Showing papers on "Islanding published in 2020"

Seamless Transition of Microgrids Operation From Grid-Connected to Islanded Mode

Abstract: One of the main features of Microgrids is the ability to operate in both grid-connected mode and islanding mode. In each mode of operation, distributed energy resources (DERs) can be operated under grid-forming or grid-following control strategies. In grid-connected mode, DERs usually work under grid-following control strategy, while at least one of the DERs must operate in grid-forming strategy in islanding mode. A microgrid may experience remarkable fluctuations in voltage and current due to an unintentional islanding event. To achieve a smooth transition to islanding mode and mitigate disturbance effect, this paper proposes a control strategy includes a) a linear voltage controller with capacitor current feedback as an input to the voltage controller and output current feedforward as an input to current controller, and b) modified droop control to emulate the inertia response of a synchronous generator. The proposed controller can suppress voltage, current and frequency fluctuations and also guarantee a smooth transition. A small signal analysis of the proposed control strategy is developed to design its coefficients as well as the destabilizing effect of constant power load (CPL). Experimental results are provided to verify the effectiveness of the proposed control strategy.

Support Vector Machine-Based Islanding and Grid Fault Detection in Active Distribution Networks

Abstract: Many techniques used and still in usage for solving the problem of islanding detection are intrinsically passive, active, or hybrid of both. Each one of them has its own benefits and drawbacks. In this paper, we propose a method, which takes the advantage of a machine learning (ML)-based algorithm, namely, support vector machine (SVM), in order to produce the results more efficiently. The results of the simulations based on the model and experimentally measured parameters of a real-life practical photovoltaic (PV) plant give much better output than the traditional reported methods. During the tests and simulations, an additional problem, namely, grid fault, emerged, posing new challenges for the proposed method. Occurrences of islanding and grid fault are grouped together with the same kernel dimension and no custom hyperplane bordering. Discrimination between islanding and grid fault events is an essential dilemma, which is handled by the proposed SVM-based algorithm to achieve more precision in islanding detection and simultaneously detect the grid faults authentically. Nondetection zones (NDZs) and detection time (DT) are tested using two dimensions, namely, the generated active energy from PV plant (0%–110% of $P_{n}$ ) and distribution network voltage levels (±10% of $U_{n}$ ). Simulations based on the model and parameters of a real-life practical PV power plant are performed in MATLAB/Simulink environment, and several tests are executed for several scenarios. Finally, comparisons with previously reported techniques prove the effectiveness, authenticity, selectivity, accuracy, and precision of the proposed islanding and grid fault detection strategy with allowable impact on power quality according to UL1741 and its superiority over other methods.

Power Quality Assessment and Event Detection in Distribution Network With Wind Energy Penetration Using Stockwell Transform and Fuzzy Clustering

Abstract: Power quality (PQ) is a vital issue in the present power systems integrated with large renewable energy sources since more power electronics devices are incorporated in the system. This article proposes a novel method for assessing PQ associated with wind energy integration. This method is effective to recognize PQ issues in power systems with high penetration of wind energy with a low computational burden. Furthermore, it detects different operational issues in the distribution network. Stockwell transform (S-transform) is utilized to decompose the voltage signal and calculate the S-matrix. To assess the PQ, a plot is developed from this matrix. The features of this matrix such as mean, standard deviation, and maximum deviation are further utilized for detecting the operational issues such as wind speed variation, islanding, synchronization, and outage of the wind generation by using clustering with fuzzy C-means. A modified IEEE 13-bus test system is utilized to validate the proposed method, which is also supported by hardware and real-time digital simulator results. The quality of power is graded with the help of a proposed PQ index under various operational events with different levels of wind energy penetration. The proposed method is effective for the identification and grading of different operational events in terms of PQ and recognizing a wide range of PQ issues with a high share of wind energy. The performance of the proposed scheme is established by comparing its results with other approaches.

Anti-Islanding Protection of PV-Based Microgrids Consisting of PHEVs Using SVMs

Abstract: The cheap and reliable primal energy source for battery energy storage system (BESS) refueling necessitates a special attention for combining renewable energy resources with plug-in hybrid electric vehicle (PHEV) charging stations in microgrids. Rapid charging is an operation mode of PHEV for drivers which demands fast recharging of BESSs of the electric cars. This charging mode manifests as low impedance short circuit at dc side, making power transient on power grid side. This paper presents a new anti-islanding protection scheme for low-voltage-sourced converter-based microgrids by exploiting support vector machines (SVMs). The proposed anti-islanding protection method exploits powerful classification capability of SVMs. The sensor monitors seven inputs measured at the point of common coupling (PCC), namely, root-mean-square (RMS) value of voltage and current ( $RMS_{V}$ , $RMS_{I}$ ), total harmonic distortion (THD) of voltage and current ( $THD_{V}$ , $THD_{I}$ ), frequency ( $f$ ), and also active and reactive powers ( $P$ , $Q$ ). This approach is based on passive monitoring and therefore, it does not affect the power quality (PQ). In order to cover as many situations as possible, minimize false tripping and remain selective, training, and detection procedures are simply introduced. Based on the presented sampling method and input model, the proposed method is tested under different conditions such as PHEV rapid charging, additional load change and multiple distributed generations at the same PCC. Simulations based on the model and parameters of a real-life practical photovoltaic power plant are performed in MATLAB/Simulink environment, and several tests are executed based on different scenarios and compared with previously reported techniques, this analysis proved the effectiveness, authenticity, selectivity, accuracy, and precision of the proposed method with allowable impact on PQ according to UL1741 standard, and its superiority over other methods.

Robust System Separation Strategy Considering Online Wide-Area Coherency Identification and Uncertainties of Renewable Energy Sources

Abstract: With the fast growth of renewable energy sources (RES), more and more uncertainties are involved and influencing the stable operation of power systems. Controlled islanding is the last measure to prevent power system blackouts, thus this paper aims to propose a novel model of system separation based on Online Coherency Identification and Adjustable Robust Optimization Programming (OCI-AROP) for minimizing load shedding considering the uncertainties of RES. First, Fuzzy C-Means (FCM) clustering method with F -statistics is utilized to identify the coherent generator groups with the frequency data measured by Phasor Measurement Units (PMUs). Then, the OCI-AROP model considering coherent group constraints, connectivity constraints and robustness constraints about RES are presented. Finally, the case studies on IEEE-39 bus system and WECC-179 bus system are employed to demonstrate the effectiveness of the proposed OCI-AROP model, and comparisons among the OCI-AROP model and the other models are also given to show its superiority.

Optimal Consensus-Based Distributed Control Strategy for Coordinated Operation of Networked Microgrids

Abstract: A two-layer optimal consensus-based distributed control strategy is proposed for the coordinated operation of networked microgrids (MGs). Several networked MG operation objectives are optimized using the proposed control strategy, including frequency/voltage regulation, proportional active power sharing, and smooth MG islanding/reconnection operation. The global objective function of networked MGs is decomposed into a series of local objectives assigned to participating distributed energy resources (DERs). In the decomposed optimization, each control layer is realized in a distributed manner in which DER state variables reach consensus along with optimizing their assigned local objective functions. Each control layer in the two-layer control strategy is formulated as an optimal consensus problem in which the optimality and asymptotical stability of the system equilibrium point for each control layer are demonstrated. The effectiveness of the proposed control strategy is validated in a modified IEEE 33-bus distribution system using the PSCAD/EMTDC platform.

Optimal Chance-Constrained Scheduling of Reconfigurable Microgrids Considering Islanding Operation Constraints

Abstract: Microgrid concept is one of the suitable strategies for increasing resilience and preventing load curtailment, especially in emergency conditions. Operation in islanded mode is one of the unique features of microgrids that can provide numerous benefits for both consumers and energy producers. Unlike the conventional distribution networks, reconfigurable microgrids enable the reconfiguration process to achieve optimal structure. In this article, a new optimal strategy for scheduling of reconfigurable microgrids considering islanding capability constraints is presented. To demonstrate the successful islanding operation, the islanding capability is considered as a probability of islanding operation (PIO) index which shows the probability, that the microgrid has adequate level of spinning reserve to meet the local load. Taking into account the forecast errors of generated power by renewable energy resources (PV and wind) as well as load demand, the 13-interval approximation is used for the simplification of nonlinearity of PIO. The scheduling of reconfigurable microgrid with islanding operation constraints is formulated as a chance-constrained goal optimization problem, where the objective is defined as minimizing the total operation cost of microgrid in terms of fuel cost, reliability cost, cost of purchasing power from the mains, and switching cost. The proposed method is implemented on a 10-bus radial reconfigurable microgrid test system with photovoltaic (PV) panels, wind turbines, battery, and microturbines, with different levels of PIO. The numerical results show the effectiveness of the proposed scheduling method.

Optimal Design and Model Predictive Control of Standalone HRES: A Real Case Study for Residential Demand Side Management

Abstract: Conventional electricity generation is one of the greatest sources of CO2 emissions. For a successful transformation of conventional energy systems into non-polluting and renewable energy systems, technology-focused traditional systems and economics must be combined for a more accurate holistic viewpoint with consideration of socio-political, technical, economic and environmental factors. Hybrid energy systems are considered the most feasible solution to the stochastic nature of renewable energy resources (RERs). Different renewable sources such as wind, solar, and hydrogen fuel cells can be integrated to form hybrid systems. An energy management strategy (EMS) is a strategy for power flow coordination among different components, by considering power demand and other constraints. The choice for an accurate EMS is the key element of a hybrid system as it is instrumental in providing an optimum solution of the hybrid system design and operation management. The objective of the optimization is to find suitable configurations for cost-effective solutions. Optimization and EMS must be treated as one entity to completely understand the system design. This study focuses on a techno-economic analysis with an optimized sizing of a hybrid renewable energy system (HRES) components to meet the residential load demand of a specific area in Pakistan. Nine different scenarios based on the PV-wind-diesel-BSS-converter system are investigated in terms of total net present cost (TNPC), Levelized cost of energy (LCOE), and greenhouse gas (GHG) emissions to find the optimal system design. HOMER Pro software is used to develop the HRES model and for simulation analysis, with optimal sizing of each component for an economical solution. Simulation studies established that PV-wind-BSS-converter is the best suitable choice for the given location, and the optimal component sizes were determined. The TNPC of this system is $47,398 and the LCOE is $ 0.309/kWh. This represents an 81.7 % decrease in overall cost, compared to the base case (diesel only) and a 100% reduction in harmful gases while satisfying 100 % of the energy requirement with a 63.9 % of the surplus. MATLAB/Simulink model is developed for the optimum HRES system design. Its validity is tested by maintaining bus voltages (dc and ac), the secure operation range of storage SOC and real power balance among different components of the hybrid renewable energy system (HRES), and an effective ac voltage, irrespective of external perturbations. Model predictive control (MPC) is regarded as a high-performing algorithm. Since power converters are largely applied in microgrids (MGs), the problem formulation with MPC for a reconfigurable bidirectional voltage source converter (VSC) is applied in this work for hybrid MG. The inevitable fluctuations due to the linear and non-linear loads and the nature of renewable sources are addressed. The regulation of ac voltage is implemented through a finite control set model predictive control (FCS-MPC) based active front end (AFE) rectifier, while direct power MPC (DPMPC) is used to control the power during grid-connected operation. The regulation of an ac load voltage is done through voltage based MPC (MPVC) in the islanding operation of the MG. Moreover, the HRES transition from grid-tied to grid-isolated mode is comprehensively analyzed. MATLAB/Simulink ® software certified the robustness and evaluated the performance of the proposed HRES model under different varying loads viz. balanced, unbalanced, and nonlinear. The proposed strategy offers superior performance with low total harmonic distortion (THD), compared to previously developed strategies. The output waveform of voltage and current have THD of 0.28 % compared to 3.71 % with the conventional strategy. The contributions of this paper lie in the sequential use of HOMER as well as MATLAB tools and in the validation of the suggested HRES plan for the considered location; along with the implementation of FCS-MPC for a reconfigurable bidirectional VSC.

A Novel Distributed Cloud-Fog Based Framework for Energy Management of Networked Microgrids

Abstract: Power grid resilience, reliability, and sustainability can be improved by decomposing the large-scale grids into the Networked Microgrids (NMGs). However, different MGs may have different roles and policies. Hence, in comparison with conventional networks, optimal energy management, as well as the grid reconfiguration of the NMGs is more completed and challenging. This article develops a three-layer cloud-fog computing architecture for energy management of reconfigurable NMGs considering dynamic thermal line rating (DLR) constraint. DLR can potentially affect the ampacity of feeders, especially in the islanding mode, when lines approach their maximum capacity. In order to avoid any feeder contingency in the off-grid (islanded) mode, the reconfiguration technique as well as the cloud fogs framework are employed to change the topology of the NMG network swiftly and release the line capacity. Finally, the proposed problem is formulated as a mixed-integer linear optimization problem considering DLR constraint. The proposed model is examined on a modified IEEE 69 bus test network. Results demonstrate the high performance and effectiveness of the developed model and also validate its reliability and economic assets.

A Risk-Averse Conic Model for Networked Microgrids Planning With Reconfiguration and Reorganizations

Abstract: The advanced switching techniques enable the topology reconfiguration of microgrids (MGs) in active distribution network. In this paper, we enhance and generalize the traditional reconfiguration strategy resorting to the concept of “dynamic MGs” (i.e., the reorganization of MGs boundaries), to achieve a higher operational feasibility against the emergency islandings. Also, a risk-averse two-stage mixed integer conic program model is presented to support the networked MGs planning with generalized reconfiguration decisions. The MGs capacity expansion and seasonal reconfiguration decisions are made in the first stage, and validated under stochastic islanding scenarios in the second stage, where the network operations are captured by a second-order conic program (SOCP). Furthermore, a conditional value-at-risk (CVaR) measure is involved to quantitatively control the islanding risks. By theoretically proving the strong duality of the SOCP subproblem, we develop and customize Benders decomposition method with the guaranteed finite convergence to the optimal value. Finally, numerical results on 33- and 56-bus networked MGs validate the effectiveness of proposed reconfiguration strategy as well as planning approach. Our method demonstrates a cost-saving up to 22.56% when comparing to the traditional scheme with fixed MGs boundaries.

Microgrid Protection and Control Schemes for Seamless Transition to Island and Grid Synchronization

Abstract: Microgrid transitions to islanded mode and grid synchronization can be designed either as seamless transitions or as a black-start. Secure and reliable seamless transition represents one of the most challenging engineering tasks during the microgrid design phase. Existing literature has several shortcomings - proposed microgrids are either ungrounded or not effectively grounded; DER transformer configurations are not properly implemented; communications within the microgrid do not reflect realistic time delays and there is very little discussion of the impact of relay protection settings on the proposed microgrid protection. This paper presents a new microgrid protection and control scheme that enables seamless islanding and grid synchronization using the point of common coupling (PCC) breaker relays, battery energy storage system (BESS) inverter controller and remote input/output mirror bits based communications approach (85RIO). All schemes have been implemented in the field within the electric utility’s microgrid installed on the 12.47kV distribution feeder. The results presented in this paper are based on approximately 9,000 islanding and grid synchronization transitions.

Two-Stage Robust Optimization for Resilient Operation of Microgrids Considering Hierarchical Frequency Control Structure

Abstract: Following a major outage in the main grid due to natural disasters, microgrids (MGs) have the ability to disconnect from the main grid and provide electricity to their consumers. However, integration of power electronic-based generation units and small-scale energy resources into MGs reduces the system inertia. Therefore, frequency deviations arising from the loss of grid power or fluctuations of renewable energy resources and loads should be managed. In this article, a two-stage robust day-ahead optimization model for resilient operation of MGs is proposed in which the hierarchical frequency control structure of the MG is precisely formulated. Based on this model, the operation cost of MG is minimized while sufficient primary and secondary reserves are scheduled to restrict frequency deviations and avoid load shedding under the worst-case realization of islanding events. A column-and-constraint generation algorithm is utilized to efficiently solve the problem. Numerical cases on a test system show the effectiveness of the proposed model and the solution algorithm. The obtained results verify that by applying the proposed model, the operating cost of MG is minimized while the frequency deviation and load shedding can be successfully managed during islanding events.

Enhancing Distribution System Resilience With Proactive Islanding and RCS-Based Fast Fault Isolation and Service Restoration

Abstract: The resilience of power systems against extreme events has become a growing concern in recent years. In view of the fact that the resilience of a distribution system depends on its system function throughout the entire multi-stage recovery process after extreme events, and to comprehensively improve the abilities of distribution systems in resisting and rapidly recovering from extreme events, it is necessary to consider this multi-stage recovery process. In this paper, a novel resilience enhancement method is proposed, where proactive islanding and RCS (remote-controlled switch)-based fast fault isolation and service restoration are comprehensively considered to improve the abilities of distribution systems in resisting and rapidly recovering from extreme events. The multi-stage recovery process is modeled in detail, including the topological and operational constraints of each stage in the multi-stage recovery process, as well as the coupling relationship among the stages. The model is formulated as a mixed-integer linear programming problem and applies to scenarios where the network topology varies. Resilience metrics based on the proposed method are introduced to evaluate the resilience level. Case studies on the IEEE 33-bus system and the real-world 94-bus system show that the proposed method is effective at resilience enhancement.

Dynamic Phasor Modeling and Stability Analysis of SRF-PLL-Based Grid-Tie Inverter Under Islanded Conditions

Abstract: Synchronous reference frame (SRF) phase locked loop (PLL) is a widely employed scheme for grid-synchronization of a three-phase grid-tied inverter (GTI). The SRF-PLL model considered for analysis in literature typically assumes the grid to be always present at the point of common coupling (PCC) in the form of a sinusoidal voltage source. The behavior of the SRF-PLL-based GTI system along with the local loads in case of a grid outage is typically not considered for the analysis. However, this is critical for the study of an unintentional island that is subsequently formed after grid-disconnection. This is required for ceasing system operation for safety reasons. In this work, a dynamic-phasor (DP)-based complex domain model of the GTI system is proposed for studying the behavior of an unintentionally islanded GTI, which leads to analytical solutions of the system. Using the proposed DP model, it is shown that the PCC voltage behavior is governed predominantly by the dynamics of two subsystems, namely, the local load characteristics and the SRF-PLL. The equilibrium solutions of the model are shown to yield the steady-state operating frequency of the islanded system with good accuracy, for various GTI power-factor and load quality-factors. Small-signal analysis is performed to linearize the DP equations. This yields insights into the stability of the multiple possible frequency solutions of the islanded system, which is analytically established using eigenvalue analysis. Simulation and islanding experimental results conducted on a 4.5 kVA three-phase GTI system are presented that validate the proposed DP model of the GTI, accuracy of the analytical frequency, and stability analysis of the islanded system.

A Full Decentralized Multi-Agent Service Restoration for Distribution Network With DGs

Abstract: The ever-growing requirement for reliability and quality of power supply suggests to enable self-healing features of smart distribution network using intelligent communication and control. In this article, a concept of fully decentralized multi-agent system (FDMAS) automation is proposed to build a unified restoration service framework for distribution network with distribution generators (DGs), where an FDMAS interaction mechanism is designed for establishing a reduced model which can significantly reduce the computational dimensions of service restoration. Furthermore, an FDMAS-based strategy is proposed for service restoration by combining network reconfiguration with intentional islanding; especially a network reconfiguration algorithm based on network flow model is presented, which, along with parameter justification, can mitigate the variations of loads and intermittence of DGs. The simulation studies are carried out on the 84-bus and 22-bus distribution system, respectively, using MATLAB and java agent development framework (JADE) simulation system and dynamic model test platform. The test results show that the proposed strategy can maximize restoration of out-of-service loads with minimum switching times and has an excellent performance on service restoration time.

A Novel Two-Stage Multi-Layer Constrained Spectral Clustering Strategy for Intentional Islanding of Power Grids

Abstract: Intentional islanding can be considered as the last action to prevent power grids from severe blackouts. In this strategy, the endangered network is deliberately decomposed into self-sustained islands to improve the power grid resilience, reliability, and security. In this way, this paper develops a novel optimal intentional islanding solution to deal with deliberate physical attacks on the power system. The proposed solution employs a modified multi-layer constrained clustering method based on multi-layer graphs via subspace analysis on Grassmann manifolds clustering. The main objectives are to minimize the active and reactive powers disruptions crossways for decomposed islands, as well as grouping the generators with high-frequency change similarity so that stable operation of each self-supplied grid is ensured. This technique guarantees that each island is only comprised of generators that are synchronized with each other. The proposed multi-layer technique increases the stability of the island by implementing different criteria such as frequency, active power, and reactive power. To better display the improvement, the method is compared with the single layer constrained clustering that can only handle one criterion at a time. The proposed intentional islanding technique is applied to IEEE-9 bus, IEEE-39 bus, and IEEE-118 bus as small, medium, and large-scale networks, respectively.

Grid-Connected PV Generation System—Components and Challenges: A Review

Abstract: Renewable energy (RE) has become a focal point of interest as an alternative source of energy to the traditional fossil fuel and other energy sources due to the fact that it is more environmentally friendly, abundant and economically feasible. Many countries aggressively promote feed-in tariff schemes and solar photovoltaic (PV) systems have become one of the fastest growing RE sources that can be integrated into the grid distribution network. This paper reviews the recent development of grid-connected PV (GPV) generation systems comprising of several sub-components such as PV modules, DC-DC converter, maximum power point tracking (MPPT) technique, and an inverter. In addition, various grid synchronization and islanding detection methods are elaborated. The future key challenges to build a smart and efficient GPV generation system were also presented.

Intelligent Control of Microgrid With Virtual Inertia Using Recurrent Probabilistic Wavelet Fuzzy Neural Network

Abstract: A microgrid with virtual inertia using master–slave control is proposed in this article to overcome the drawbacks of traditional inverter-based distributed generators for lack of inertia and without grid-forming capability. The microgrid using master–slave control is composed of a storage system, a photovoltaic (PV) system and a varying resistive three-phase load. The storage system and PV system are regarded as the master unit and the slave unit, respectively, in the microgrid. Moreover, in order to improve the reactive power control in grid-connected mode and the transient response of microgrid during the switching between the grid-connected mode and islanding mode, an online trained recurrent probabilistic wavelet fuzzy neural network (RPWFNN) is proposed to replace the conventional proportional-integral (PI) controller in the storage system. Furthermore, when the microgrid is operated in islanding mode, the load variation will have serious influence on the voltage control of the microgrid. Thus, the RPWFNN control is also proposed to improve the transient and steady-state responses of voltage control in the microgrid. Finally, according to some experimental results, excellent control performance of the microgrid with virtual inertia using the proposed intelligent controller can be achieved.

A Planning Framework for Optimal Partitioning of Distribution Networks Into Microgrids

Abstract: This paper proposes a novel methodology for the optimal design of microgrids in distribution systems with multiple distributed generation units (DGs). Following the IEEE Standard 1547.4-2011, the operation and control of large distribution networks can be enhanced by dividing these networks into multiple virtual microgrids. The proposed planning framework incorporates the necessary conditions for microgrids to operate efficiently in grid-connected operating mode and successfully during islanding. To obtain a robust design, the clustering process considers three objectives: maximizing the self-adequacy of the designed microgrids, maximizing microgrid islanding success probability, and a combination of both targets. For this purpose, the PG&E distribution system with 69 buses is selected as a test case. Backtracking search optimization algorithm, a probabilistic load flow approach, and graph-based theories are used to accomplish this research. Simulation results demonstrate the effectiveness of combining the self-adequacy and the islanding success probability objectives in the clustering process. Compared with other strategies present in the previous literature, the proposed framework results in more self-sufficient and successful islands assessed in terms of active and reactive power adequacy as well as voltage constraints. Next, the effects of increased penetration level of DGs and installation of both distributed energy-storage units and distributed reactive sources on the design process are examined. Finally, a comparison with other microgrid design objectives applied in previous researches reveals that the resultant design is sensitive to the system's reliability, security, and economic requirements.

Design and Real-Time Implementation of a Centralized Microgrid Control System With Rule-Based Dispatch and Seamless Transition Function

Abstract: With reference to the newly released microgrid standards, design and real-time implementation of a centralized microgrid control system is presented in this article. In the grid-connected mode, the utility grid will provide the voltage and frequency reference at the point of connection. The assets within the microgrid will follow power command references provided by the control system. In the islanded mode, the energy storage system (ESS) can provide the voltage and frequency reference to all other generators. Based on the state-of-charge of the ESS, a rule-based dispatch is proposed, with priority given to diesel generator and then the storage in the middle state of charge range. To alleviate power fluctuations, meet smooth planned islanding requirement, and compensate for the feeder losses ignored in dispatch algorithm, a supplementary slack-bus power control based on closed-loop feedback and first-order filter is proposed. The potential of the storage system in firming short-time power fluctuation and providing long-term load shifting capabilities is exploited. An emergency dispatch function for unplanned islanding considering the speed of response limitation of a diesel generator is also proposed. The proposed control strategy is implemented and tested on a controller hardware-in-the-loop test bench. It demonstrates the capability of the control system to reduce load shedding and renewable curtailment, and to implement power management at the point of interconnection.

Harmonic Phasor Estimator for P-Class Phasor Measurement Units

Abstract: Fast harmonic phasor measurements are very useful in power system protection applications, e.g., high-impedance fault location and intelligent method-based islanding detection. To address this problem, a novel harmonic phasor estimator is proposed in this paper, especially for P-class phasor measurement units (PMUs). The exponential functions are used to model the decaying dc (ddc) component, and the optimal time constant (TC) set for the ddc model is searched based on an enumeration method. In addition, the dynamic harmonic phasors are modeled based on the Shannon sampling theorem. As a result, a filter bank is designed for harmonic phasor and frequency estimations. The rate of change of frequency (ROCOF) of the harmonic is estimated based on a second-order fitting method. The response time of the proposed method for harmonic phasor estimation is always no longer than 40 ms. Simulation test results indicate that the proposed method is more accurate than the Taylor–Fourier transform (TFT) under ddc offset and frequency deviation conditions. In particular, the proposed method is more robust to ddc’s TC variations. An experimental test is implemented to demonstrate the advantages of the proposed method.

Advanced Control Strategy with Voltage Sag Classification for Single-Phase Grid-Connected Photovoltaic System

Abstract: This paper develops a fault ride-through (FRT) control strategy for achieving low voltage ride through (LVRT) in single-phase grid-connected photovoltaic (PV) systems (GCPVS). The proposed control system adapts a neural network (NN) classifier for islanding classification and model predictive control (MPC) for achieving the control of the two-stage PV system. This control scheme takes advantage of the nonlinear nature of the power converters and develops a cost function-based approach to achieve fast and efficient control. Besides, the proposed controller provides voltage support to the grid during voltage sags by injecting minimum reactive current within the threshold. The operation of the proposed control strategy is verified by performing simulation tests on a 4 kW GCPVS by creating a sag type of fault in the utility. Further, laboratory experiments were carried out with the developed controller. The results ensure that the proposed control system adheres to the grid requirements by enabling voltage support during grid faults.

Internal Model Based Smooth Transition of a Three-Phase Inverter Between Islanded and Grid-Connected Modes

Abstract: Recent technical advances in control, protection and interconnection of distributed power generation units imply that it is practically viable and economically profitable to keep them as backup generators in isolated operating modes. Therefore, along with the development of islanding detection techniques, seamless operation in transition between islanded and grid connected modes is required and more sophisticated control strategies are needed to recognize the existing working condition and adjust the performance to meet the strict standards of grid interconnection. This paper presents a new adaptive control structure, based on internal model control (IMC), which uses multiple models and an inherent islanding detection method through an optimized switching mechanism to tune the operation of a three-phase inverter under transitions between islanded and grid-tied conditions. By applying a power synchronization method, the system emulates the operation of a synchronous machine which is needless to rely on a phase-locked loop to synchronize during the transitions. Hardware co-simulation environment in Simulink/PLECS and Xilinx System Generator have been utilized to evaluate the transient behavior of the controller in discretized domain and verify its robustness during parameter variations and load switching conditions. Various switching rules have been applied and a comparison of their effect in transient response is demonstrated. The results, taken from several case studies, confirm the significant robustness of the proposed control methodology.

Islanding Detection of Distributed Generation Based on Parallel Inductive Impedance Switching

Abstract: This paper deals with a new islanding detection method based on parallel inductive impedance (PII) switching at distributed generation (DG) connection point, and monitoring the rate of change of voltage $(dv\!/\!dt)$ at DG output. In the proposed approach, switching the PII causes variation in the $dv\!/\!dt$ . This variation is very small in the case that DG operates in parallel with the main grid, whereas the changes will be very large during the occurrence of islanding. Therefore, the $dv\!/\!dt$ is employed to identify both the islanding and nonislanding situations; however, to better analyze the $dv\!/\!dt$ changes, a fast Fourier transform (FFT) is employed to process the variation of the $dv\!/\!dt$ . To select the type of inserted impedance, the effect of switching various impedance types on the $\text{FFT}$ $(dv\!/\!dt)$ is thoroughly analyzed. It is demonstrated that the purely inductive impedance has better performance than other impedance types. The performance of the proposed method is examined through comprehensive simulation studies in MATLAB. The simulation results indicate that the proposed method retains its efficiency for both inverters- and synchronous-based DGs. Moreover, the proposed method not only has a substantial influence on the reduction of disturbances due to the small amount of PII but also eliminates the nondetection zone entirely in comparison with other available methods.