Hybrid Distributed Generation System Research Articles

Analysis of the Behavior of the Electromagnetic Frequency Regulator (EFR) Used in Hybrid Wind-Solar Photovoltaic Generation Systems

Within the context of integrating renewable energy sources, the Electromagnetic Frequency Regulator (EFR) presents a promising technology, particularly in hybrid distributed generation systems. This paper conducts a comprehensive analysis of pole pair configurations for both the EFR and the induction generator within such systems to enhance overall performance. An algorithm developed in Scilab is utilized for steady-state analyses considering various configurations. The methodology involves repetitive computations to evaluate the angular velocity of both the EFR and the generator, as well as the transformation ratios of the speed multiplier for different pole pairs. Scenarios with varying combinations of pole numbers are explored, demonstrating the impact on EFR velocity and the drive frequency of the EFR. Results showcase the efficacy of the proposed algorithm, providing insights into the selection of the most appropriate pole pairs to improve system performance.

A novel hardware implementation approach to enhanced stable island operation of hybrid distributed generation using superconducting fault current limiters

In this research study, we have explored the transformative potential of integrating Superconducting Fault Current Limiters (SFCLs) and Superconducting Magnetic Energy Storage (SMEC) systems in hybrid distributed generation setups. Through a meticulous series of experiments, simulations, and detailed analyses, we have delved into the dynamic responses of these advanced technologies amidst various grid disturbances and fault scenarios. Our investigations encompassed a spectrum of grid disturbance scenarios, including voltage sags, frequency variations, and short circuits, revealing the crucial role that SFCLs and SMEC play in maintaining stable islanded operation. The numerical results showcased in this study demonstrate the pivotal role of SFCLs and SMEC in swiftly responding to grid disturbances, effectively limiting fault impacts and ensuring a continuous and uninterrupted power supply to critical loads. For instance, SFCLs reduced fault currents by up to 60 % within 15 ms during short circuit events at Node A, while voltage sags of 20 % were mitigated within 75 ms, showcasing a fault clearing time of 45 ms. Additionally, the SMES system's energy capacity of 10 kWh played a significant role in voltage and frequency stabilization, reducing fault impacts by over 50 % during various fault scenarios. Furthermore, our detailed analyses provide valuable insights into the SFCL performance, including activation times and fault current reduction capabilities. The transient responses of the system exemplify the remarkable ability of SFCLs to expedite fault recovery and stabilize microgrids. This study presents a novel hardware implementation approach aimed at enhancing the stable island operation of hybrid distributed generation systems through the integration of SFCLs and SMEC. The research addresses the pressing need for innovative solutions to ensure grid stability and reliability amidst the increasing penetration of renewable energy sources. Through hardware simulations, the effectiveness of SFCLs in limiting fault currents and improving system stability is demonstrated. Moreover, a quantitative comparison with existing solutions highlights the superiority of the integrated SFCL-SMES system in enhancing stable island operation, with fault tolerance improvements of up to 56 % compared to traditional methods. Overall, this research contributes to advancing the field of hybrid distributed generation and fault management, offering valuable insights into the practical implementation of SFCLs and SMES for grid resilience and reliable renewable energy integration.

Design of a stand-alone hybrid dispersed generation network unified by passivity-based control.

In this article, we propose a model for a stand-alone hybrid distributed generation system. In this model, the input sources are distributed DC sources like solar panels or batteries. The idea behind this network framework is to introduce a hybrid DC/AC network, feasible for small and remotely located areas with stand-alone DC grids, in the vicinity of larger towns requiring a functional AC connection. The behaviour of the system in the steady state is analysed, and the network is mathematically represented with port-controlled Hamiltonian modelling. Stabilization to the desired voltage, both AC as well as DC, is attained with nonlinear passivity-based control taking into consideration not only the energy characteristics but also the inherent physical structure.

Hybrid Power Systems Planning with Geographical Information System Models

This paper presents planning models for hybrid distributed generation systems, as well as the results corresponding to a distribution system planning problem obtained using a new computational tool based on a Geographic Information System, GIS. This computational tool is a powerful instrument for analyzing energy resources and energy conversion technologies that can be used for the distribution networks expansion. It has been used in the economic evaluation of energy produced by hybrid systems. Thus, suitable models and techniques have initially been applied to obtain maps of solar and wind energy resources in a user defined area and maps of costs for hybrid systems, identifying the geographical locations that offer the best economic potential in distributed generation with renewable hybrid systems, supported (or not) with fuel to supply internal-combustion electric generators. Accurate evaluations of the cost of the produced energy need the use of geographic distributed costs corresponding to refuelling, installation and maintenance of the hybrid system. The developed software tool is flexible, appropriate for studying different scenarios, and enables geographical analysis of the economic competitiveness of the hybrid systems with different distributed generation resources (photovoltaic, wind, hydraulic or biomass energy systems), and it is suitable to study the optimal expansion of existing power distribution networks (isolated hybrid systems versus connected ones).

A communication-less islanding detection scheme for hybrid distributed generation systems using recurrent neural network

The proposed scheme in this research paper is a communication-less islanding detection system based on recurrent neural network (RNN) for hybrid distributed generator (DG) systems that include both synchronous and inverter-based DG devices. The scheme consists of three stages: time-domain feature extraction (FE) from the three-phase voltage signal at the point of common coupling (PCC), feature selection using the wrapper method, and detection using a long short-term memory (LSTM) RNN algorithm. To assess the performance of the proposed scheme, a comprehensive set of islanding and grid-connected scenarios was created using the IEC 61850-7-420 test system in MATLAB/Simulink. After feature extraction in MATLAB, the feature selection and LSTM model training/testing steps were conducted in Python. Thirteen features were extracted from the voltage signal, and the most significant features were selected for detection using the wrapper method. The detection process encompassed various events, such as line faults, load switching, and capacitor switching, occurring in both islanded and grid-connected modes. The proposed scheme was compared against existing techniques, artificial neural networks, and support vector machines under the same conditions. The proposed scheme demonstrated excellent accuracy (99.68 %), selectivity (99.44 %), and sensitivity (100 %) under normal conditions with all features. It also performed well in noisy environments, with accuracies of 98.94 % and 97.04 % with 40 dB and 30 dB noise, respectively. This research highlights the importance of quality and quantity of data for training intelligent RNN-based IDSs and demonstrates the effectiveness of the proposed scheme in detecting islanding in hybrid DG systems.

Zero power mismatch islanding detection algorithm for hybrid distributed generating system

Distributed generation is essential for both keeping up with the rising power demand and reducing the amount of money spent on fossil fuels. There is widespread agreement that the world should prioritize the development of renewable energy systems such as wind and solar energy. This study describes the design and utility-grid integration of a hybrid distributed generating system that utilizes photovoltaic and wind-driven permanent magnet synchronous generators (hybrid PMSG-PV systems). To prevent damage to the grid, hybrid distributed generation systems, consumer devices, and line workers must be protected from islanding. Detection of islanding in hybrid DG systems has been suggested using passive islanding and time-spectral analysis. Measuring and amplifying the ripple content present in voltage at point of common coupling (PCC) about 0.4 seconds after the permissible delay time after the circuit breaker opens on the utility grid side is how islanding is discovered using this method. Compared to other methods, the proposed method has smoother islanding detection waveforms owing to increases in both the window size and threshold limit. The suggested method detects islanding in 40 ms and is verified in a variety of non-islanding scenarios, such as fault occurrence, parallel feeder loss, and load shift. In addition, the cost is reduced, the response time is rapid, and there is no non-detection zone (NDZ) when using these methods. Unlike active islanding detection methods, their function is unaffected by the size, quantity, or type of distributed generators linked to the utility grid; hence, there are no power quality concerns.

Multifunctional Control Technique for Grid-Tied Hybrid Distributed Generation System Taking into Account Power Quality Issues

This paper proposes a new multifunctional control technique for a grid-connected hybrid distributed generation system composed of a photovoltaic system and a wind power system based on a voltage source converter (VSC). Indeed, aside from the generation and the injection of energy into the grid, the proposed system deals with power quality issues caused by harmonics generated by non-linear loads in order to keep the source current uncontaminated. The VSC serves to first ensure that the power generated from the hybrid renewable energy source is fed to the utility grid and acts as a shunt active power filter in case an abnormal increase in the THD of the source current above the standard permissible values is detected due to the non-linear load connection. The two sources of the hybrid system are connected to a common DC bus to simplify the control and reduce the cost of the system, and a maximum power point tracking controller is used for both sources. The major advantage of this novel proposed multifunctional control technique is its ability to inject harvested power into the grid while simultaneously ensuring the compensation of the harmonics and reactive power. The proposed multifunctional control technique is validated through an extensive simulation analysis using MATLAB/Simulink.

Passive Island Detection Method Based on Positive Sequence Components for Grid-Connected Solar–Wind Hybrid Distributed Generation System

This paper presents the development and practical implementation of a new passive island detection method for grid-connected hybrid distributed generating systems. The method employs positive sequence voltage and current components at the point of common coupling. The product of the difference in positive sequence voltage and the difference in positive sequence current is used to produce the Islanding Detection Index (IDI). Islanding is identified when the IDI magnitude surpasses a predefined threshold over a predefined delay time. Even in the case of a zero power mismatch condition, the proposed method can identify the islanding condition in under 70 msec. Its effectiveness is validated under various operating circumstances. It provides excellent stability against various non-islanding situations, avoiding unwanted tripping. The suggested method also has the advantages of being simple and inexpensive to implement, having no adverse effects on output power quality, not requiring a classifier, not being system-dependent, and working regardless of the quantity and type of distributed generation connected to the utility grid. The obtained detection timings were compared to those previously reported in the literature, confirming the proposed approach’s superiority. The suggested work utilizes the OPAL-RT real-time hardware-in-loop environment and MATLAB/Simulink.

Optimal allocation of solar and wind distributed generation using particle swarm optimization technique

<span lang="EN-US">Power demand in the current days is increasing more and more where the conventional power generation systems are failing to meet these power demands due to less availability of non-renewable resources. Hence, many of the researchers are working on the distributed generation (DG) by using renewable resources like wind and solar. The penetration towards wind, solar DG faced challenging situations during power generation due to uncertainty in the wind speed and solar radiation. Recent studies have predicted that the combination of both solar and wind can lead to better performance. However, the sizing and placement of DG systems is necessary to achieve efficiency otherwise the systems may lead to adverse effects in distribution networks. This paper introduced the solar DG, wind DG and hybrid (solar and wind) DG system. The particle swarm optimization technique is used to size and place the DG because of its parallel search capability. Also, the combination of wind-solar DG gives better DG sizing in the respective DG location. The voltage profile of these DG systems has shown better results for the efficient power system. In comparison to conventional DG systems, the suggested hybrid DG system is capable of minimizing power loss and maintaining voltage profile.</span>

Analysis and Power Quality Improvement in Hybrid Distributed Generation System with Utilization of Unified Power Quality Conditioner

This paper presents a comprehensive study that includes the sizing and power flow by series and parallel inverters in a distributed generation system (DGs) that integrates the system of hybrid wind photovoltaic with a unified power quality conditioner (UPQC). In addition to supplying active power to the utility grid, the system of hybrid wind photovoltaic functions as a UPQC, compensating reactive power and suppressing the harmonic load currents. Additionally, the load is supplied with harmonic-free, balanced and regulated output voltages. Since PVWind-UPQC is established on a dual compensation scheme, the series inverter works like a sinusoidal current source, while the parallel inverter works like a sinusoidal voltage source. Consequently, a smooth alteration from interconnected operating modes to island operating modes and vice versa can be achieved without load voltage transients. Since PV-Wind-UPQC inverters handle the energy generated through the hybrid wind photovoltaic system and the energy demanded through the load, the converters should be sized cautiously. A detailed study of the flow of power via the PV-Wind-UPQC is imperative to gain a complete understanding of the system operation and the proper design of the converters. Thus, curves that allow the sizing of the power converters according to the power flow via the converters are presented and discussed. Simulation results are presented to assess both steady state and dynamic performances of the grid connected hybrid system of PV-Wind-UPQC. This investigation is verified by simulating and analyzing the results with Matlab/Simulink.

Energy management and harmonic compensation of micro‐grids via multi‐agent systems based on decentralized control architecture

AbstractHere, a new energy management strategy based on a multi‐agent structure is presented by introducing hybrid control of AC micro‐grid (MG), where current harmonics compensation is also considered. This energy management strategy is based on Mealy machine in a multi‐agent system (MAS), which is implemented by generating coordination signals and sending them to the renewable energy sources (RES). In RES, maximum power point tracking (MPPT) or reverse of Hill‐climbing (RHC) is used based on these received coordination signals to limit the exchange power between the MG and the grid. Also, the multi‐agent structure of shunt active power filters (SAPFs) and passive filters have been studied in power MGs. The comparison of MG current harmonic compensation by these filters by fast Fourier transform (FFT) algorithm has been investigated in the proposed network. The simulation results show that the proposed energy management system (EMS) with proper management of MG different agents has been able to have a suitable performance for hybrid distributed generation (DG) systems. Also, the SAPF with better and more appropriate harmonic compensation than the SC‐RC‐LCL passive filter can eliminate the harmonic pollution of MG and be used with high performance in hybrid DG systems.

Experimental verification of STATCOM based on quasi impedance source inverter for power quality enhancement in the hybrid distributed generation system

PurposeThis paper aims to introduce the quasi impedance source inverter (qZSI)-based static compensator (STATCOM), which is incorporated into the hybrid distributed power generation system for enhancement of power quality. The distributed power generation system includes the photovoltaic (PV), wind energy conversion system (WECS) and battery energy storage system.Design/methodology/approachThe WECS is used by the self-excited induction generator (SEIG) and the flywheel energy storage system (FESS). To regulate its terminal voltage and frequency, the SEIG requires adjustable volt-ampere reactive (VAR). A combination of a STATCOM and a fixed condenser bank usually serves to satisfy the VAR demand. The maximum correntropy criterion-based adaptive filter technique (AFT) is proposed to control the qZSI-STATCOM and to guarantee that the voltage at the SEIG terminal is harmonic-free while providing non-linear three-phase and single-phase loads.FindingsThe coordinated operation of the suggested voltage control and flywheel control systems ensures that load voltage and frequency are retained in their respective values at very low harmonic distortions regardless of wind speed and load variation. The simulation and experimental studies are carried out under different load conditions to validate the efficiencies of the PV-assisted STATCOM.Originality/valueTo improve system stability and minimize total costs, extra load current sensors can also be avoided. This paper proposes to control the SEIG terminal voltage and harmonic elimination in the standalone WECS systems using maximum correntropy criterion-based AFT with a fuzzy logic controller.

Load frequency stabilization of stand‐alone hybrid distributed generation system using QOHS algorithm

AbstractThe proposed work studies the frequency stability of the identified hybrid power network (HPS) model with the integration of RESs and ESDs. The research work depicted here includes load frequency issue pertaining to isolated mode of operations with uncertainties in power oscillations of wind and solar energy. The studied HPS model is constitute of three wind turbine generators, two solar thermal generators, three diesel engine generators, an aqua electrolyzer and two fuel‐cells as generating units while battery energy storage system, flywheel energy storage system and ultra‐capacitor as back‐up energy sources. A centralized control scheme using PID controller is employed for the controller design problem and its parameters are tuned by a nature inspired Quasi‐oppositional Harmony Search (QOHS) algorithm. The three scenarios as step change, step change with stochastic effects and firm model of wind velocity, solar radiation and load demand are studied for the load frequency control dynamic performance. The execution of suggested QOHS based PID controller is contrasted with the studied optimization techniques. It may be inferred that the RESs and ESDs feeding isolated loads are properly operated to attain the coveted level of system frequency by using the QOHS technique.

An Intelligent Deep Convolutional Neural Networks-Based Islanding Detection for Multi-DG Systems

Unintentional islanding is a problem in electrical distribution networks; it happens when the central utility is unintentionally separated from the rest of the distributed power system. The islanding detection problem becomes severe in non-detection zones. We propose an intelligent islanding detection technique with zero non-detection zone for a hybrid distributed generation system. It is based on the computation of frequency spectrum variations over time using short-term Fourier transform and convolutional neural networks. For various islanding and non-islanding occurrences, the three-phase voltage at the point of common coupling is monitored, and time-series data is collected. Then computations for a set of multiple frequencies on scaled time-series data are carried out, and complex numbers are split into magnitude and phase values. To detect islanding and non-islanding occurrences, a modified convolutional neural network with forward propagation was utilized. For the IEC 61850-7-420 test system, several islanding and non-islanding scenarios are created and deployed to train the convolutional neural network for the proposed approach. The efficacy of the proposed islanding detection learning model is assessed using 5-fold cross-validation. The findings reveal that under normal and noisy conditions, the proposed methodology has zero non-detection zone with original dataset, excellent accuracy, selectivity, and sensitivity.

Novel Control Approach with FRT capability for Grid connected HYBRID distributed generation system using ANN controller based DVR

Abstract: For ever increasing power demand and depletion of conventional energy resources, Renewable Energy Systems (RES) became an alternative source of electricity to reduce the load stress on the Power Grid. Although several control & design modifications are presented in past literature to improve reliability & performance of through Distribution Generation (DG) technologies, they always fall short in some aspects of voltage stability and Fault Ride Through (FRT) capabilities. The main aim of the project is Protecting Critical load from Grid side altercations which occur due to harmonics generated by DG’s and Short circuit faults near to load center. This project proposes the application of a Dynamic Voltage Restorer (DVR) to enhance the power quality and improve the Fault Ride Through (FRT) capability of a three-phase medium-voltage network connected to a hybrid distribution generation (DG) system. In this hybrid farm, the Photo Voltaic (PV) plant via single-stage energy conversion (DC-AC inverter) & DFIG (Doubly-Fed Induction Generator) based Wind power plant are connected to the same Point of Common Coupling (PCC). For MPPT of wind power plant, we use Pitch Angle Control (PAC) technique. This topology allows Perturb and observe (P&O) based MPPT algorithm for PV plant through connection of the DG (Distribution generation) system to the public grid through a step-up transformer. In addition, the DVR based on Artificial Neural Network (ANN) controller is connected to the same PCC. Different fault condition scenarios are tested for improving the efficiency and the quality of the power supply and compliance with the requirements of the sensitive Load. The efficiency of this control technique is that it enhances restoration and harmonics suppression capabilities of DVR which are far superior than that of PI controller used in existing model. Keywords: RES, DG, LVRT, FRT, PV, DFIG, PCC, MPPT, P&O, DVR, PI, ANN, THD, Voltage stability.

Genetic Algorithm Based Power Control Strategies of a Grid Integrated Hybrid Distributed Generation System

In this manuscript, a genetic algorithm (GA) is proposed for the power management (PM) of a grid integrated hybrid distributed generation (DG) system. The hybrid distribution generation (DG) system incorporates photovoltaic (PV), wind turbine (WT), fuel cell (FC) and battery. The power fluctuations are produced in the distributed generation system, because the hybrid resource utilization and the generation of power is changeable. The major purpose of the proposed control method is “to control the power flow (PF) of active with reactive energy amid the source and grid side. The proposed GA-based power control system is mainly utilized for optimizing active with reactive power flow controllers. By controlling charge with discharge of battery, the proposed system met the energy requirement of the charge and managed the sensitivity of the charge. The proposed method provides an optimal power flow in DG systems. To evaluate the management of PF, the equality with inequality constraints is determined that is used to specify the accessibility of renewable energy sources (RES), the demand for electricity and storage components load level. The security of power system is improved with the help of proposed control system. Moreover, the battery is used to allow the renewable energy system and maintain a stable power output. The proposed method is activated in MATLAB / Simulink work site and the performance is compared with existing methods. The statistical analysis of mean, median and standard deviation (SD) are also analyzed for proposed with existing methods. The proposed technique mean value is 1.5784, median is 1.4892, SD is 0.5883.

Power Management System of a Particle Swarm Optimization Controlled Grid Integrated Hybrid PV/WIND/FC/Battery Distributed Generation System

In this manuscript, the Power management of grid integrated hybrid dis-tributed generation (DG) system with Particle swarm optimization (PSO)algorithm is proposed. The hybrid DG system combines with photovoltaic,wind turbine, fuel cell, battery. Depending on the use of hybrid sources andthe changes of power production the variation of power can occurs in the DGsystem. The major purpose of the proposed method restrains the power flow(PF) on active with reactive power between the source and grid side. In thepower system control the proposed PSO method is utilized to maximize theactive with reactive PF and the controllers. The proposed method interact theload requirement energy and maintain the load sensitivity due to chargingand discharging battery control. In the DG system, the proposed PSO methodallows maximum power flow. To assess the PF, the constraints of equalityand inequality have been evaluated and they are utilized to determine theaccessibility of renewable energy source (RES), electricity demand, and thestorage elements of charge level. The protection of the power system is enhanced based on the proposed PSO method. Additionally, for retaininga stable output the renewable power system and battery is used. The pro-posed method is activated in MATLAB/Simulink working platform and theefficiency is likened with other existing methods.

A Novel Time-Domain Passive Islanding Detection Technique for Grid-Connected Hybrid Distributed Generation System

In this paper, a time-domain passive islanding detection technique for a grid-connected hybrid distributed generating system has been developed using modified empirical mode decomposition (MOEMD). With the help of the MOEMD, the point of common coupling voltage is decomposed into several oscillatory components called intrinsic mode functions. The islanding will be detected if the magnitude of the islanding detection waveform exceeds the threshold over a predefined delay time. The proposed technique can identify all kinds of islanding cases even for zero power mismatches nearly at 0.3 s of the predefined delay time. The effectiveness of the proposed scheme is tested for different operating conditions that include various non-islanding events. Moreover, the proposed method is faster than the discrete wavelet transform technique, and it has low computational time. The advantages of the proposed method are independent of the system parameters, zero non-detection zone, no classifier requirement, and its performance is independent of the capacity and nature of D.G. connected to the grid.

A New Architecture Topology for Back to Back Grid-Connected Hybrid Wind and PV System

In this paper, a new grid-connected hybrid distributed generation system architecture has been proposed. The proposed architecture provides an efficient power transfer with a reduced number of power converters and conversion stages as compared to existing architectures. In this proposed architecture, the wind and solar PV hybrid generation system is coupled to the grid with a back-to-back voltage source converter. The Photovoltaic (PV) array is attached instantly to the dc-link bus without any intermediary power converters and maximum power is extracted from the solar PV system by Maximum Power Point Tracking (MPPT) algorithm and the output voltage of the PV system is given to the dc-link. Permanent Magnet Synchronous Generator (PMSG) is connected to the wind turbine system and it delivers maximum power with an optimal torque control algorithm and further, it generates reference currents for Wind Side Converter (WSC). The merit of the proposed scheme is that peak power is obtained from both the energy sources with two independent MPPTs. Further, the DC link voltage is inverted and can synchronize with the grid by employing Grid Side Converter (GSC). The proposed work has been implemented using MATLAB/Simulink under various modes of power transfer conditions.

Benefit Cost Analysis of Electrification of Urban Districts: Case Study of Philadelphia, Pennsylvania

AbstractIn this paper, the results of a feasibility analysis are summarized to assess the energy, economic, and environmental benefits of electrification and renewable energy integration for an urban district of Old City, Philadelphia, Pennsylvania. First, the energy demand for the district is reduced through the implementation of cost-effective energy efficiency measures (EEMs) appropriate for Philadelphia’s climate. Then, a combination of distributed generation (DG) systems including wind, photovoltaics, and hydropower is evaluated to determine optimized hybrid systems that meet the energy demand of non-electrified and electrified districts. The analysis indicates that the implementation of common and proven EEMs to all the district buildings can reduce its annual energy consumption and CO2 emissions by 13% and 13.8%, respectively. These EEMs are estimated to be cost-effective based on the current electricity price of $0.082/kWh offered by Philadelphia’s utility, Philadelphia Electric Company (PECO). Through cost optimization analysis, a hybrid DG system combining wind and hydropower connected to the grid is found to lower the cost of energy for the non-electrified district to $0.007/kWh, lower than the current PECO rate, with the added benefit to lower carbon emissions by 10%. Moreover, the analysis considered the case of an electrified district which reduces life cycle costs by 3.5%. By implementing electrification and EEMs, the electricity usage decreases by 14% and peak demand by 19.5% as well as CO2 emissions by 18%. Through cost optimization to design a hybrid DG system that can meet energy demands of the electrified district, wind and hydropower connected to the grid is found to achieve a cost of energy of $0.008/kWh and carbon emissions reduction of 34.9%.