Deploying grid ancillary services through distributed energy resources (DERs) challenges islanding detection techniques (IDTs). Power regulations, for instance, may mitigate power mismatches in islanded microgrids, increasing the risk of undetected islands. Additionally, when the grid is connected, false islanding detection during low-voltage events can disrupt low-voltage ride-through (LVRT) operations. Existing IDTs that comply with these services and requirements often suffer from power quality degradation and limited scalability in multi-inverter systems. To address these gaps, this study proposes an active IDT using the DER's input admittance shaping within a narrow negative-sequence frequency band. The shaped admittance results in a negligible negative-sequence disturbance (NSD) injection during grid-connected operation while ensuring rapid and synchronized NSD jump after island formation in multi-inverter systems. Thus, islanding is detected when the rate of change of negative-sequence voltage at the DER terminal exceeds a preset threshold within a specified timeframe. Importantly, the proposed IDT does not affect the positive sequence component, avoiding conflict with ancillary services in grid-connected operations. Numerous simulations are conducted in PSCAD-EMTDC in accordance with the IEEE Std. 1547.1-2020 test procedure. The results demonstrate precise and rapid islanding detection in single- and multi-inverter scenarios, including zero/small power mismatches with DER's power regulations. In addition, the proposed IDT does not exhibit false tripping during low-voltage events, complying with LVRT requirements.

The sudden outage of a transformer due to a fault can cause irreparable damage to the electricity industry. Hence, by conducting momentarily inspections of the transformer's condition, faults can be promptly detected, and the transformer can be disconnected from the power grid to prevent subsequent failures in this equipment. Detecting faults at an early stage can also result in reduced repair costs. One recent promising technique for fault detection is Frequency Response Analysis (FRA), which compares the transformer's response in healthy and faulty conditions for understanding the occurrence of transformer faults. This paper presents a comprehensive and accurate modeling approach for the behavior of the transformer at different frequencies, followed by an exposition of the requirements for implementing this method in order to find the fault type, severity, and location. Additionally, various methods for analyzing the results of frequency response are introduced and discussed. In this regard, attempts have been made to introduce advanced complementary methods to address the weaknesses and limitations of the frequency response method. Finally, the concepts are summarized, and suggestions for further research with applications in this field are presented and compared.

The connection of renewable energy sources (RESs) to the distribution network has been rising at a steady pace over the past decades. The great penetration of RESs such as grid-connected photovoltaic system brings new technical challenges to the distribution networks such as unintentional islanding. Conceptually, this situation occurs when a portion of the network that has been isolated from the main grid remains energised by the embedded RESs. This unexpected scenario should be thereby identified effectively to avoid frequency and voltage deviations and their hazardous effects. The aim of this paper is to provide a comprehensive review on the recently developed islanding detection methods for grid-following/grid-connected photovoltaic system, analyse their existing limitations, and suggest possible future research implementations. In this context, an in-depth comparison is provided considering the main features used in islanding detection methods such as non-detection zone, detection time, implementation cost and complexity, and power quality degradation. Finally, the main technical requirements established by the current grid codes are recalled identifying potential multi-functional approaches to expand the current islanding detection capabilities.

This study proposes a fast and precise voltage feedback-based islanding detection method (IDM) for grid-connected photovoltaic systems (GCPVSs) based microgrid. In this algorithm, a disturbance containing the absolute deviation of the output voltage is injected into the inverter's d-axis reference current which tunes the active power output. In islanded mode, the applied disturbance reduces the active power output and consequently point of common coupling voltage beyond the standard setting while its effect at the presence of the grid is negligible. The assessment of the proposed IDM has been conducted in the MATLAB/Simulink platform under extensive scenarios defined by IEEE 1547-2008 and UL 1741 standards for a case study system with two large-scale GCPVSs. The provided outputs remark accurate islanding classification in all cases within 810ms, much lower than the maximum permissible time postulated in islanding standards. This time is short enough to restore GCPVS for autonomous operation of microgrid as well. The comparative analysis of the proposed strategy with a few existing IDMs confirmed its overall superiorities in the terms of non-detection zone, detection time, being applicable into the microgrid, simple threshold determination, and straightforward and cost-effective implementation.

This paper investigates the economic viability of a commercial grid-connected photovoltaic system (GCPVS) in the Middle East region. In this regard, an economic assessment of a 120 kW_p GCPVS connected in December 2017 under a feed-in tariff (FiT) scheme in Iran—the leading country in the region establishing a supportive policy—is carried out. In this plan, private enterprises can install GCPVS and sell whole generated energy at a high guaranteed price for twenty years. Several economic indices, including net present value (NPV), internal rate of return (IRR), benefit-cost ratio (BCR), payback period time (PBT), and levelized cost of energy (LCOE) are determined to unveil the effectiveness of the enacted program. This paper exploits one-year recorded energy data of this commercial system to boost the reliability of the results. Moreover, PV module degradation factor is taken into account to make the analysis as realistic as possible. The computed outputs imply that this commercial system, with 3.36 BCR, 31.88% IRR, 5.24 years PBT, and 0.0477 $/kWh LCOE, is highly appealing. The sensitivity analysis also highlight that the profitability of the GCPVS investment is secure under a wide range of unpredictable parameters. It is shown for instance that the PBT and IRR are deteriorated by 5.48% and 1.50 years, while the generated energy lowers by 20% compared with the predicted value for the upcoming years. Having said that, it is still far away from the infeasible condition. A comparative analysis between the current findings and similar researches endorse the Middle East region as the highest potential site for PV installation. It is finally deduced that a properly modified FiT scheme can be set in the region's countries concerning the local meteorological and economic conditions to stimulate the investment of this technology.

This article proposes a fast and reliable two-level islanding detection method (IDM) for grid-connected photovoltaic system (GCPVS)-based microgrid. In the first level of the proposed IDM, the magnitude of the rate of change of output voltage (ROCOV) is computed. If this variable exceeds a predefined threshold, a disturbance is injected into the duty cycle of DC/DC converter after a given time delay to deviate the system operating point away of its maximum power point (MPP) condition. This leads to a substantial active power output and voltage reduction in an islanded mode. Therefore, the ROCOV and the rate of change of active power output (ROCOP) indices, measured in the second stage, pose great negative sets at the same time in islanding states. However, the variation of at least one of these variables is near-zero in non-islanding switching events. The assessment of the presented algorithm has been conducted under extensive islanding and non-islanding scenarios for a case study system with two PV power plants using hardware-in-the-loop (HiL) simulation tests. The provided results remark precise islanding classification with an eminently small non-detection zone (NDZ) within 510 ms. The presented IDM has the advantages of self-standing thresholds determination, no improper effect on the output power quality, and simple and inexpensive structure. Moreover, the fast MPP restoration of the proposed scheme after islanding identification boosts the chance of seamless reconnection and DG autonomous operation in microgrid.

This paper proposes a novel islanding detection method (IDM) for grid-connected photovoltaic systems (GCPVSs) through a disturbance injection in the maximum power point tracking (MPPT) algorithm. When an absolute deviation of the output voltage exceeds a threshold, the applied disturbance shifts system operating point from its maximum power point (MPP) condition. This leads to a sharp active power output reduction and consequently, a significant voltage drop in islanded mode beyond the standard voltage limit. The proposed algorithm is defined in a way that the distributed generator (DG) can be restored to MPP after islanding classification. It is thereby effective in microgrid in where the power injection at maximum level to cater the critical loads and maintain the stability of the isolated area are pursued. An intentional time delay has also been considered to avoid nuisance tripping in short-circuit faults which do not require tripping. The assessment of the proposed technique has been conducted for a sample network containing two GCPVSs in a real-time platform including actual relays in hardware-in-the-loop (HiL). The provided results under extensive islanding scenarios defined in islanding standards endorse timely and accurately detection with negligible non-detection zone (NDZ) as well as no false tripping in non-islanding disturbances. The comparative analysis of the presented scheme with a few recent IDMs for GCPVS highlights its overall superiorities, including very small NDZ, fast detection, thresholds self-standing determination, no adverse effect on power quality, and simple and inexpensive integration.