Inverter-based Distributed Generation Research Articles

Highly sensitive protection scheme considering the PV operation control models

The integration of distributed generation (DG) based on inverters into power systems has increased significantly, necessitating a thorough understanding of its impact on fault analysis and the performance of distribution networks' protection mechanisms. This study addresses this issue by examining how various inverter management modes influence protective relay systems within IEEE 9-bus redial and mesh networks, CIGRE and IEEE 33-bus networks featuring Photovoltaic (PV) farms and Battery Energy Storage Systems (BESS), by IEEE1547–2018 and German grid code standards. By analyzing grid-connected scenarios with five distinct PV control modes, the research introduces a novel protection methodology termed the Photovoltaic Overcurrent Relay (PVOCR). This method introduces a current-voltage characteristic to optimally coordinate Overcurrent Relays (OCRs), aiming to reduce their operational time and eliminate mis-coordination events. The proposed PVOCR is evaluated against standard inverse time, SOCR, and modern adaptive voltage, VOCR, relay schemes across various fault scenarios differing in type and location. Furthermore, the PVOCR scheme effectively operates across all PV inverter modes without experiencing miscoordination events, whereas the SOCR and VOCR schemes encountered such issues during the operation of Control 4. These results underscore the potential utility of the PVOCR methodology in enhancing the reliability and efficiency of protection systems in inverter-based DG networks.

Multi-stage framework for optimal incorporating of inverter based distributed generator into distribution networks

Recently, hydrogen-based distributed generators (DG) have gained significant attention for modern energy generation systems. These modem DGs are typically outfitted with power electronics converters, resulting in harmonic pollution. Furthermore, increasing the growth of modern nonlinear loads may result in exceeding the harmonic beyond the permitted level. This research proposes a framework for optimal incorporation of inverter-based distributed generation (a fuel cell connected to an AC distribution system) for minimizing power losses, enhancing the voltage profile, and limiting both total and individual harmonic distortion according to the IEEE-519 standard. In addition, for accounting system sustainability, the proposed framework considers load variation and the expected rise in demand. Therefore, the suggested framework comprises three stages, which include fundamental and harmonic power flow analysis. The first stage identifies the optimal size and location of the DG in relation to the base load operating condition. While, with the optimal DG of the first stage, the amount of harmonic pollution may violate the limits during a high level of nonlinear load penetration, as a result, the second stage resizes the DG, considering the connection bus of the first stage, to mitigate the harmonics and optimize the system at a higher level of nonlinear load penetration. Both the first and second stages are performed off-line, while the third stage optimizes the system operation during run time according to loading conditions, harmonic pollution, and the available DG capacity of the previous stages. DG’s harmonic spectrum is represented according to recently issued IEEE 1547-2018 for permissible DG’s current distortion limits. The suggested approach is applied and evaluated using an IEEE 33-bus distribution system for various combinations of linear and nonlinear loads. For run-time operation throughout the day, the presented framework reduces the energy losses from 5.281 to 2.452 MWh/day (about 53.57% energy savings). This saving is associated with voltage profile enhancement without violating the permissible standard levels of harmonics and other system constraints.

An Islanding Detection Method Based on the Reactive Power Disturbance for Multiple Inverter-Based DG Systems

In this paper, an islanding detection method for multiple inverter-based distributed generation systems is proposed, which is based on perturbing reactive power output. An asymmetric form of positive and negative reactive power disturbance is presented so that there always exists a certain total amount of disturbance in the system. To decrease the disturbance amplitude without expanding the non-detection zone, a positive feedback of frequency difference is added to the disturbance. A reactive power disturbance synchronization method without communication among inverters is proposed so that the averaging effect caused by unsynchronized reactive disturbances can be eliminated and the island can be detected in a multiple-DG system. Additionally, the islanding detection criterion is improved by establishing the relationship between the direction of disturbance and the numerical symbol of frequency difference, so there is no misjudgment of islanding detection in a weak grid. Finally, an experimental platform consisting of three 6kW three-phase grid-connected inverters and a 99.9kVA islanding detection test device is established. The experimental and simulation results indicate that the proposed method performs fast and precise islanding detection for the multiple-DG system with small NDZ and little impact on power quality. Additionally, no misjudgment happens in a weak grid.

Oppositional based artificial rabbits optimization applied for optimal allocation of nonlinear DG in distribution networks considering total harmonic distortion limit

This paper proposes a new optimization approach to identify the optimal placement and sizes of distributed generation (DG) units in a radial distribution network (RDN). Inverter-based DG also known as nonlinear DG (NLDG) units inject nonlinear current into the system, which can cause harmonic distortion. This harmonic distortion can limit the penetration of DG in the system by affecting the stability and reliability of the power system. Therefore, it is essential to consider harmonic distortion when identifying the optimal placement and sizes of DG units in RDNs to ensure DG’s safe and effective integration into the power system. The aim of the proposed work is to minimize real power loss, voltage deviation (VD), and total harmonic distortion limit (THD), and improve the voltage stability index (VSI) by integrating the search strategies of opposition-based learning and artificial rabbits optimization (ARO) to achieve better performance. The proposed algorithm, called opposition-based artificial rabbits optimization (OARO), considers different types of DG units like DG TYPE I and DG TYPE III and is suggested for two familiar RDNs: IEEE 33-bus, and 118-bus systems. The Pareto optimality concept has been introduced to solve the multi-objective problems of the systems. The simulation outcomes have been analyzed by comparing several optimization techniques in various cases. OARO has been shown to produce high-quality results with minimal iterations, reducing the time needed to solve the issue and conserving energy. Overall, the proposed approach offers a promising solution for identifying DG units’ optimal placement and sizes in RDNs while considering various operating scenarios.

Comparison of a Novel AFPSO-SFS & PSO-SFS Approaches for Islanding Protection of Inverter-Based DGs

The most significant of the active islanding detection techniques is “Sandia Frequency Shift” (SFS), and this employs frequency drifting to identify extra Nondetection Zone. Inappropriate tuning parameters, such as the acceleration factor and chopping factor, result in frequency drifting, which degrades the quality of the power and causes the continuous power mode to fail. The failure can be overcome by considering optimized parameters to identify the nondetection zone (NDZ) in small DG system (120 kVA) at constant power/current mode. This article discusses, a new Adaptive Fuzzy Particle Swarm Optimization-SFS (AFPSO-SFS) technique is recommended to attain optimal parameters of SFS anti-islanding detection technique for validation of the proposed algorithm Particle Swarm Optimization–SFS (PSO-SFS) is also implemented. Furthermore, the ability of this method is to identify an islanding situation which deteriorates the major scientific issues for small DG system. Thus, the optimized parameter helps to attain an anti-islanding as well as less impact on power quality. Moreover, this article concerns serious issue of the grid interconnected DG model in an islanding condition, when the utility line would be unintentionally isolated. The grid detachment is generally considered as a fault. When an islanding occurs, the DG protection system must be inactive to detect the fault. For the investigation of power mismatches, the output of considered system using the proposed methods is contrast with results obtained from PSO-SFS and conventional SFS. The recommended strategy analyzes islands more effectively and diagnoses nondetection zones more accurately. The recommended method’s reliability is calculated quantitatively and emulated with MATLAB/Simulink.

Sampled-Data Cooperative Output Regulation: An Adaptive Distributed Continuous-Discrete Observer Approach

This paper studies the sampled-data cooperative output regulation problem for linear multi-agent systems. Firstly, a novel adaptive distributed continuous-discrete observer is established to recover the leader's state, which, on one hand, only relies on the sampling output of the leader, and on the other hand, does not need to store the sampled message from neighbors. Secondly, by solely making use of the digital states of both the agent and the distributed observer, a certainty equivalence control law is synthesized featuring a time-varying feedforward gain. It is rigorously proven that, with this time-varying feedforward gain, the proposed control approach can achieve exponential convergence of the tracking errors given arbitrary time-varying leader's signal, and the upper bound for the sampling intervals is explicitly given. Thirdly, for the class of chain-integrator multi-agent systems, the proposed control approach does not need any restriction on the upper bound of the sampling intervals, and thus would be more practical in certain application scenarios from the perspective of energy saving. The performance of the proposed control approach is validated by the simulation results of inverter-based distributed generation systems.

Distributed fast finite-time secondary control of islanded microgrids: A disturbance observer-based approach

For islanded microgrids with inverter-based distributed generators (DGs), this article focuses on the fast finite-time secondary voltage and frequency control problem considering system uncertainties. The distributed controller is designed based on the command filtered backstepping procedure, and a disturbance observer is constructed to estimate the lumped system uncertainties (including parameter perturbations, unmeasurable variables, etc.). In addition, the singularity issue derived from differentiating the virtual control law is avoided by using a smooth switch function. The proposed controller guarantees that the tracking errors of voltage and frequency converge to a small region around the origin in a finite time, while achieving desired active power sharing ratio. Case studies are conducted on a microgrid system to demonstrate the effectiveness of the proposed strategy in the presence of load changes and parameter perturbations.

A Novel Scheme to Protect Distribution Networks in Presence of Inverter-Based Distributed Generation

One of the most important challenges of distributed generation (DG) development in distribution systems is their protection. It is necessary to have a scheme for keeping the protection settings unchanged. In this paper, adverse impacts of the inverter based distributed generation (IBDG) are evaluated, and an algorithm is proposed to limit the fault current, feed, which is generated by IBDGs. This algorithm is only implemented on the inverter controller and other elements are not used in fault current limitation. The simulation results are provided to verify the proposed control scheme.

Adaptive harmonic-based protection coordination for inverter-dominated isolated microgrids considering N-1 contingency

Protection coordination is typically approached considering the main network configuration. Nevertheless, contingencies such as generator or line failures may disrupt power grids. Low fault currents in inverter-based isolated microgrids adversely impact the conventional overcurrent protection schemes. This paper proposes a sensitive and selective protection scheme for isolated microgrids using an adaptive third harmonic voltage generated by inverter-based distributed generators (IBDGs) and adapted to fault severity. The generated harmonic voltage results in a harmonic layer established during faults and is decoupled from the fundamental fault current, which is limited by IBDGs. Harmonic directional overcurrent relays sense the generated harmonic currents and voltages at the relay location to ensure optimal protection coordination (OPC). The OPC problem is formulated as a constrained nonlinear program to determine the optimal relays’ settings. The constraints are defined for the isolated configuration and each potential configuration resulting from an N-1 contingency. A radial microgrid that is part of a Canadian urban distribution network is used to ensure the successful operation of the proposed protection scheme. The results demonstrate the ability of the proposed scheme to protect isolated microgrids and preserve protection coordination without communication.

Optimal inverter-based distributed generation in ULP Way Halim considering harmonic distortion

Integration of distributed generation (DG) based on the use of new renewable energy is considered to be able to increase the capability of the electric power distribution system. However, the use of inverter-based DG is not optimal, it can worsen the condition of the system, especially in terms of the spread of harmonic distortion which can damage the equipment. This is due to the inverter-based DG technology, apart from supplying electrical energy, DG also injects harmonic currents from existing semiconductor components. This research discusses optimization placement of inverter-based DG using the multi objective particle swarm optimization (MOPSO) method which was tested on the Unit Layanan Pelaksana (ULP) Way Halim 88-bus radial distribution system based on MALTAB 2020b to increase the efficiency of the electrical system by reducing losses and %THDv. The inverter-based DG placed on 24 bus points with a capacity of 690 kW can reduce losses by up to 12.74 kW or 14.96% and all %THDv values for each bus are below 5%.

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.

Design and FPGA-in-loop based validation of predictive hierarchical control for islanded AC microgrid

This paper proposes a decentralized control approach for the flexible operation of an autonomous AC microgrid (MG). AC MG typically consists of two or more voltage source inverters (VSI), capable of simultaneously regulating the voltage at the point of common coupling (PCC) and meeting the local power demand. The classical linear control techniques attain these functions. However, they have many limitations, such as slow transient response, high sensitivity to the parameter variations, and inability to handle the system nonlinearities. This paper aims to address these issues by presenting an improved finite control set model predictive control (FCS-MPC) approach for inverter-based distributed generation (DG). The proposed scheme tracks the voltage trajectory using cost function (CF) over two-step prediction horizons. The proposed control method is employed for the AC MG having two parallel DGs. Droop control is responsible for the power-sharing between the parallel DGs regardless of impedance mismatch at the distribution level of AC MG. The decentralized secondary control is developed to eliminate the deviation in the voltage and frequency caused due to overlooking the primary control. The proposed control scheme has been validated through extensive simulations and real-time controller hardware in the loop tests using an FPGA ZYBO Z7 board. Moreover, the proposed methodology depicts the enhanced transient response, less computational burden than the classic MPC, and shows robustness to parametric uncertainties in terms of THD than hierarchical linear control. The simulations and experimental results visually represent research outcomes, exhibiting the THD of 0.98 % for different dynamic loads, which is within the limit of IEEE and IEC standards. Furthermore, the proposed controller’s mathematical stability is further supported by analysis based on the Lyapunov stability theory.

Controllable Transient Power Sharing of Inverter-Based Droop Controlled Microgrid

The transient power shared by inverter-based distributed generators (DGs) restricts the normal operating range and overstresses the power electronic devices under disturbing events. Additionally, the inevitable incorporation of DC side voltage dynamic during transient worsens the uncoupled dynamics between active and reactive power. Furthermore, unsafe transient power supplied by DGs can easily destabilize system operation. Therefore, this paper proposes a control strategy that controls the transient power distributed between several DGs integrated into a microgrid. To comprehensively design the proposed control, (i) an extended steady state and transient modeling of a microgrid that incorporates DC side dynamics in AC side-based model is first carried out. (ii) After that, designing the proposed control is systematically conducted and verified using frequency and time domain analyses. (iii) Moreover, the effectiveness of the proposed control is compared with state-of-the-art control strategies. The results demonstrate that the proposed control prevents power electronics-based DGs from sharing the majority of transient currents when integrated with other DGs, especially, inertial sources. The results show that the power overshoot and oscillation are reduced more than two times whereas the settling time is decreased by about three times, ensuring quick stabilized, and reliable integration of power electronics DGs in microgrids.

Quadratic-Droop-Based Distributed Secondary Control of Microgrid With Detail-Balanced Communication Topology

This article proposes a quadratic-droop-based fixed-time distributed secondary voltage control of an islanded ac microgrid. The microgrid consists of inverter-based distributed generators, connected over a detail-balanced communication topology with bidirectional unequal edge weights. The proposed voltage restoration strategy is derived from the quadratic relation between voltage and reactive power for inductive microgrids against their linear dependence, which has been conventionally used in designing voltage droop controllers. It has been illustrated that the proposed quadratic-droop-based control design strategy shows better performance as compared with the linear counterpart. We provide a rigorous Lyapunov stability analysis for the proposed controller and also obtain an upper bound on the convergence time, independent of the system's initial conditions. In addition, frequency restoration and proportional active power sharing among the generators are realized in the fixed time. Simulations are provided to verify the efficacy of the proposed controllers, including a comparative analysis with conventional droop control and finite-time control through a case study.

Islanding detection and classification of non-islanding disturbance in multi-distributed generation power system using deep neural networks

This paper proposes a statistical feature-based deep neural network (S-DNN) islanding detection technique and classification of non-islanding disturbances for hybrid systems with both synchronous and inverter-based distributed generators. The proposed technique extracts five statistical features from the point of common coupling (PCC)'s three-phase voltage. Several islanding and non-islanding scenarios for the test system were developed in the MATLAB environment. The S-DNN model is employed to effectively detect islanding and classify non-islanding disturbances using extracted features. In the detection phase of this study, the model is designed to identify events that occur in both islanded and non-islanding modes, providing the capability to accurately detect islanding conditions. In the classification phase, the model focuses specifically on non-islanding disturbances, such as line faults, load switching, and capacitor switching disturbances, enabling precise categorization of these distinct types of events. By leveraging the S-DNN model's capabilities, this study aims to enhance both islanding detection and non-islanding disturbance classification. By introducing white Gaussian noise with varying signal-to-noise ratios (30 dB and 40 dB) to the data, we aimed to evaluate the method's ability to handle and mitigate the effects of noisy and uncertain input signals. The inclusion of noise was intended to simulate realistic conditions where measurement inaccuracies or disturbances can be present. The decision tree (DT), multilayer perceptron (MLP), and support vector machine (SVM) are put up against the proposed technique, and it performs better than them in terms of accuracy, precision, recall, and F1 score.

Decentralized Robust Control of a Network of Inverter-Based Distributed Generation Systems

This paper presents the design of decentralized robust controllers for a network of inverter-based distributed generation systems with LC filters in the scale of a nanogrid. Using overlapping decomposition, the network of inverters is clustered into several subnetworks such that all inverters within a subnetwork are strongly coupled and there is no or a weak coupling effect between any two inverters from different subnetworks. For the inverters within the same subnetwork, decentralized robust controllers are designed sequentially in the μ-synthesis framework. In addition, all controllers are designed to be robust against ±10% variations in the LC filter parameters. To assess the performance of the proposed sequentially-designed controllers and compare it to that of the benchmark independently-designed ones, the distances between two neighboring inverters from the same and different subnetworks are considered to be 200 (m) and 800 (m), respectively. In this case, time-response and robustness analysis results illustrate the superiority of the proposed sequentially-designed controllers in the overlapping decomposition framework over the benchmark independently-designed ones. Moreover, transient overload and nonlinear load analyses demonstrate that the proposed sequentially-designed decentralized controllers are able to keep the load voltage within ±10% of the nominal value and the harmonic voltage distortions to less than 4%.

Roadmap to modernization of line protection in active distribution systems

The nature of distribution systems is changing from passive to active networks due to the integration of Distributed Energy Resources, especially Inverter-Based Distributed Generation (IBDG). This change presents challenges for existing fuse-based unidirectional protection schemes, as active networks experience bidirectional flow of power and small fault current contribution from IBDGs. Such fault behavior can impact the protection scheme’s sensitivity and selectivity, compromising the reliability of active distribution networks and leading to customer outages due to improper fault isolation. The problem is exacerbated in networks that allow the islanded mode of operation. Upgrading the entire protection system to microprocessor-based relays is expensive. Instead, this work proposes a planning strategy to optimally upgrade protective devices. The proposed framework is able to incorporate IBDG integration plans, distribution system reliability targets, protection requirements, and economic viability throughout the planning horizon. The obtained strategy determines the optimal number, location, and deployment time of protective devices in consideration of network characteristics. The developed optimization model is formulated as a Mixed-Integer Linear Programming problem. The results verify the proposed framework’s ability to economically upgrade the protection scheme while enhancing the reliability of the active distribution network with IBDGs.

Demand-Side Management of Self-Sustained Droop Based Standalone Microgrid Using Conservation Voltage Reduction Strategy

Self-sustained microgrid (MG) carries the potential to replicate a conventional grid network with a smooth and robust control scheme to generate and disseminate power with the integration of diverse renewable sources by employing the voltage source inverter (VSI). The power generation capability is the primary function of VSI in an inverter-based distributed generation (DG). In addition, it is also operated to perform the task of demand-side management with the utilization of the conservation voltage reduction (CVR) strategy. In a conventional distribution network, the CVR strategy is exploited by voltage deduction within permissible range with the support of open-loop schemes, such as tap changers, capacitors, or close-loop schemes, such as supervisory control and data acquisition system. However, the CVR's applicability in a standalone MG is still a viable approach to be delved into and hence, this article intends to employ CVR by utilizing the conventional P-f droop and V-I droop principle in inverter-based DG. The proposed strategy produces voltage compensation according to the degree of voltage or frequency variation and therefore, the degree of voltage reduction is not fixed but it varies with the disturbance. The proposed control mechanism relies on the deviation of the voltage generated by the V-I droop and frequency output provided by the P-f droop during the overloading and peak demand condition. In addition to it, a control methodology is devised to check the coordination between CVR and load shedding strategy to shed load during overloading conditions. The performance testing of the proposed control methodology is being validated through real-time Opal-RT device.

Twin Delayed Deep Deterministic Policy Gradient (TD3) Based Virtual Inertia Control for Inverter-Interfacing DGs in Microgrids

Environmental and energy security concerns lead to the continuous displacement of traditional fossil fuel-based power generation to power electronics interfaced distributed generations (DGs). Increasing penetration of renewable energy sources and the substitution of synchronous generators with power electronic converters have resulted in reduced power system inertia and damping. This causes large frequency deviations and a higher rate of change of frequency. The fast and flexible nature of the energy storage system with a designed controller can achieve frequency stability in low inertia microgrids (MGs). The conventional proportional-integral-based virtual inertia controller is unable to eliminate frequency instability in low inertia MG. To enhance frequency stability, this article proposes a virtual inertia emulation strategy using a twin delayed deep deterministic policy gradient (TD3) algorithm for fast frequency regulation of MGs with inverter-based DGs. A comparative analysis of the TD3 scheme and the conventional method is made. The results show that the TD3-based virtual inertia control provides better tracking with a 56.6% reduction in frequency deviation and faster transient recovery than the conventional virtual inertia control against a broad range of operational scenarios. Performance metrics and simulation results are shown to demonstrate the feasibility of the proposed control scheme.

Injection Harmonic Current Differential Protection Based on Control-Protection Synergy for Distribution Networks with IBDGs

The high penetration of inverter-based distributed generations (IBDGs) leads to traditional distribution networks’ complex and variable fault characteristics. Traditional passive detection protection methods can hardly meet the stability and reliability requirements. To solve this problem, an injection harmonic current differential protection (IHCDP) scheme based on the idea of control-protection synergy is proposed in this paper. By analyzing the circuit structure, control strategy, low-voltage-ride-through characteristics of IBDGs, and short-circuit currents provided by IBDGs, an injection-control strategy of characteristic harmonic currents (CHCs) based on the d-axis and q-axis is proposed. According to the change of short-circuit currents provided by the IBDG, the amplitude of CHCs is adaptively corrected to strengthen the fault characteristics and ensure that the distribution network harmonic injection protocols are always satisfied. An IHCDP criterion based on the distortion rate of the negative-sequence component of CHCs is proposed by analyzing the fault characteristics of the CHCs after injection. To effectively eliminate the dead-zone problem during symmetrical short-circuit faults, the proposed IHCDP utilizes the distortion rate of A-phase CHCs. The feasibility of the proposed protection scheme is demonstrated by the theoretical analysis and simulation results in this paper.