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Cascading outages in power systems can lead to major power disruptions and blackouts in power systems. By taking Manual Corrective Actions (MCAs), operators could be able to mitigate a cascading outage following an initiating event. However, due to stressful and time-constrained situations, they might not be able to take appropriate corrective actions in time and might even take counter-productive actions. Although numerous approaches have been developed to assess the risk of cascading outages in a probabilistic way, they generally do not consider in a realistic manner MCAs, including their imperfection. This paper aims to address that gap by proposing a Human Reliability Analysis-Optimal Power Flow (HRA-OPF) framework. The developed approach is applied to the New England Test System (NETS) and to the Reliability Test System (RTS). The risks of loss of supplied power are compared for different possibilities: no MCAs, perfect MCAs, and imperfect MCAs. • Grid operators can halt cascading outages during the slow phase before fast escalation. • Nonetheless, improper manual corrective action (MCA) due to degraded situational awareness worsen the situation. • Proposed HRA-OPF framework estimates the failure probability of MCAs due to time limits. • Estimated failure probabilities are then employed in risk assessment of cascading outages. • The risk of cascading outages is compared for three cases: Perfect, Imperfect and No MCAs. [ABSTRACT FROM AUTHOR]

Distributed Energy Resources (DERs) integration into distribution systems becomes problematic when the penetration level exceeds the system DER hosting capacity. Although several studies propose to quantify DER hosting capacity, methodologies to maximize it in distribution systems are scarce. Some approaches propose installing var compensators, incurring in costly solutions; others propose reduced cost solutions like network reconfiguration or optimized Volt–Var curve. Nevertheless, the combination of these approaches has not been proposed. Therefore, this paper proposes the simultaneous network reconfiguration and optimized setting of grid-tie inverter Volt–Var curve to maximize DER hosting capacity and minimize power losses. The uncertainties are addressed using Monte Carlo simulation, whereas Non-Dominated Sorting Genetic Algorithm II handles the multi-objective problem. The simulations are performed using Matlab and OpenDSS software, considering the IEEE 33-bus test system. Finally, the results demonstrate the superiority of the proposed approach against previous studies that performed network reconfiguration and Volt–Var optimization separately. • Network reconfiguration and Volt–Var optimization for hosting capacity maximization. • Multi-objective approach to increase DER hosting capacity and minimize power losses. • Inclusion of uncertainties related to DERs and loads in a 24-hour cycle. • Cost-effective solution by avoiding the need for additional var compensator equipment. [ABSTRACT FROM AUTHOR]

We propose a new heuristic approach for solving the challenge of determining optimal placements for geomagnetically induced current blocking devices on electrical grids. Traditionally, these determinations are approached by formulating the problem as mixed-integer nonlinear programming models and solving them using optimization solvers based on the spatial branch-and-bound algorithm. However, computing an optimal solution using the solvers often demands substantial computational time due to their inability to leverage the inherent problem structure. Therefore, in this work we propose a new heuristic approach based on a three-block alternating direction method of multipliers algorithm, and we compare it with an existing stochastic learning algorithm. Both heuristics exploit the structure of the problem of interest. We test these heuristic approaches through extensive numerical experiments conducted on the EPRI-21 and UIUC-150 test systems. The outcomes showcase the superior performance of our methodologies in terms of both solution quality and computational speed when compared with conventional solvers. • New heuristic approaches for placing geomagnetically induced current blocking devices. • The proposed approaches provide high-quality solutions. • The proposed approaches are scalable with respect to the problem instance size. [ABSTRACT FROM AUTHOR]

This paper proposes to extend the fast-decoupled state estimation formulation to bring its well-known efficiency and benefits to the processing of networks with embedded FACTS devices. The proposed method approaches shunt-, series-, and shunt-series-type devices. The controller parameters are included as new active or reactive state variables, while controlled quantity values are included in the metering scheme of the decoupled approach. From the electrical model adopted for each device, the extended formulation is presented, and a modified fast-decoupled method is devised, seeking to ensure accuracy and impart robustness to the iterative solution. Simulation results conducted throughout the IEEE 30-bus test system with distinct types of FACTS devices are used to validate and evaluate the performance of the proposed decoupled approaches. • Fast-Decoupled State estimator with embedded FACTS devices. • Accurate and low computational cost steady-state modelling for networks with FACTS. • Modified algorithm-decoupled for FACTS parameter estimation. • FACTS modelling in fast-decoupled state estimation. [ABSTRACT FROM AUTHOR]

This paper addresses the Optimal Transmission Switching (OTS) problem in electricity networks, which aims to find an optimal power grid topology that minimizes system operation costs while satisfying physical and operational constraints. Existing methods typically convert the OTS problem into a Mixed-Integer Linear Program (MILP) using big-M constants. However, the computational performance of these approaches relies significantly on the tightness of these big-Ms. In this paper, we propose an iterative tightening strategy to strengthen the big-Ms by efficiently solving a series of bounding problems that account for the economics of the OTS objective function through an upper-bound on the generating cost. We also discuss how the performance of the proposed tightening strategy is enhanced if reduced line capacities are considered. Using the 118-bus test system we demonstrate that the proposed methodology outperforms existing approaches, offering tighter bounds and significantly reducing the computational burden of the OTS problem. • Optimal Transmission Switching (OTS) finds the grid topology that minimizes cost. • OTS is formulated as a mixed-integer model and therefore belongs to the NP-hard class. • We propose an iterative tightening strategy to strengthen the big-Ms in the OTS model. • The proposed methodology outperforms existing approaches computationally. • Simulation results of a 118-bus network involve speedups of 8×–22×. [ABSTRACT FROM AUTHOR]

• The paper makes a significant contribution by conducting an in-depth and comprehensive literature review, synthesizing the current body of research on methods for detecting faults in LVDC-MGs. • The investigation entails conducting a detailed simulation of LVDC-MGs with diverse fault scenarios, configurations, and operational conditions that are systematically considered and analyzed. • The major contribution lies in the proposal of two novel fault detection techniques: K-CUSUM and K-DCUSUM. • The study adds significant value by conducting tests with different fault resistances, DG penetration, and introduction of noise. The energy industry is rapidly shifting from conventional to smart grid systems, involving advancements in microgrids and power management systems. However, achieving desired outcomes with the existing grid setup poses significant challenges. To address the above issues, adopting a Low Voltage Direct Current (LVDC) distribution system provides successful operational advantages. The primary objective of this work is to improve the system's security by developing a more resilient fault detection scheme. The presented work has proposed a Kernel-based Cumulative Sum (K-CUSUM) and Kernel-based Differential Cumulative Sum (K-DCUSUM) technique which is designed to identify changes in data under fewer assumptions. Instead of using the classical Maximum Mean Discrepancy (MMD) technique, the K-CUSUM and K-DCUSUM methods use a non-parametric MMD testing framework to evaluate incoming data by comparing it to reference distribution samples. Further, a comprehensive analysis is undertaken on an LVDC test system, considering fault scenarios involving pole-to-pole and pole-to-ground configurations. This research encompassed the determination of fault location, evaluation of fault resistance, examination of noise introduction, and an exploration of the influence of photovoltaic (PV) penetration. Moreover, the proposed approach is tested for a standard LVDC Microgrid. The results are compared with other contemporary techniques and recent literature. [ABSTRACT FROM AUTHOR]

Operating reserves (OR), alongside other ancillary services, are essential for mitigating the increasing uncertainty in generation from Intermittent Renewable Energy Sources (IRES). Traditional OR are determined based on rules of thumb, such as reliability considerations (N − 1 or N − k), and they neglect the uncertainty between dispatch intervals. Load–generation imbalances lead to excessive reliance on regulation reserves and out-of-merit dispatch. Highlighting this, recent literature has focused on developing models for dynamic reserve quantification. While the models significantly enhance the traditional static reserve quantification, they heavily rely on probabilistic approaches. Despite their effectiveness, probabilistic approaches are computationally complex and necessitate precise historical data. Furthermore, most studies do not consider the correlation between load and IRES when determining reserves, leading to inaccurate estimation and impacting the system's economics. Affine arithmetic-based models emerge as a promising solution, offering the ability to estimate correlated uncertainties with reduced computational complexity. This paper contributes to developing affine arithmetic models for OR quantification, considering IRES and load correlated uncertainties. Two distinct approaches to reserve quantification are explored: (1) deterministic scheduling with exogenous OR quantification, and (2) affine arithmetic-based scheduling framework to quantify and allocate OR endogenously. A comparative analysis is conducted with probabilistic scenario-based method and interval arithmetic scheduling. The effectiveness of the models is analyzed on the Great Britain test system with 40% renewable integration. Numerical results highlight that around 99% of the probabilistic net-load scenarios are within the net-load bounds generated by the proposed methodology. The reserve requirement is minimized by approximately 8% during peak hours and 35% during off-peak hours with correlated uncertainty. Furthermore, AA-based approach achieved a 15% reduction in total operating cost during the considered operational time-frame, compared to interval arithmetic optimization. • A multi-objective optimization model for reserve quantification and allocation. • Affine arithmetic based correlated uncertainties of renewable power and load. • Exogenous and endogenous methods for reserve assessment are presented. • Trade-offs between computational time and cost are deciding factors. [Display omitted] [ABSTRACT FROM AUTHOR]

• The model of the cyber-physical-transportation network is established. • A two-stage model is applied to enhance the resilience for power system. • The accurate model of restoration time of faulty components is presented. • The load recovery model of cyber-physical is established. In this paper, a two-stage collaborative stochastic optimization method for pre-disaster emergency repair station planning and post-disaster recovery strategy of cyber-physical-transportation networks is proposed in this paper to enhance the resilience under extreme scenarios. In the first stage, based on the principle of hierarchical portioning, the responsible area for the emergency repair station is divided by the community theory, and the emergency repair station planning model is developed. In the second stage, the time sequence of repairing the faulty components is first established based on the graph theory. Then, based on the spatial distribution of adjacent time-series faulty components on the transportation network, a faulty component restoration time model is established to accurately reflect the faulty restoration time. On this basis, the functional coupling effects of economic dispatch control and substation automation system failures on load recovery are analyzed to establish a load recovery model. The case studies of the IEEE RTS-79 test system demonstrate that, compared with traditional independent recovery model, the model proposed in this paper performs better in enhancing resilience under extreme scenarios. [ABSTRACT FROM AUTHOR]

• Enhancing the reliability of the electricity distribution system (EDS) in normal conditions by allocating the remote control switches (RCSs) using an MILP formulation. • Improving the resiliency of the EDS. Specifically, aiming to minimize the customers' interruption time and cost by using both the fragility and bathtub curves. • Improving the reliability and resiliency of the EDS by incorporating RCSs and distributed generations (DGs). • Conducting a sensitivity analysis of various factors, such as the customers' load, the investment cost, the RCS operations, and the failure rate. In today's world, power outages significantly impact people's lives. Improving the reliability and resiliency of the electricity distribution system (EDS) can significantly reduce the negative impact of power outages. In this regard, remote control switches (RCSs) are efficient devices that play a crucial role in enhancing the reliability and resiliency of EDSs. However, the challenge lies in strategically placing these switches to minimize power outages. This paper proposes a mixed-integer linear programming (MILP) formulation for the optimal allocation of RCSs. It considers load uncertainties and aims to enhance reliability under typical circumstances while reinforcing resiliency during extreme conditions. The formulation also considers two specific resilience criteria: the duration of interruptions experienced by customers and the total interruption cost incurred by all affected customers in the aftermath of disasters. A system is considered more resilient if individual customers experience fewer power interruptions during disasters. The formulation is rigorously assessed through its implementation on bus four of the Roy Billinton test system (RBTS4), and the outputs demonstrate that the proposed method improves both reliability and resiliency indices. Finally, this paper concludes with technical and economic comparative analyses that examine the effect of changing various parameters. [ABSTRACT FROM AUTHOR]

• Network Equivalent-based VQ Curve is used in real-time voltage stability assessment. • Voltage stability margin is derived from PV to VQ curves through network equivalent. • Network equivalent and power flow methods used to identify voltage stability limit. • Operation tasks encourage to explore the complementarity between PV and VQ curves. • Voltage and reactive power margins improve real-time voltage stability assessment. The PV and VQ curves have been widely accepted tools for monitoring voltage stability. Although these curves have been used in offline studies, their online applications are not trivial, involving specific issues and complexities concerning real-time environment. The literature presents some approaches to determine quantities related to voltage stability limit in real-time analysis of the PV curve. However, it does not occur with the corresponding quantities for the VQ curve, making it difficult to analyze these curves jointly. This work presents two significant innovative contributions, based on the use of real-time network equivalents estimated through measurement data. The first is a technique suitable for real-time applications to calculate the complete VQ curve, called Network Equivalent-based VQ Curve. The second is a methodology for determining voltage stability margins using information from both PV and VQ curves. Simulations were carried out in RVS Test System, and 9, 14, 30 and 118 Bus Test Cases available in MATPOWER. The results of Network Equivalent-based VQ Curve application were validated by power flow solution. The voltage stability assessment methodology proposed in this paper represents a significant advance, going beyond the traditional approaches. [ABSTRACT FROM AUTHOR]

• Two-stage robust optimization has been implemented to solve RFSCUCDRPs based on an economic investigation. • Determination of operational flexibility in power systems due to uncertainty caused by wind energy production and gas network. • The uncertainty set of the gas networks has been obtained in the SCUC by robust optimization. • A flexibility index is calculated for the RFSCUCDRPs problem for each scenario. The power system with flexibility provision will lead to the expansion of the utilization of renewable energy resources. Providing flexibility is one of the basic challenges for power system operators and developers, which is addressed in this study. Moreover, the security of the gas supply system is important for power system operators, because the operation of gas-fired units depends significantly on the gas supply. In this study, the availability of pipelines has been considered as a gas supply uncertainty. Then, an optimal uncertainty set is proposed for security constraint unit commitment (SCUC) which is calculated for managing the uncertainty of wind and gas supply in different scenarios of risk. Robust-based optimization has been implemented to obtain the optimal uncertainty set in which both feasibility and economic optimal robustness have been guaranteed. A new robust flexibility-based SCUC model has been applied using a demand response program (RFSCUCDRP). The transactive flexibility between flexible providers, such as thermal units and DR, and uncertainty producers, such as wind resources, has been determined in the proposed model. The problem has been implemented on the 6-bus and IEEE-118-bus standard test systems with different risk percentages. The operation costs of the 6-bus system with and without robust optimization are 89,094 $ and 119,475 $, respectively. It is concluded that robust optimization is ultimately economically better. [ABSTRACT FROM AUTHOR]

Flexible DC Transmission Systems (FDCTS) devices offer the most promising solution for Power Flow Management (PFM) problem in complex meshed MTDC grids. This paper proposes a new formulation for steady state analysis of a MTDC grid, integrated with the multiport version of the FDCTS device called Multiport Interline DC Current Flow Controller (MIDCCFC). MIDCCFC can regulate the current flow of two or more lines, thereby achieving line power flow regulation and aid for DC line breaking in a MTDC system. The proposed formulation integrates the steady state operating point of MIDCCFC with the MTDC system. The proposed formulation is tested on a 5 bus 320 kV meshed MTDC grid with 5-port MIDCCFC. A criterion is evolved to ensure the feasibility of the operating point obtained from the proposed formulation. The line current regulation range offered by MIDCCFC for line-12 in the test system is (30-3086) A. The impact of line-12 current variation on the system variables over the obtained range is investigated. The application of MIDCCFC for DC breaking is also investigated. The results are validated by performing steady state simulation of the test system in MATLAB/Simulink and real time simulation of the test system in Real Time Digital Simulator. [Display omitted] • Formulation of Power flow model for MIDCCFC integrated meshed MTDC system. • Application of Newton–Raphson based iterative algorithm for DC power flow analysis of MTDC system with MIDCCFC. • Criteria for feasible existence of the steady state operating point. • Validation of the power flow results in real-time using Real Time Digital Simulator (OP4510). [ABSTRACT FROM AUTHOR]

• A novel method for performing Decoupled Harmonic Load Flow (DHLF) analysis in radial distribution systems is presented • The proposed method involves solving load flow equations for both fundamental and higher frequencies as constrained minimization problems • The effectiveness of the proposed method is assessed across three IEEE test systems: 18-bus, 33-bus, and 69-bus. • Five cases of DHLF analysis are taken into consideration – cases with distributed generators (DGs), shunt capacitors (SCs), simultaneous DGs and SCs, and electric vehicles (EVs). In this article, a novel method for performing Decoupled Harmonic Load Flow (DHLF) analysis in radial distribution systems is presented. The proposed method involves solving load flow equations for both fundamental and higher frequencies as constrained minimization problems utilizing a nonlinear programming (NLP) CONOPT solver integrated into the General Algebraic Modeling Systems (GAMS) environment. The effectiveness of the proposed method is assessed across three IEEE test systems: 18-bus, 33-bus, and 69-bus. Five cases of DHLF analysis are taken into consideration. DHLF was performed on standard test systems with incorporated non-linear loads in the first case. Cases two through five examine the DHLF in the presence of distributed generators (DGs), shunt capacitors (SCs), simultaneous DGs and SCs, and electric vehicles (EVs). Comparing the obtained results to those of DHLF analysis tools ETAP and DigSilent, as well as to those found in the literature, proved that the proposed CONOPT solver provides precise solutions. [ABSTRACT FROM AUTHOR]

This paper presents a new, improved approach to fault location in long and very long transmission lines, which uses measurements at both terminals of the line that do not need to be synchronized, using the satellite time-reference. The new method employs symmetrical component sequence voltage profiles that are computed using an innovative approach in which the detailed three-phase model of a multiconductor transmission line is represented as the series connection of several chain matrices. This allows the new method achieve the best performance, when compared to other 4 similar fault location approaches, requiring measurements at both terminals of a symmetrical line, considering all types of faults, under realistic variations in variables and parameters of the test system, including the effect of saturation of current transformers, and arc faults. The main advantage of this proposed technique is that it can be applied with no major changes in symmetrical and unsymmetrical transmission lines keeping its good performance. In addition, division of the line in chain matrices allows the new proposed approach to be applied in non-homogeneous lines. In this paper, for space reasons, the new approach is initially applied to symmetrical (ideally transposed) transmission lines only, with very successful and encouraging results. • This approach considers the detailed model of a multiconductor symmetrical line. • It achieves the best performance of all the considered algorithms of this type. • It was tested successfully considering 15 different realistic conditions. • Measurements do not have to be synchronized. • The simplicity of the algorithm, make it adequate to be implemented in a relay. [ABSTRACT FROM AUTHOR]

• Proposing new convex optimization model to improve resiliency of electrical network. • Considering both planning and operational aspects as a complete technique. • Considering resiliency of electrical networks through multi-scenario disasters. • Dynamic micro-grid formation is applied to guarantee sustainability of networks. • Considering load priority, uncertainty of wind turbine and photovoltaic generation. Due to increasing the intensity and frequency of natural catastrophes, sustainable supplying of consumers is one of the main challenges of electrical distribution companies against these high-impact and low-probability (HILP) events. Recently, researches are directed to solve the mentioned challenge by various methods including optimal distributed generation and energy storage placement, micro-grid formation, structural reinforcement and etc. In addition, the uncertainty nature of the disasters, loads and renewable generations has influenced these studies. Despite the availability of different solutions considering all resilient-oriented methods and uncertain parameters, applying a proper model as long as simplifying the equations, which satisfies all the needs, are still the outstanding aspects that must be studied. This paper applies and proposes convex equations in all parts, including both operational and planning perspectives as an innovation. Mixed-integer quadratically-constrained programming (MIQCP) is adapted for formulating the problem. The proposed model is developed under GAMS environment, and its performance is evaluated by the IEEE 33-node test system under various severe fault scenarios. Comparing the results reveals that the hybridization technique against only planning technique leads to a decrease of 46.15 % and 42.45 % in load shedding and investment costs respectively. Also, it causes a decrease of 40.63 % and 25.32 % in load shedding and investment costs respectively compared to only operational techniques causes. [Display omitted] [ABSTRACT FROM AUTHOR]

• ML-Assisted Benders Decomposition for large-scale stochastic optimization problems • Application to power system expansion planning under uncertainty • Able to solve larger problems that are otherwise computationally intractable • Reduces the execution time of Master MILP Problems • Generalizes well to modified problems without re-training of ML models. The necessary decarbonization efforts in energy sectors entail integrating flexible assets and increased levels of uncertainty for the planning and operation of power systems. To cope with this in a cost-effective manner, transmission expansion planning (TEP) models need to incorporate progressively more details to represent potential long-term system developments and the operation of power grids with intermittent renewable generation. However, the increased modeling complexities of TEP exercises can easily lead to computationally intractable optimization problems. Currently, most techniques that address computational intractability alter the original problem, thus neglecting critical modeling aspects or affecting the structure of the optimal solution. In this paper, we propose an alternative approach to significantly alleviate the computational burden of large-scale TEP problems. Our approach integrates machine learning (ML) with the well-established Benders decomposition to manage the problem size while preserving solution quality. The proposed ML-enhanced Multicut Benders Decomposition algorithm improves computational efficiency by identifying effective and ineffective optimality cuts via supervised learning techniques. We illustrate the benefits of the proposed methodology by solving multi-stage TEP problems of different sizes based on the IEEE24 and IEEE118 test systems, while also considering energy storage investment options.. [ABSTRACT FROM AUTHOR]

• Proposing an active control strategy. An active control strategy is achieved by setting different reference values of the filter inductor current of each DG when the fault intensity of the active distribution system changes. • Analysis of the effect of the active control strategy on the faulty feature. A detailed fault theory analysis is conducted by considering the active control strategy. It presents how the active control strategy influences the faulty feature. • Proposing a protection criterion based on fundamental phase angle difference. With the help of the active control strategy, this criterion can simplify the calculation procedure and coordination among different relays. To enhance the fault current amplitude of active distribution systems during the weak fault period and decrease the influence of the measurement equipment noise, this paper proposes an active protection method based on superimposed phase currents for active distribution systems. This method is shown as follows. First, the reference value of the filter inductor current of each distributed generator (DG) is set as different values when the fault intensity of the active distribution system changes. Second, the superimposed phase current in each relay is obtained by subtracting each sample of phase current from its corresponding sample of phase current in the previous cycle. Third, the fundamental phase angle of the superimposed phase current is extracted. This is because the fundamental current component of the superimposed current cannot be affected by the active control strategy, which is proved in this paper in detail. Meanwhile, the feature direction is built by fundamental phase angles at both ends of the line to detect faulty zone. Finally, the proposed protection method has been validated in a modified IEEE 13-bus test system, and the test results prove the effectiveness of the proposed active protection method that can enhance the faulty feature to detect faults. [ABSTRACT FROM AUTHOR]

This article proposes a worst-case generalized active disturbance rejection control (WGADRC) technique for power systems with parametric uncertainties. The proposed scheme is based on the worst-case plant selection strategy. Firstly, a worst-case model of the plant is identified out of the various possible models of an uncertain system, and afterward, the GADRC scheme is employed to design a controller. The best feature of the proposed scheme is that the designed controller ensures superior performance under nominal as well as uncertain plant conditions than other control schemes in the existing literature. To authenticate the supremacy of the proposed methodology, the load frequency control (LFC) issues associated with numerous power systems such as single-area thermal power system, IEEE 39 bus 10 machine test power system, and higher order hydro-thermal power system involving unmodeled parametric uncertainties, unexpected nonlinearities, and physical discrepancies are considered. • A worst-case mathematical model of the uncertain plant is obtained instead of the nominal fixed parameter plant model. • A novel worst-case GADRC (WGADRC) technique is developed considering GDB and GRC-type nonlinearities. • The supremacy of the proposed scheme over pre-existing control techniques is validated on the single-area power system and IEEE 39 bus 10 machine power system to cope with the LFC problem. • The effectiveness of the proposed technique is further extended to the high-order hydro-thermal power plant subjected to bounded parametric uncertainties. [ABSTRACT FROM AUTHOR]

• The inherent difference between global active and reactive power sharing schemes is discussed and revealed. Two suitable communication topologies and their constraint requirements for global active/reactive power sharing management are discussed and proposed based on graph theory. • Precise global power sharing management are fulfilled. BICs can cooperatively adjust their power outputs with the frequency and active/reactive power sharing rate signals based on communication with neighbors. Accurate global active/reactive power sharing management is achieved, and the frequency and bounded voltage are restored. • The consensus and stability of the proposed cooperative control strategy are proved. The Lyapunov function of the dominated modes in the proposed two-layer method is built. The consensus and stability are thoroughly investigated and proved. Flexible multi-terminal direct current (MTDC) connection scheme is an ideal way to integrate multiple adjacent microgrids and form interconnected microgrids (IMGs). However, under the traditional control mode, MTDC will lead to frequency/voltage decoupling among all the microgrids. Moreover, improper control scheme design of bidirectional interlinking converters (BICs) in MTDC will make global active/reactive power sharing management impossible, which is considered as the significant task in IMGs. Therefore, a novel distributed cooperative control strategy is designed in this article. In the proposed control strategy, frequency/voltage regulations and local active/reactive power sharing management are achieved through distributed secondary control within each MG. Accurate global active/reactive power sharing management is realized by coordinating the power exchange instructions of each BIC in a distributed manner. The control dynamics of these two levels are designed to be decoupled. The stability of the proposed control strategy is demonstrated by the Lyapunov method, and its effectiveness is verified by simulating a test IMG system in MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

• A new comprehensive voltage stability index that characterized by minimal assumptions is formulated and suggested. • Develop a proposed index based on the most accurate transmission line model that can consider the impact of line length on voltage stability evaluation. • The new index takes into account the impact of off-load and on-load tap changer transformers that verified its accuracy by implementing some cases. Recently, voltage stability has become increasingly important because of the expansion and growing demands on power transmission networks. Several factors may contribute to the blackouts occurrence in power system, including severe voltage instability and insufficient power transfer capabilities. To avert voltage collapse in power grids, identifying the critical operating conditions with high precision is crucial. By representing a new index in this paper, the assessment of voltage stability within transmission networks can be undertaken. In contrast to other indices, the proposed index has least assumptions and can assess the voltage stability in power systems with significant precision. Afterward, the suggested index is broadened to encompass the influence of on-load tap changers (OLTC). In order to attain this, the OLTC model has been developed using a precise implementation of mathematical equations, enabling an accurate evaluation of the impact of tap changer variations on voltage stability. To ascertain the efficacy of the proposed index, an evaluation has been conducted on a two-bus as well as 9-and 30-bus transmission test systems under various operational scenarios. The simulation outcomes suggest the superior effectiveness of the suggested index compared to other well-established indices. These results illustrate its ability to accurately assess the impacts of OLTC. [ABSTRACT FROM AUTHOR]

• Compatible parameters-based method. • Multi-objective bat algorithm. • Minimizing total harmonic voltage and current distortion reduction, minimizing investment cost, and maximizing power factor compensation. This study propose a comprehensive filter design method based on passive power filter topology and its characteristics. The proposed design parameters are suitable for heuristic algorithms for addressing incompatibility problems. Additionally, the proposed compatible parameter-based method was applied to the optimisation filter design of power systems with harmonic pollution. The proposed optimal filter design in this study, based on a multi-objective bat algorithm, simultaneously achieved total harmonic voltage and current distortion reduction, minimised investment costs, and maximised power factor compensation. The performance of the proposed method was validated using various test systems. [ABSTRACT FROM AUTHOR]

In the modern distribution management system, state estimation (SE) has a key role in monitoring the entire distribution system using advanced measurement units. Since the conventional weighted least squares (WLS) approach faces convergence issues due to insufficient measurement devices in the distribution system, deep learning (DL) models are highly effective in performing SE. However, the existing DL models suffer from generalizability issues, unawareness of the system's physics, and scalability issues. To address this, physics-based deep learning models have been introduced. In this paper, a physics-based temporal convolutional neural network (Ph-TCN) is proposed to perform distribution system SE (DSSE). The first stage of the proposed approach utilizes a conventional TCN model in a supervised manner for the estimation of system states, while the latter stage incorporates physics-based properties to reconstruct the measurements. The use of the TCN model in first stage facilitates the capturing of temporal features with a large receptive field, whereas the inclusion of physics equations in the second stage with problem-specific Huber-loss function enhances the performance of the model to provide accurate SE results. Simulation studies are performed on modified IEEE 13-node and IEEE 37-node distribution test systems and the corresponding results have been compared with the WLS approach and existing DL models. The numerical results show that the proposed Ph-TCN approach has exhibited superior performance and its robustness is also tested under the presence of different percentages of missing measurement data. Finally, the models' performance is also evaluated for the modified IEEE 123-node distribution system to check for the scalability issues. • A Physics-based TCN model is developed for distribution system state estimation. • A novel loss function by combining MSE and problem-specific Huber loss is used. • The model performance is compared with WLS, physics-based deep learning approaches. • The robustness of the proposed model is tested at different levels of missing data. • The results prove that the proposed model performance is effective for DSSE. [ABSTRACT FROM AUTHOR]

• Novel methods for mitigating undesired voltage rises in modern-day transmission power systems. • Comparison of methods. • Application on two actual power systems. • Very promising results and showcase of major contribution by renewable energy sources. This paper proposes some novel methods for mitigating undesired voltage rises in modern-day power systems. Some older approaches are also revisited in the light of new developments including the proliferation of power-electronic interfaced equipment. The analysis is performed using both power flow technique as well as long-term simulation employing quasi-steady-state approximation of short-term dynamics. Guidelines and mitigation countermeasures that may be utilized during either system planning or operation are investigated, such as optimal placement of new reactor installations, special transformer load-tap-changer (LTC) controls and reactive power absorption by renewable energy sources, such as wind farms connected through power converters in distribution feeders. Several case studies are investigated in two test systems: a sub-transmission area of the French Transmission Grid, and the Hellenic transmission power system, for which a number of different operating points is considered. [ABSTRACT FROM AUTHOR]

The transmission line is an essential and long element that plays a vital role in the operation of an electric power system. Quick and accurate fault detection along with classification helps the system operator locate the fault as soon as possible in the transmission line. The method proposed in this paper works fast and accurately for fault detection and classification. A fault identification matrix (FIM) based on the change in the resultant current samples of α - β components and signs of the rate of change in α and β component currents (R o C C α and R o C C β ) at both ends of a transmission line for fault detection is proposed. A strategy using the second-order harmonic component of redefined Clarke-transformed currents of the transmission line for the fault classification is framed. The proposed method has been tested with all types of short circuit faults and validated under various abnormal conditions in PSCAD/EMTDC simulations. In all fault cases, the proposed method detects and classifies the faults within a cycle. The fault detection and classification results signify that the proposed method is fast, reliable and parameter-independent. It is concluded that the proposed method can effectively work on any configured transmission network. • |FIM| and RoCCs are proposed using Clarke's currents to detect faults. • A classification strategy proposed using SHCs of redefined Clarke's currents. • The method was validated on the standard two-bus and IEEE-9 bus test systems. • The proposed algorithm is simple and set free. • The reliability of the proposed method has been ensured in all abnormal conditions. [ABSTRACT FROM AUTHOR]

In this paper, a systematic short- and long-term voltage stability analysis of grid-forming converters with current limitations is conducted. For this, sampling studies are performed in an aggregated version of the Nordic test system. Here, the grid-forming control approach, the simulation type (EMT/phasor), current prioritisation and load composition are varied. Also, a stability-enhancing control method is developed to stabilise the converter during current limitation. The proposed method does not require any parameter tuning and can be applied to almost all grid-forming approaches. Its performance is demonstrated by comparing it to similar methods. The results show that the proposed method can greatly improve short- and long-term voltage stability for all investigated grid-forming approaches. In addition, accurate load models are crucial, as small modelling differences can have a greater impact on stability than the choice of simulation type. Here, both simulation types show the same voltage dynamics but have small differences in the stability limits. • Voltage stability analysis of various grid-forming converters with current limitation. • Variations in control approach, model type (phasor/EMT) and current prioritisation. • Derivation of a computationally efficient power system model for sampling studies. • Short and long-term voltage instability can occur due to current limitation. • A proposed stability-enhancing control method can stabilise the converter. [ABSTRACT FROM AUTHOR]

In this paper, a classifier based early warning system is designed, trained and tested based on time-series of Phasor Measurement Unit (PMU) measurements at all buses in a power system. The classifier is based on a novel combination of Graph Attention Networks and Long Short-Term memories, and is trained to label power system data in the form of captured windows of PMU measurements. These labels are then used to provide early warning for transient instability. The classifier is trained and tested data from simulations of the Nordic44 test system, and includes extensive topological variations under two different load levels. It is found that accurate early warnings can be provided, but the quality of prediction is highly dependent on specific power system characteristics, such as how quickly the power system responds to transient disturbances. • A Graph Attention Network is trained for transient stability classification. • Classifier results are processed to provide early instability warnings. • Accurate early warnings are possible. • Provided warning times are found to be system dependent. [ABSTRACT FROM AUTHOR]

Increasing renewable integration leads to faster and more frequent fluctuations in the power system net-load (load minus non-dispatchable renewable generation) along with greater uncertainty in its forecast. These can exacerbate the computational burden of centralized power system optimization (or market clearing) that accounts for variability and uncertainty in net load. Another layer of complexity pertains to estimating accurate models of spatio-temporal net-load uncertainty. Taken together, decentralized approaches for learning to optimize (or to clear a market) using only local information are compelling to explore. This paper develops a decentralized multi-agent reinforcement learning (MARL) approach that seeks to learn optimal policies for operating interconnected power systems under uncertainty. The proposed method incurs less computational and communication burden compared to a centralized stochastic programming approach and offers improved privacy preservation. Numerical simulations involving a three-area test system yield desirable results, with the resulting average net operation costs being less than 5% away from those obtained in a benchmark centralized model predictive control solution. • A decentralized, multi-agent method for multi-area power exchange with uncertainties. • The proposed method reduces computational and communication requirements. • The proposed method requires less knowledge regarding the uncertainties. • Derived policies are practical, efficient, and expedite implementation. [ABSTRACT FROM AUTHOR]

This paper explores the potential application of quantum and hybrid quantum–classical neural networks in power flow analysis. Experiments are conducted using two datasets based on 4-bus and 33-bus test systems. A systematic performance comparison is also conducted among quantum, hybrid quantum–classical, and classical neural networks. The comparison is based on (i) generalization ability, (ii) robustness, (iii) training dataset size needed, (iv) training error, and (v) training process stability. The results show that the developed hybrid quantum–classical neural network outperforms both quantum and classical neural networks, and hence can improve deep learning-based power flow analysis in the noisy-intermediate-scale quantum (NISQ) and fault-tolerant quantum (FTQ) era. • Quantum neural networks are used for deep learning-based power flow analysis. • The performance of quantum neural networks is systematically assessed. • The use of quantum neural networks can significantly improve generalization ability. • The experiments are performed using small-scale distribution networks. • Hybrid quantum–classical neural networks are recommended as models of choice. [ABSTRACT FROM AUTHOR]

Thévenin equivalent has been considered the standard power system representation for short-circuit analysis. However, the increasing penetration of power electronics in modern power systems introduces diversified short-circuit current responses which are not considered by conventional Thévenin equivalent. As an alternative, this paper proposes a different dynamic grid equivalent representation for short-circuit analysis of power systems with power electronics. The equivalent parameters are identified to accurately capture the dynamic short-circuit current responses contributed by power converters. Also, the equivalent parameters are varied from different depths of short-circuit fault in order to cover various fault conditions. The proposed grid equivalent has been tested and validated on studied systems with Voltage Source Converters (VSCs). • This paper proposes a new dynamic equivalent for short-circuit analysis of power systems with power electronics. • The equivalent parameters are obtained considering both fault dynamics and steady-state short-circuit current. • Case-studies in test systems with VSCs validate the effectiveness of the proposed equivalent. [ABSTRACT FROM AUTHOR]

This paper presents a novel model order reduction technique tailored for nonlinear power systems with a large share of inverter-based energy resources. Such systems exhibit an increased level of dynamic stiffness compared to traditional power systems, posing challenges for time-domain simulations and control design. Our approach involves rotation of the coordinate system of a linearized system using a transformation matrix derived from the real Jordan canonical form, leading to mode decoupling. The fast modes are then truncated in the rotated coordinate system to obtain a lower-order model with reduced stiffness. Applying the same transformation to the original nonlinear system results in an approximate separation of slow and fast states, which can be truncated to reduce the stiffness. The resulting reduced-order model demonstrates an accurate time-domain performance, the slow eigenvalues of the linearized system are correctly preserved, and a reduction in the model stiffness is achieved, allowing for accurate integration with increased step size. Our methodology is assessed in detail for a 3-bus system with generation units involving grid-forming/following converters and synchronous machines, where it allows for a computational speed-up of up to 100 × compared to the original system. Several standard larger test systems are also considered. • Models of power systems with large share of renewables exhibit increased stiffness. • Model order reduction approach tailored to reduce stiffness of (nonlinear) systems. • Real Jordan canonical form to separate fast and slow modes of linearized system. • Numerical results for various (large-scale) low-inertia test systems. • Computational speed-up of up to 100 × compared to the original (stiff) model. [ABSTRACT FROM AUTHOR]

• In this paper, Sub-DMD algorithm is applied to the identification of PFs in power systems. It is rare that this method is based on ambient data, and the identification of PFs can be carried out in real-time in the system. • Different from the traditional method of extracting PFs based only on eigen-decomposition, the proposed algorithm is used to obtain the low-dimensional approximate matrix of the system, and then use eigen-decomposition and model energy calculation to obtain the PFs of variables in electromechanical oscillation modes. • The traditional model-based SSSA method calculates the PFs related to the state variables, but cannot extract the PFs of the algebraic variables in the system. The data-driven method in this paper can extract the PFs of both state variables and algebraic variables. This paper focuses on the extraction of PFs of algebraic variables. • On the IEEE 4-generator 2-area test system and IEEE 16-generator 68-bus test system, the accuracy of the extracted PFs related to the active power (P e) of the generator is proved by the change of the damping ratio of the inter-area oscillation mode caused by the power generation dispatching. And the conclusion shows that the PFs related to Pe extracted by Sub-DMD can be directly used to guide the open-loop damping modulation of the system. Analyzing the connection between the variables participating in the oscillation and modes in electromechanical oscillation is particularly important for maintaining system stability. This paper proposes an ambient data-driven method based on Subspace Dynamic Mode Decomposition (Sub-DMD) to extract the Participation Factors (PFs) related to system state and algebraic variables in electromechanical oscillation modes. This method uses ambient data to calculate the low-dimensional approximate matrix of the system, and the PFs is extracted by using eigen-decomposition and mode energy. Compare the extracted PFs with the results of power generation dispatch. The effectiveness of the proposed method is demonstrated by using simulation data from IEEE 4-generator 2-area test system and IEEE 16-generator 68-bus test system. [ABSTRACT FROM AUTHOR]

The mobile energy storage system (MESS) with temporal and spatial flexibilities plays an important role in resilience enhancement of power systems. However, the aging characteristics of these mobile storage facilities are rarely considered or not exactly quantified in the general MESS scheduling approach and consequently the economical operation of MESSs can't be ensured during dispatch. To address this issue, in this work, the degradation cost of batteries in MESSs is integrated into a resilience-oriented scheduling model for distribution networks. Specifically, the empirical degradation model is linearized as a function of the state of charge (SoC), depth of discharge (DoD), and current rate. The nonconvex term of degradation cost model is further linearly relaxed by the McCormick envelope method. The scheduling problem is formulated as a mixed integer linear program (MILP) model so that the dispatch decisions of MESSs can be derived by using commercial solvers. Finally, the proposed model is validated by several case studies on IEEE 33-bus and 118-bus test systems. The comparative results demonstrate that the degradation-aware scheduling model can markedly decrease the degradation cost of MESSs while enhancing the resilience of distribution networks. Following the load interruption cost reduction of 42.52% and 34.77%, the degradation cost of MESSs during scheduling will decrease by 47.58% and 36.59% for the 33-bus and 118-bus systems. • A degradation-aware scheduling model of mobile energy storage systems is established. • The battery degradation cost is determined using high-fidelity modeling. • The McCormick envelope relaxation is utilized for the linearization of degradation model. • The proposed model shows benefits in co-optimization of resilience and MESSs' operation. [ABSTRACT FROM AUTHOR]

• This paper proposes a novel fast time-domain protection scheme in a large-scale PPP system, with prominent features such as simplicity. • There is no need of parameters tuning because of the adaptive nature of ITD. Also, all the protection scheme parameters are determined analytically, such as threshold value and number of iterations. • A wide variety of fault scenarios are analyzed for fault detection such as different fault resistance, location and types. • Communication medium is not required. Consequently, there is no communication delay and data loss. • The protection scheme's capability in various conditions such as noisy environments, uncertainty in renewable energy generation, change in GC, various sampling frequencies and CT saturation is discussed. • The proposed protection scheme is tested in two the 2-bus and IEEE 39-bus test systems in MATLAB and PSCAD environments. The performance of a distance relay can be significantly affected by various uncontrolled factors such as fault resistance, fault type, fault location and noise. Moreover, when photovoltaic power plants are integrated into electrical grids, they exhibit distinct fault current characteristics compared to conventional power systems with synchronous generators. These factors introduce variations in the recorded apparent impedance, deviating from the predefined settings of the distance relay. This paper presents an effective scheme for fault detection using ITD methodology. The ITD method decomposes the target signal into proper rotation and monotonic signals, which are then used to calculate the Energy Index. The performance of this scheme has been extensively investigated under various scenarios, including fault resistance, fault location, fault type, CT saturation, GC compliance, noise, and sampling frequency. To validate the effectiveness of the proposed scheme, simulations are conducted using both the PSCAD/EMTDC and MATLAB software. The proposed scheme is assessed using both the 2-bus and IEEE 39-bus test systems. The results show the merit and effectiveness of the proposed scheme in the accurate diagnosis of fault detection with 400 Ω fault resistance, in the presence of 20 dB noise, with variable sampling frequency (0.5-16 kHz) and variable irradiance values (600-1000 (W / m 2)) in power systems. [ABSTRACT FROM AUTHOR]

Massive integration of distributed generation originates the active distribution networks, introducing new control, protection and operation challenges. This paper proposes a strategy for adaptively protecting active distribution networks that undergo frequent changes in operating conditions. Numerical overcurrent relays capable of storing multiple setting groups, each with different settings designed to address various operating conditions, are used to overcome this issue. The proposed strategy uses locally acquired voltage and current measurements to accurately identify the operating conditions during fault occurrence. The identified condition is then used to select the appropriate overcurrent relay settings using a strategy which includes signal characterisation, data recognition, and optimisation to minimise the operating time for both primary and backup relays. Validation of the protection strategy is conducted on the IEEE 34-Bus test system, and the results indicate its ability to accurately detect different operating conditions in both connected and islanded operating modes, even in the presence of high-impedance faults and load variation. The performance rate exceeds 97.27% for all analysed cases, and the proposal identifies the operating condition in less than 20 ms after fault inception, demonstrating its low computational burden and suitability for implementation in field applications. • A fast method for recognising system operating conditions (OCs) is presented. • Relays are adaptively adjusted using the recognised OC. • The proposed adaptive relay uses locally acquired voltage and current measurements. • The optimised relay coordination is based on nonlinear objective functions. [ABSTRACT FROM AUTHOR]

• Optimal voltage/VAR control for active distribution networks with distributed PVs. • Active management of branch switches, tap changers, VAR compensators, smart PVs. • Mixed integer second-order cone programming-based formulation. • Multiple network operation modes are encoded and tested. • Multiple smart PV operation modes are encoded and tested. Rapidly increasing penetration of distributed PVs brings great challenges to distribution networks. Driven by the revised IEEE 1547 standard, inverter-based smart PVs provide customized control and voltage regulation capabilities. This paper presents a comprehensive study investigating voltage/VAR control considering network reconfiguration, VAR optimization, and smart PVs. To do so, a second-order cone programming-based VAR optimization and network reconfiguration (VONR) model is formulated. The enhanced necessary radiality condition, and the extensions for multiple smart PV operation modes and multi-period operation are provided. A comprehensive case study considering various network and smart PV operation modes, and hourly VONR operation is conducted. The results show that implementing VONR with smart PV reactive power dispatching optimizes the scheduling plans, resulting in a reduction of network loss by 59.97 % and 30.37 % for the 33-bus and 123-bus test systems, respectively, compared to the no-control operation. [ABSTRACT FROM AUTHOR]

• Detailed modeling of CIGRE-14 bus standard test system along with inverter control scheme (with and without grid code) and protection system is done in PSCAD environment. • The performance of directional relaying schemes (32Q and 67pos,67neg,67zero) are evaluated in the presence of inverter-interfaced renewable energy resources. A comparative study on the performance of the relays is done in the presence of inverter-interfaced renewable energy resources for different fault types and fault resistances. • The interdependencies between the inverter control scheme used and performance of relaying schemes have been analyzed through mathematical analysis and circuit realization of the inverter-interfaced renewable energy resources. • Based on the mathematical analysis and circuit realization, the probable causes of relay failures in the presence of inverter-interfaced renewable energy resources are detailed. • The impact analysis of the dynamic response of the controller on the protective relay settings from the perspective of protection operation time-frame has been attempted. The potential impacts of the inverter-interfaced renewable energy resources (IIRERs) on the performance of sequence-based directional relaying schemes (SBDRS) have been investigated in this paper. The directional overcurrent relays such as 67 POS , 67 NEG , 67 ZERO and 32Q have been considered for the investigation. CIGRE-14 bus system with IIRERs along with detailed modeling of inverter control scheme (with and without grid codes) and SBDRS have been done in the PSCAD environment. The mathematical analysis and circuit realization of the IIRERs have been attempted in the paper. The exclusive fault characteristics exhibited by IIRERs cause the conventional SBDRS to mal-operate. Significant change in levels of sequence currents and angular relationships between sequence voltages and currents during faults contributes to relay's unpredictable behavior. The comparative study based on different fault types, fault resistances and interconnecting transformer connections have also been done. The study reveals the impact of non-generalized angular differences between positive sequence voltage and current at the inverter terminal on performance of 67 POS. It is found that 67 NEG and 32Q mal-operated for all types of unbalanced faults while the 67 ZERO can be utilized for grounded fault with delta-star grounded connection of interconnecting transformer. [ABSTRACT FROM AUTHOR]

Traditional methods for assessing the resource adequacy (RA) of a power system are becoming obsolete due to emerging trends such as the increasing deployment of variable renewable energy and storage. Consequently, analysts are recommending that RA be assessed using a Monte Carlo simulation approach that models chronological power system operations over many instances of possible operating conditions. However, this approach is necessarily more complex and computationally demanding, which is an obstacle to real-world implementation. In this study, we investigate which operational details of power systems are important to capture in order to accurately evaluate a system's RA, versus details that add complexity but do not meaningfully affect RA results. To do so, we develop a probabilistic RA assessment framework by adapting an existing production cost model and apply it to a case study based on the IEEE Reliability Test System. Our results indicate that multi-year data, storage dispatch, and transmission limits are key details to incorporate. Accurate RA results can be obtained using non-economic dispatch strategies as long as they are coordinated with detailed operational strategies. We also demonstrate how popular expectation-based RA metrics can mask important differences in the characteristics of loss of load events. • Power systems are evolving to feature more renewables and storage. • Motivates resource adequacy (RA) assessments that model system operations. • We investigate how representations of operational details affect RA outcomes. • Multi-year data, transmission limits, and storage dispatch are important to include. • Economic dispatch objectives and day-ahead forecast errors are less important. [ABSTRACT FROM AUTHOR]

• Admittance Angle Based Fault Detection for Microgrid Protection. • Proposed Scheme utilizes Rate of Change of Differential Positive Sequence Admittance Angle parameter for Fault Detection. • Efficient Scheme for detection of Shunt Fault, Three-Phase Fault and High Impedance Fault. Advancement in converter control technology enables extensive integration of renewable energy sources (RES) in a grid or distribution network and operates as a single controllable entity constituting a microgrid (MG) to provide several benefits. Further intermittency of RES modified network topology; different operating modes of MG imposes protection challenges. The fault current level varies significantly with changes in operating conditions; thus, the conventional overcurrent relays cannot detect shunt faults (SFs) and high impedance faults (HIFs). This paper introduced an efficient protection scheme utilizing the Rate of Change (ROC) of the differential positive-sequence admittance angle (DPSAA) parameter and issued the trip signal (TS). The proposed scheme is compared with the existing scheme to evaluate the performance and efficacy of the proposed scheme. Furthermore, the proposed and existing schemes are tested and validated on the modified IEEE 13 Bus test system (BTS) in MATLAB R2021b /SIMULINK platform. The obtained test result reveals the proposed scheme's efficacy in detecting both SFs and HIFs. [ABSTRACT FROM AUTHOR]

This paper presents an interval approach for the Holomorphic Embedding Load Flow Method (HELM) considering load and generation uncertainties. In the proposed method, power flow equations are considered as holomorphic complex functions, being their solutions determined recursively based on the expansion in Maclaurin series and analytical continuation using Padé approximants. The concepts of the interval arithmetic are applied into the HELM equations assuming active and reactive powers as uncertain data to obtain interval values associated with the voltage phasors for all the system buses. The procedures to calculate interval results are described along the paper including the use of interval arithmetic concepts applied into the HELM equations. IEEE test systems such as 6, 14, 30 and 57-bus are used for computational simulations, being the results compared with Monte Carlo (MC) approach, Krawczyk method, Taylor series, affine arithmetic and the traditional interval power flow. As important contribution, a novel interval power flow technique is presented allowing to compute interval values closer to the ones determined by MC simulations than other alternative methods. Results are obtained in a computational time approximately 500 times faster than the MC approach considering 20,000 simulations and the interval sensitivities are, at least, twice lower than other interval methods. • The Interval Holomorphic Embedding Load Flow Method (IHELM) is presented. • Load and generation uncertainties are considered. • Results are obtained in an advantageous computational time. • Voltage intervals are determined by a direct method. [ABSTRACT FROM AUTHOR]

• Bi-directional power electronic switches enable a rapid and flexible conversion between low reactance in non-current-limited mode and high reactance in current-limited mode, suppressing the development of DC faults while achieving current limitation during mechanical switch opening. • The energy absorbed by the MOV is reduced. • DC opening time is shorter. • The proposed DCCB has economic advantages. The use of a DC circuit breaker to open and isolate DC faults in a flexible DC grid is one of the simplest and most reliable methods for handling DC faults. However, current limiting capacity and opening time generally contradict each other in most DC circuit breakers during the DC opening process. Furthermore, current limiting is generally not possible during mechanical switching, which results in higher requirements for the quick-acting nature of protection. To address these issues, a bi-directional current-limited hybrid DCCB topology with fast DC fault opening is proposed. Bi-directional power electronic switches enable a rapid and flexible conversion between low reactance in non-current-limited mode and high reactance in current-limited mode, suppressing the development of DC faults while achieving current limitation during mechanical switch opening, in addition, the time for the arrester to release energy is shortened. The simulation testing system is built on PSCAD/EMTDC, using the Zhangbei Flexible DC Grid project as the engineering background. Comparative analysis of numerous test results demonstrates that the proposed DCCB topology has low DC breaking voltage and current stress, short breaking time, and certain economic benefits. [ABSTRACT FROM AUTHOR]

Fault distance estimation (FDE) in transmission lines with a thyristor controlled series compensator (TCSC) is a challenging task since the performance of FDE techniques gets affected by the variations in measured terminal voltages and line currents caused by the operation of TCSC during faults in the lines. Therefore, a robust FDE technique is utmost required for quicker power system restoration in the event of lines experiencing faults. Consequently, a matching pursuits algorithm (MPA) based traveling wave detection technique is presented in this work. The method is further utilized for FDE in lines with TCSC. The aerial-mode terminal bus voltage of the line is considered. The proposed technique first reconstructs the aerial-mode signals using MPA followed by determination of residuals from the difference of original and reconstructed signals. The next step determines time of arrival waves from respective peaks of the Teager energy of residual signals. Finally, the obtained ATWs are utilized for FDE. For simulation, a 3-machine 9-bus test system with one of its line compensated with TCSC is modeled in PSCAD/EMTDC platform. Different case studies are undertaken to validate the effective performance of the proposed technique. Further, comparative assessment is carried out to test the superiority of presented technique. • Fault distance estimator (FDE) for TCSC compensated transmission lines is proposed. • The proposed estimator utilizes the information of traveling waves terminating at two terminals. • Matching pursuits algorithm (MPA) is used detect traveling waves by decomposing modal voltage signals. • The peak of Teager energy of decomposed signal estimates arrival time of wave at the terminal of the line. • For simulation, WSCC 9 bus test system with TCSC compensation is used. [ABSTRACT FROM AUTHOR]

• This paper investigates the decision-dependence relationship between demand response commitment and the corresponding scheduling uncertainty. • A novel data-driven risk-averse tri-level (i.e., outer, middle, inner) two-stage (dispatching & operational) economic dispatch framework is proposed to address the demand response uncertainty. • A decomposition framework embedded with Benders' and Column-and-Constraint generation methods is used to obtain the optimal solution of the proposed distributionally robust optimization model. Demand response (DR) is usually regarded as a valuable balancing and reserve resource that contributes to maintaining the power balance. However, electricity customers can freely decide whether to reduce their electricity consumption or not in the liberalized day-ahead market and therefore DR is difficult to predict. Considering that, this paper investigates a novel tri-level two-stage data-driven / distributionally robust optimization risk-averse and decision-dependence economic dispatch framework to incorporate DR uncertainties into the day-ahead electricity market clearing process. First, DR commitment is made after establishing the decision-dependence relationship between DR commitment and the corresponding dispatching uncertainty. Then, we construct an ambiguity set for the unknown distribution of the DR uncertainty by purely learning from the historical data. Considering the worst-case distribution within the ambiguity set, an optimal strategy is investigated for scheduling the hourly uncertain DR in day-ahead markets. Finally, a decomposition framework embedded with Benders' and Column-and-Constraint generation (CC&G) methods is built for identifying the optimal solution. The effectiveness of the proposed method is investigated through case studies on the IEEE 30 and IEEE 118 test systems. [ABSTRACT FROM AUTHOR]

• Introducing a loss allocation method based on power tracking that can be implemented in any desired network topology, including loop and meshed networks. • Proposing a loss allocation method that can be properly implemented in transactive energy markets. • Determining the exact transacted energy between each supplier and consumer using optimal power flow methods. • Running the proposed method on different test systems and discuss its superiorities. Due to the expansion of power networks in response to the increase in total load demand, the complexity regarding power systems transmission networks' configuration has been increased. Similarly, with the advent of local energy markets and transactive energy concept, power distribution networks are undergoing a fundamental change. In this respect, numerous agents are transacting power within both distribution and transmission networks. Therefore, as more power is transacted among agents in different energy networks, power networks face higher power losses. Dealing with the financial outcomes of these losses, a general accurate yet fast method for loss allocation in power networks is of utmost importance. In response, this paper proposes a novel loss allocation framework based on the power tracking method that is applicable for any desired network topology within both transmission and distribution networks. In this regard, at first, a new method is proposed to obtain how the optimal scheduled generation of each production unit should be allocated to each specific load of the network. Then, it is obtained that how these transactions are flown in each line of the network. In the next step, the exact losses in each line resulted from distinct transactions between each pair of agents in the network are obtained. Finally, how each specific transaction contributes to the total losses of the network can be calculated. By implementing the proposed framework on a modified IEEE 14-bus test system and a 69-bus IEEE distribution network, the applicability and effectiveness of the proposed method is demonstrated by the numerical results. The results indicate that the proposed method can be implemented in any network and with any scale. [ABSTRACT FROM AUTHOR]

• The proposed method is insensitive to system operating conditions and fault location. It can be used for all faults LG, LL, LLG, and LLL. • The proposed single-ended impedance-based fault location numerical scheme offers higher fault location accuracy. • The proposed method is robust against faults in the load current, fault resistance, remote end infeed, line length, non-homogeneous network, measurement errors, capacitive current, and decaying DC components. • The proposed method can be easily implemented in IEDs along with the distance relay feature. Accurate fault location reduces the time and cost of an outage. Intelligent Electronic Devices (IEDs) commonly use impedance-based fault location techniques because they are simple and adaptable. This paper presents a novel single-ended impedance-based fault location algorithm. The proposed numerical method calculates the remote end source voltage during the fault in the transmission line. PSCAD/EMTDC-based test system model was developed to simulate the power system faults. The proposed methodology was put into practice using the MATLAB program. The algorithm has been tested on real-time fault data files COMTRADE (Common format for Transient Data Exchnge for Power Systems) taken from IEDs. Several complex tests were performed for single-circuit/parallel transmission lines to validate the proposed algorithm. The proposed single-ended impedance-based fault location numerical scheme offers higher fault location accuracy, and fault location accuracy is insensitive to fault resistance, load conditions, measurement errors, capacitive current, and decaying DC components. [ABSTRACT FROM AUTHOR]

• The penetration of DFIG wind farms into the power systems can lead to PSB of the distance protection malfunction. • DFIG wind farms lead to an impedance trajectory increase speed in the R-X plane of distance protection during power swing. • Adaptive adjustment of power swing blocking bands in concentric and blinder schemes improves distance protection security. • Power system dominant modes can be used to adjust the power swing blocking band. This article proposes a new approach to improve the security of transmission line protection by correctly detecting power swing when large-scale doubly-fed induction generator wind farms (DFIGWF) exist in the proximity of the relay. In the presence of large-scale DFIGWFs, following large disturbances, power swing may probably cause the distance protection to malfunction. This issue can also lead to widespread transmission line outage and cause instability in the power system. Therefore, a new approach is proposed to solve the challenge by adapting the power swing blocking (PSB) function in the distance protection relays and utilizing the dominant power system oscillation modes. Thus, related calculations are performed in a central module remotely connected to intelligent electronic devices (IEDs) for distance protection and stabilized against power swing. The calculation to adjust the PSB setting of the IEDs in the central module is based on the oscillation modes of the power system and the rate of change of impedance, which is influenced by the penetration rate of the DFIGWFs. Simulation studies have been done on two test systems and the results reveal that the proposed scheme significantly improves the security of distance protection against power swing under different DFIGWF intrusion conditions. [ABSTRACT FROM AUTHOR]

This paper presents an accuracy analysis from the application of techniques for the extraction of characteristic data from current and voltage signals in transmission line fault location based on traveling wave theory. The techniques used were the empirical mode decomposition and the variational mode decomposition associated with Teager energy operator, which helps to identify the instantaneous energy of the first intrinsic mode function. The simulation of the power system was carried out using the MATLAB/Simulink® software, for a test system consisting of a 200 km long transmission line between two Thevenin equivalents. Data is obtained from both terminals. The fault resistance was fixed at 100 Ω , but the incidence angle, the sampling rate and the fault location were varied for all fault types. The numerical and graphical results proved that the techniques can extract the characteristic data of the current and voltage signals and estimate the fault distance to the terminal with high accuracy, depending only on the sampling rate adopted. • Current and voltage signals are used for data extraction in fault location. • VMD and EMD with TEO are applied for AC transmission line fault location. • Accuracy analysis is performed for different sampling rate values. [ABSTRACT FROM AUTHOR]

In this paper, a new method for on-line inertia estimation is developed. The proposed method is based on the sliding window concept and uses ambient responses, i.e., responses obtained during the normal operation of the power system, to identify inertia constants of generation devices. The effectiveness of the developed method is evaluated by means of simulations on two benchmark power system models, namely the IEEE 9-Bus Test System and the IEEE 39-Bus Test System. The conducted analysis reveals that the proposed method can accurately identify inertia constants of conventional synchronous generators (SGs), converter-interfaced units operated as virtual SGs, and virtual power plants. The performance of the proposed method is also evaluated under noisy conditions, by performing Monte Carlo simulations. Finally, comparisons with conventional methods are performed, demonstrating the superior performance of the developed method. • A new method for the on-line tracking of inertia constants in developed. • The proposed method uses ambient data that are always available to system operators. • Inertia estimation of conventional synchronous generators (SGs). • Inertia estimation of virtual SGs and virtual power plants. • The proposed method presents higher accuracy compared to conventional approaches. [ABSTRACT FROM AUTHOR]

• A protection scheme is proposed for protecting SSSC-compensated double-circuit TLs utilizing synchronized measurements of PMUs. • A newly driven index is suggested as a relaying signal depending on the differential positive sequence active power transients with a unique setting for both single/double circuit operations. • The effectiveness of the proposed scheme is extensively tested on the two-area four-machine test system using MATLAB/SIMULINK environment. • The scheme has approved its dependability for fault detection irrespective of the fault conditions including inter-circuit faults, HIFs, evolving faults, and faults during current/voltage inversion. • Its proficiency to activate power swing blocking, de-blocking for faults occurring during swings, and the immunity against load changes, capacitor switching, typical ON/OFF switching, and external faults are confirmed. Static Synchronous Series Compensator (SSSC) allows dynamic control capabilities of transmitted power. Unfortunately, inserting SSSC in transmission lines (TLs) disturbs impedance-based distance relays as their directionality and reachability are affected by overreaching or underreaching. This paper proposes an approach for protecting double-circuit TLs compensated with SSSC. It relies on the centralized wide-area protection architecture to calculate a proposed driven index: the rate of change of positive sequence active power difference. Phasor measurement units (PMUs) at TL ends estimate voltage and current phasors to calculate the positive sequence active power at TL ends and send them to the system protection center that evaluates the index and gives the trip decision or not. Ensuring the sensitivity, dependability, and security of the approach is essential. So, the overall scheme integrates two other algorithms. One is based on the polarities of the incremental power at both ends to determine whether the fault is internal or external. The other evaluates the phase angle of the integrated impedance to deactivate the power swing-blocking function for fault detection. The scheme's effectiveness is validated comprehensively through extensive simulation tests for fault and system conditions. The results show that the proposed approach is fast, secure, selective, and reliable. [ABSTRACT FROM AUTHOR]

Phasor models have been widely used in short-circuit simulations, in which system operators verify the behaviour of the grid over thousands of different contingencies. However, it is still unclear if phasor models can still be used in fault studies in modern or future power grids dominated by renewable generation with power electronics and converters. Therefore, this paper analyses the suitability of phasor models to simulate short-circuit transients in grids with grid-following (GFL) and grid-forming (GFM) voltage-source converters (VSC). Phasor models of GFL and GFM were developed and tested in two test systems, one with 50% of converters in the generation mix and another powered 100% by converters. Asymmetrical and symmetrical faults were applied at different points of the systems and key variables were used to compare the phasor models against EMT models during the transients. The results showed that, despite neglecting transients in the grid, phasor models could be used in a preliminary stage of short-circuit studies as it was capable of tracking the steady-state value of almost all variables analysed. In this case, detailed EMT simulations, although necessary, would be used only at more advanced stages of the studies. • Suitability of phasor models to simulate short-circuit transients in low-inertia grids. • New grid-forming phasor models. • Suitability of phasor models to simulate grid-following and grid-forming converters. [ABSTRACT FROM AUTHOR]

Parallel operation of grid-forming inverters (GFMIs) is often achieved using droop characteristics implemented in converter controllers. Converters' recovery after a disturbance depends on the dynamics of each individual GFMI, and the droop characteristic alone is unable to ensure successful parallel operation. This work proposes a dynamic-phasor based modeling approach that enables eigenvalue analysis of multi-converter systems to identify the underlying factors that affect the interactions among parallel GFMIs. Network dynamics are included through dynamic phasor modeling of its elements, and controller dynamics are fully included. Modeling modularity is preserved, which allows to easily extend the test system to any topology of interest. The results presented for an exemplar two-converter system prove that the virtual inertia time-constant plays a significant role in exciting interactions, and that network and control system parameters are vital in extending the stability margins of the systems. EMT simulation results from PSCAD/EMTDC are included to verify the validity of the predictions of the dynamic-phasor based model. • A modeling platform based upon dynamic phasors is developed form small-signal modeling of multi-converter systems. • Using the developed platform interactions among grid-forming converters in low-inertia systems is studied. • Several factors contributing to interactions among grid-forming converters are identified. [ABSTRACT FROM AUTHOR]