lowers environmental emissions and increases the renewable contribution compared to the grid outage at night. Reducing the grid’s purchase capacity while increasing the share of renewable energy provides significant advantages. The stand-alone PV/Batt has a higher COE (0.26 $/kWh) than the PV/Batt system (0.072 $/kWh) with the net metering option connected to the national grid.

Comparative analysis of control techniques using a PV-based SAPF integrated grid system to enhance power quality

The deterioration of power quality due to the increased adoption of Power Electronic Switching Devices is a major concern for electrical engineers. In addition to industrial loads, household loads cause numerous disturbances on the utility side, such as sags, ripples, flickers, and harmonics. It is possible to create power quality problems in a system or to have them arise due to a faulty consumer. This paper implements a renewable energy system with a Shunt Active Power Filter (SAPF) that injects PV energy into a power grid in the presence of nonlinear loads and under various load conditions to maintain power quality and improve power grid capacity. The Perturb and Observe (P&O) algorithm adjusts boost converter duty cycles to track the Maximum Power Point (MPP). The boost converter output is connected to the grid via a SAPF. The effectiveness of SAPF in reducing total harmonic distortion has been investigated using various reference current generation strategies of control methods and improved maximum power factor. The voltage source inverter switches are controlled through hysteresis current control. Moreover, this paper explains how to regulate the dc link capacitor of a three-phase SAPF with PI, fuzzy, and Adaptive Fuzzy Neuro Inference System (ANFIS) controllers to enhance power quality and compensate for reactive power and harmonic current caused by nonlinear loads. This system is developed under balanced and unbalanced nonlinear loads in MATLAB-Simulink. Furthermore, SRF-based reference current generation techniques with ANFIS controller to achieve better performance tested for control performance in proto-type hardware model to validate the proposed performance of this system.

Precise Dynamic Modelling of Real-World Hybrid Solar-Hydrogen Energy Systems for Grid-Connected Buildings

Hybrid renewable hydrogen energy systems could play a key role in delivering sustainable solutions for enabling the Net Zero ambition; however, the lack of exact computational modelling tools for sizing the integrated system components and simulating their real-world dynamic behaviour remains a key technical challenge against their widespread adoption. This paper addresses this challenge by developing a precise dynamic model that allows sizing the rated capacity of the hybrid system components and accurately simulating their real-world dynamic behaviour while considering effective energy management between the grid-integrated system components to ensure that the maximum possible proportion of energy demand is supplied from clean sources rather than the grid. The proposed hybrid system components involve a solar PV system, electrolyser, pressurised hydrogen storage tank and fuel cell. The developed hybrid system model incorporates a set of mathematical models for the individual system components. The developed precise dynamic model allows identifying the electrolyser’s real-world hydrogen production levels in response to the input intermittent solar energy production while also simulating the electrochemical behaviour of the fuel cell and precisely quantifying its real-world output power and hydrogen consumption in response to load demand variations. Using a university campus case study building in Scotland, the effectiveness of the developed model has been assessed by benchmarking comparison between its results versus those obtained from a generic model in which the electrochemical characteristics of the electrolyser and fuel cell systems were not taken into consideration. Results from this comparison have demonstrated the potential of the developed model in simulating the real-world dynamic operation of hybrid solar hydrogen energy systems for grid-connected buildings while sizing the exact capacity of system components, avoiding oversizing associated with underutilisation costs and inaccurate simulation.

A novel solar photovoltaic powered grid interactive battery charging system for electric vehicle applications

ABSTRACT In this work, a novel Solar Photo Voltaic (SPV) powered grid interactive Electric Vehicle (EV) battery charging system has been proposed and validated. The objective of the proposed system is to provide seamless battery charging facility that includes a high capacity station battery system. The grid interactions like integration of SPV energy, station battery charging and reactive power support are included through the DC link of aShunt Active Power Filter (SAPF). The SAPF maintains unity power factor on the source side grid current. The objectives of the proposed system are ensuring the source side power factor nearly unity with minimal THD of source current, an SPV grid integration system with Maximum Power Point Tracking (MPPT), a comfortable charging point for EVs with a reliable charging station supported by a back up station battery. The novelty of the proposed work is that the common DC bus bar maintains a high DC link voltage when the utility source is available and the SAPF is active. The regulation of the DC link voltage is achieved by a PI controller tuned by the Gravitational Search Algorithm. The proposed system has been validated using simulations in the MATLAB SIMULINK environment as well using an experimental prototype. The proposed GSA controller outperforms in terms of THD (%) of source and load currents are 2.4 and 17.87, respectively.

Stability Improvement of Wind Farm by Utilising SMES and STATCOM Coupled System

The rising number of intermittent wind energy-based generation systems in power systems affects the grid system’s stability and reliability. These wind generators reduce the inertia of the system, thus making the system sensitive to grid disturbances. Due to their unique features, the Doubly Fed Induction Generators (DFIG) wind generators are being connected at a large scale. The Energy Storage Device (ESD) offers a viable solution to the integration issues caused by variable-natured renewable energy sources. In this work, the Static Compensator (STATCOM) is attached to the Superconducting Magnetic Energy Storage (SMES) technology to strengthen the wind farm integrated grid system for better performance. The SMES is interlinked with the grid system via a power electronic interface (PEI) and chopper for the energy exchange. This work examines the functioning of the proposed STATCOM as PEI and three-level chopper control circuit based on fuzzy logic for the SMES system. The fuzzy logic based SMES with STATCOM (STAT-SMES) is proposed for a DFIG-based integrated system under different fault conditions. This coupled controller can compensate for both real and reactive powers, improve voltage stability, and can damp power oscillations at a fast rate. The results have been compared without any controller, with STATCOM only, and with the proposed, fuzzy based SMES coupled to STATCOM using MATLAB. The simulation outcomes prove that coupling SMES to STATCOM is effective in handling wind farm integration issues in a better way than STATCOM.

Fast and Robust Adaptive LMAT Control for Power Quality Improvement in Grid-Tied SPV System

This paper deals with the power quality improvement in a double stage solar photovoltaic (SPV) grid integrated system by an adaptive least mean absolute third (LMAT) control. This topology has advantages such as, (1) it has high efficiency, and (2) it provides an enhanced response. This SPV generating system consists of many components such as, a BC (Boost converter), a RC ripple filter, a VSC (Voltage source converter), local loads, and a 3-ɸ grid. Here, the VSC is connected at DC bus for feeding SPV power into the three-phase grid, which is also used to improve the power quality. An adaptive LMAT control estimates the fundamental load components, which provides the fast rate of convergence and less steady state error. The THDs (Total Harmonic Distortions) of grid currents are shown within the limits of the IEEE-519 standard.

Optimal control for a photovoltaic integrated grid system using PSO and modified whale optimization to enhance power quality

The paper proposes a modified & optimized controller for PV-integrated grid-connected PV systems. As the solar power output depends on the environmental conditions, i.e., irradiation and atmospheric temperature, the maximum power from the photovoltaic (PV) module is extracted using perturb and observe (P & O) algorithm. With a variety of controllers, such as conventional proportional and integral (PI) controllers, particle swarm optimization (PSO), and the modified Whale optimization algorithm (MWOA) method based on optimum control, the power as compared to extracted from PV panels using MWOA-based controllers. A complete simulation and implementation of a single-phase grid-connected inverter are shown to verify the proposed PV controller. The power flow control and grid synchronization are also presented when the above controllers act as MPPT controllers in the proposed system. The performance of proposed system is evaluated and compared among conventional and optimal controllers under a MATLAB-Simulink environment.

PV-Fed Micro-Inverter with Battery Storage for Single Phase Grid Applications

Nowadays, micro-inverters are trending due to the latest features consisting in PV technology. However, integration of a high-gain boost converter is needed to improve the low rating output voltage of PV modules to meet the load demand. A high-gain converter with less component count is required for grid integration systems. This article proposes a new quasi z-source based high-gain DC–DC converter with reduced components, cost, and size. The proposed converter is integrated with the micro-inverter for single-phase grid applications along with battery storage. A radial basis function network algorithm is utilized for a PV system to track the maximum power point, an efficient hysteresis current controller is applied for the full-bridge inverter for the robust regulation of current and the energy can be stored through the bidirectional dc/dc converter to supply the power to grid when the sources are drained conditions. An efficient PV extraction, low total harmonic distortion and achieves unity power factor which is perfectly suitable for grid-connected PV systems. The operating modes in every aspect and analysis of the proposed configuration have been investigated in detail. The implementation of control strategies is discussed in detail. Simulation of the proposed micro-inverter is designed in MATLAB/SIMULINK tool to validate the efficiency under variable operating conditions. With the successful implementation of the proposed technique, total harmonic distortion is reduced to 2.05% and efficiency is enhance to the 98%.

Impact of plug-in electric vehicles on grid integration with distributed energy resources: A review

The rise of electric vehicles (EVs) has a massive impact on the electricity grid due to the electrification of vehicles in the transportation sector. As a result, various techniques are needed to minimize the effects of charging on the grid. One of these techniques is having intelligent coordination between the various components of the EV charging network. This ensures that the network has enough electricity to support the charging needs of the vehicles. This article provides an overview of the many aspects of the EV industry and its charging infrastructure. It also provides a step-by-step approach for implementing the Vehicle to Grid (V2G) deployment, the utilization of recordings from the data by the EV battery through Artificial Intelligence and the cost-benefit analysis from effective utilization of the V2G method. The paper also explores the various aspects of the EV market and the role of aggregators and consumers. Finally, it assesses the possibility of expansion of the EV charging and grid integration system and outlines its challenges and solutions.

Cascade feedforward neural network and deep neural network controller on photovoltaic system with cascaded multilevel inverters: Comparison on standalone and grid integrated system

The introduction of a micro-grid-based power generation network will help to meet the demands of consumers while reducing environmental impact. Several industrialized and emerging countries allocate considerable resources to renewable energy-based power generation and invest significant sums of money in this area. This study examines the challenges involved with electricity generation through photovoltaic (PV) systems and the integration of the same with the grid to mitigate power quality issues and improve the power factor for various loading conditions. An innovative multilayer inverter for grid-connected PV systems has been developed to enhance the voltage profile and resulted in a drop in total harmonic distortion (THD). A cascade multilevel inverter (associated with a grid-integrated PV system and managed using multiple innovative artificial intelligence controllers) was developed in this research project. Various advanced intelligent controllers, such as cascade feedforward neural networks (CFFNN) and deep neural networks (DNN), have been analyzed under various operating situations and observed that the THD of voltage, current at the grid, and the load is less than 3 % as per the IEEE 519 standards along with this power factor is maintained nearly unity for the grid-connected system. The quality of power in terms of voltage, frequency, total harmonics distortion, and power factor are improved by using a novel deep neural network algorithm in a cascaded multilevel inverter and verified according to IEEE 1547 and IEEE 519 standards to determine the efficacy of the proposed system.

Wind Energy Harvesting and Conversion Systems: A Technical Review

Wind energy harvesting for electricity generation has a significant role in overcoming the challenges involved with climate change and the energy resource implications involved with population growth and political unrest. Indeed, there has been significant growth in wind energy capacity worldwide with turbine capacity growing significantly over the last two decades. This confidence is echoed in the wind power market and global wind energy statistics. However, wind energy capture and utilisation has always been challenging. Appreciation of the wind as a resource makes for difficulties in modelling and the sensitivities of how the wind resource maps to energy production results in an energy harvesting opportunity. An opportunity that is dependent on different system parameters, namely the wind as a resource, technology and system synergies in realizing an optimal wind energy harvest. This paper presents a thorough review of the state of the art concerning the realization of optimal wind energy harvesting and utilisation. The wind energy resource and, more specifically, the influence of wind speed and wind energy resource forecasting are considered in conjunction with technological considerations and how system optimization can realise more effective operational efficiencies. Moreover, non-technological issues affecting wind energy harvesting are also considered. These include standards and regulatory implications with higher levels of grid integration and higher system non-synchronous penetration (SNSP). The review concludes that hybrid forecasting techniques enable a more accurate and predictable resource appreciation and that a hybrid power system that employs a multi-objective optimization approach is most suitable in achieving an optimal configuration for maximum energy harvesting.

Modeling and Control Design of Wind-Battery Integrated Grid System

Due to the large amount of increase in wind power generation in the past decade, the wind-battery storage systems are needed. Using such systems can neutralize the power fracture and instability caused by wind power production. This paper begins with reviewing the system components, mainly wind turbine (WT) and battery energy storage system (BESS), including how they work, what problem they resolve, and what challenges they are facing. Then this paper will present mathematical modeling methods for those components and the wind-battery integrated system itself. Finally, different control methods will be reviewed.

Fault Classification and Localization Scheme for Power Distribution Network

In this paper, a fault protection diagnostic scheme for a power distribution system is proposed. The scheme comprises a wavelet packet decomposition (WPD) for signal processing and analysis and a support vector machine (SMV) for fault classification and location. The scheme is tested on a reduced Eskom 132 kV power line. The WPD is used to extract fault signatures of interest and the SVM is subsequently used for fault classification and locating various fault conditions. Furthermore, we investigate the effectiveness of the SVM scheme using different samples of the cycles for fault classification and location. The results show that the fault classification and location on a distribution line can be determined rapidly and efficiently irrespective of the fault impedance and incipient angle with minimum estimation error. Lastly, the proposed scheme is tested on a grid-integrated system with renewable energy sources.