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• Analysis of traction power supply system is conducted considering cross-bonding cable. • Model simplification method based on multiport network hybrid parameters is designed. • The calculation difference of loss before and after consideration is more than 10 %. • Cross-bonding cables should be set near the position with large train power. The urban rail transit traction power supply system adopts DC power supply. The upstream and downstream rails are generally connected by cross-bonding cables at intervals, so as to decrease the rail equivalent resistance and reduce the rail potential and loss. The existing modelling methods for power flow calculation do not consider the influence of cross-bonding cables due to the complexity of modelling, which causes some deviations in the calculation results. Hence, a modelling method for power flow calculation of urban rail transit traction power supply system considering cross-bonding cables is proposed in this paper. Firstly, the influence of cross-bonding cables on power flow model is analyzed. Subsequently, a model simplification method based on multiport network hybrid parameters is designed. Finally, power flow calculations considering cross-bonding cables are carried out with a metro line. The calculation results show that the calculation difference of traction network loss before and after consideration is more than 10 %. Moreover, this paper analyzes the influence law of the setting of cross-bonding cables on the power flow state, and gives some suggestions on the setting in actual engineering application. [ABSTRACT FROM AUTHOR]

• The proposed single-ended fault location framework fully considers the effect of partial coupling, without requiring measurements from the remote ends. • Within the proposed framework, two methods based on impedance line model and fully distributed line model are presented. • The effectiveness of the proposed methods is validated through many simulation analyses. The proposed methods demonstrate some robustness towards measurement noises and parameter errors. Accurate fault location technology can not only speed up fault search but also enhance the power supply reliability. This paper introduces a single-ended fault location framework for single line to ground faults, taking into account the effects of partially coupled lines. The proposed framework relies only on local measurements. Within the proposed framework, the two methods proposed in this paper are based on the impedance line model and the fully distributed parameter line model, respectively. The impedance model based fault location method does not require iteration and has no risk of divergence, while the method based on the fully distributed parameter model has higher accuracy. The estimated results of the impedance-based method can be used as the initial values of the solution of the distributed parameter model based method. The proposed methods are validated through a number of testing cases, encompassing various fault locations, resistances, and coupling ratios. [ABSTRACT FROM AUTHOR]

• A new control method for DER is suggested. • The proposed control method balances the load between feeders. • DER connects to feeder through SST. • DER-controlled circuit shared the load between two feeders like ring connection. • Voltage profiles are improved. The multi-purpose use of distributed energy resources (DER) can bring a lot of income to its owners. For example, the load imbalance of the radial feeders in the distribution network is an old problem that occurs due to the simple structure of the radial topology and the unidirectional power flow in traditional networks. With emerging DERs and the development of power electronic technology, previous concepts are changing continuously. This paper aims to balance the load between two feeders whilst, it yields better voltage profiles and more appropriate utilization of distribution feeders. This paper proposes a new control method for DERs (including PV panels plus battery storage) that makes the radial system pretends a ring topology properties. It is done with the help of a solid-state transformer (SST). The relationships of the DER current controller are formulated based on current passes through the ring connection. Case studies are carried out on improved IEEE 33-node and 13-node systems with DERs and SSTs. The results show that the suggested control method can simulate the real ring topology and operating objective namely, load balancing is reached. [ABSTRACT FROM AUTHOR]

Detection of cyber attacks in smart power distribution grids with unbalanced configurations poses challenges due to the inherent nonlinear nature of these uncertain and stochastic systems. It originates from the intermittent characteristics of the distributed energy resources (DERs) generation and load variations. Moreover, the unknown behavior of cyber attacks, especially false data injection attacks (FDIAs) in the distribution grids with complex temporal correlations and the limited amount of labeled data increases the vulnerability of the grids and imposes a high risk in the secure and reliable operation of the grids. To address these challenges, this paper proposes an unsupervised adversarial autoencoder (AAE) model to detect FDIAs in unbalanced power distribution grids integrated with DERs, i.e., PV systems and wind generation. The proposed method utilizes long short-term memory (LSTM) in the structure of the autoencoder to capture the temporal dependencies in the time-series measurements and leverages the power of generative adversarial networks (GANs) for better reconstruction of the input data. The advantage of the proposed data-driven model is that it can detect anomalous points for the system operation without reliance on abstract models or mathematical representations and data labels. To evaluate the efficacy of the approach, it is tested on IEEE 13-bus and 123-bus systems with historical meteorological data (wind speed, ambient temperature, and solar irradiance) as well as historical real-world load data under three types of data falsification functions. The comparison of the detection results of the proposed model with other data-driven methods verifies its superior performance in detecting cyber attacks in unbalanced power distribution grids. • An unsupervised neural network model combines the GANs and autoencoder for FDI attacks. • The proposed model utilizes the outputs of autoencoder and critic score for attack detection. • The proposed model is tested on unbalanced power distribution grids integrated with DERs. • Simulation results verify the model's superior performance compared to other data-driven models. [ABSTRACT FROM AUTHOR]

Stochastic fluctuations in power injections from distributed energy resources (DERs) combined with load variability can cause constraint violations (e.g., exceeded voltage limits) in electric distribution systems. To monitor grid operations, sensors are placed to measure important quantities such as the voltage magnitudes. In this paper, we consider a sensor placement problem which seeks to identify locations for installing sensors that can capture all possible violations of voltage magnitude limits. We formulate a bilevel optimization problem that minimizes the number of sensors and avoids false sensor alarms in the upper level while ensuring detection of any voltage violations in the lower level. This problem is challenging due to the nonlinearity of the power flow equations and the presence of binary variables. Accordingly, we employ recently developed conservative linear approximations of the power flow equations that overestimate or underestimate the voltage magnitudes. By replacing the nonlinear power flow equations with conservative linear approximations, we can ensure that the resulting sensor locations and thresholds are sufficient to identify any constraint violations. Additionally, we apply various problem reformulations to significantly improve computational tractability while simultaneously ensuring an appropriate placement of sensors. Lastly, we improve the quality of the results via an approximate gradient descent method that adjusts the sensor thresholds. We demonstrate the effectiveness of our proposed method for several test cases, including a system with multiple switching configurations. • Bilevel optimization minimizes number of sensors capturing all voltage violations. • Conservative linear approximations tackle power flow nonlinearities. • MILP reformulation proves tractable across various test cases. • Post-processing minimizes false alarms, validated through testing. [ABSTRACT FROM AUTHOR]

• The proposed data-driven control method eliminates the need for an accurate offline system model. • The presented control method incorporates a regularization term and introduces slack variables to effectively handle uncertainties and disturbances. • The FADMM method is utilized to enhance privacy and scalability by decomposing the centralized optimization problem into several sub-problems. The networked microgrid system (NMG) has become an effective alternative for integrating various types of distributed energy resources (DERs). However, because of the increasing share of DERs and high R/X ratio in the system, the uncertainty and variability of DERs' power generation may cause significant voltage violations in the system. To address these issues, this paper introduces a novel distributed data-driven voltage control strategy based on data-enabled predictive control (DeePC) to address voltage violations problems in the NMG. The DeePC algorithm uses only historical system trajectories, eliminating the need for parameter identification procedures of power system. Based on the system data model, the proposed controller coordinates MGs in the NMG in a distributed manner by employing a consensus version of the fast alternating direction method of the multiplier algorithm (FADMM), which achieves a better privacy and scalability. Simulation studies in a modified two-MG NMG demonstrate the effectiveness and superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

• The output power volatility of wind-photovoltaic and the operating characteristics of the electrolyzer is considered. • A capacity optimization method for off-grid RES-H2 production systems considering the load-follow-source mechanism is proposed. • A multi-objective optimization model with minimum cost, minimum energy storage capacity and optimal power supply efficiency was constructed. • An improved optimization algorithm based on two common algorithms is designed. Based on the uncertainty of the output of renewable energy such as wind and photovoltaic (PV), a capacity optimization allocation method considering the load-follow-source mechanism is proposed to solve the shortages of traditional methods, which is low in utilization rate of energy and low in economy. Firstly, considering the fluctuations of renewable energy sources (RES) and the operating characteristics of the electrolyzer, this paper proposes a capacity optimization method for off-grid hydrogen(H2) production system of renewable energy sources considering the load-follow-source operation mechanism. Then, combined with this mechanism, a capacity optimization allocation model is established, the objectives contain minimizing the levelized cost of hydrogen (LCOH), minimizing the capacity of energy storage, and optimizing the efficiency of power supply. Finally, an adaptive non-dominated sorting differential evolution algorithm (ANSDE) with external archiving is proposed to solve the established model. The calculation results show that the load-follow-source mechanism is effective for improving the economy of the system, and the proposed algorithm is high in efficiency and good in convergence comparing with traditional algorithms. [ABSTRACT FROM AUTHOR]

Utilizing Distributed Generators (DGs) and Energy Storage Systems (ESSs) enhances power system reliability, drawing significant research attention. However, these systems pose challenges, compelling scientists to explore optimization methods. Our paper presents an innovative solution, Parallel Multi-Objective Multi-Verse Optimization (PMOMVO), aimed at optimizing DGs and Battery Energy Storage Systems (BESSs) allocation. This optimization addresses voltage violations and operation costs, crucial concerns for system operators and consumers. By leveraging a parallel approach, PMOMVO significantly accelerates the optimization process. We compared its results with a base case scenario, demonstrating the superior efficiency of our parallel method. It not only enhances the optimization performance but also proves its efficacy by generating optimal solutions from the Pareto front set. This research showcases the benefits of PMOMVO, offering a faster, more efficient, and reliable way to optimize power systems, benefiting both operators and consumers. • Introduces a novel bi-level optimization approach for DG and BESS allocation and operation. • Proposing a multi-objective formulation to identify Pareto optimal solutions, offering a balance between voltage stability and cost-effectiveness. • Optimizes asset operation strategies, considering both peak and off-peak load times, enhancing resource utilization. • Proposes a parallel processing method based on modified MOMVO, significantly accelerating computations for large distribution systems problems. • Achieves a substantial improvement in the speed-up index, ensuring swift and effective DG and BESS allocation and operation in complex systems. [ABSTRACT FROM AUTHOR]

• Novel Methodology : Introduces a new double-ended terminal method for locating vegetation high impedance faults (VHIFs) in power distribution systems using the third harmonic component. • Efficiency and Cost-Effectiveness : This technique requires only two measurement terminals, significantly reducing the need and expense of extensive sensor deployment. • Overcomes Traditional Limitations : Unlike traditional methods, it eliminates the need for complex mathematical formulation models, improving accuracy in fault localization. • Demonstrated Accuracy : Simulation tests validate the method's effectiveness, achieving error rates below 1.6 %, highlighting its potential for real-world applications. • Practical Implications : Offers a proactive approach to power system protection, contributing to improved operation and maintenance of power distribution networks. Vegetation-related high-impedance faults (VHIFs) on overhead distribution systems can cause damage, maintenance issues, and even wildfires, impacting both utilities and ecosystems. Existing fault location techniques struggle to accurately locate VHIFs. In this paper, we propose a novel double-ended terminal location method based on the third harmonic component of the fault system. The proposed technique determines the distance of the VHIF by approximating the third harmonic voltage at the fault local, utilizing measurements from the remote terminal located at the far-end of the feeder. This method efficiently locates VHIFs with just two measurement terminals, cutting the need and cost of extensive sensor deployment. Moreover, the proposed method overcomes the limitations of traditional fault location techniques by using a third harmonic model of the faulted system, eliminating the need for complex mathematical models to approximate the fault behavior and voltage at the fault local. Simulation tests were conducted to validate the proposed method, demonstrating its effectiveness in accurately locating VHIFs. The technique achieved error rates below 1.6 %, making it a promising solution for real-world applications in power distribution systems. The ability to precisely locate VHIFs meets a proactive protection philosophy and contributes to improved power system protection and ensures uninterrupted power supply. [ABSTRACT FROM AUTHOR]

• Locational nodal pricing for distribution system based on DER value. • DER locational value can be determined to mitigate voltage and capacity violations. • Novel linear approach to determine DER value in distribution systems is introduced. • DER value in terms of dollars per kilowatt can provide locational value. • Scores for critical nodes emphasize those with the greatest value. Under most NEM policies, DER customers sell excess electricity at full retail price. Although this structure helped the widespread growth of DER, it is argued to subsidize DER at the expense of non-DER customers. In that regard, value-based compensation emerged, and as of 2022, at least 12 states have conducted studies to investigate alternative NEM compensation methods to inform new policy decisions. DER can provide various benefits to the distribution system, including energy, reliability, resilience, environmental, societal, and investment deferral. Each benefit has an individual value, and calculating these values is challenging. This paper presents a practical methodology to calculate the DER location value. The proposed approach utilizes established utility planning and reliability criteria. It analyzes the distribution system's current status, capturing any planning or reliability criteria violations, and determines the utility upgrade investment costs to remediate them. The proposed approach then determines the size, locational, and temporal profile of the DER that can be added to the distribution network and defer any of the utility upgrade investment costs, thus obtaining the value to the system and assigning a monetary value. The results provide a nodal distribution value of DER to the distribution system. [ABSTRACT FROM AUTHOR]

• A three-stage RCM framework is proposed for power distribution systems. • Critical component identification is carried out using BWM and TOPSIS. • The proposed ranking is benchmarked with a state-of-the-art SECA approach. • The optimal maintenance strategy is determined to minimize maintenance costs. • Cold-line, hot-line, and run-to-failure are considered for strategy determination. In this paper, a three-stage reliability-centered maintenance (RCM) framework for critical feeder identification, failure modes prioritization, and optimal maintenance strategy assignment is presented for the power distribution system. This three-stage methodology addresses a notable gap in the literature by incorporating these three stages together. The first stage ranks critical feeders using the BWM and TOPSIS methods. In the second stage, the failure modes are prioritized using feeder rank, severity, occurrence, and detection factors and are assigned a score representing their priority. Finally, in the third stage, a maintenance strategy assignment, formulated as a mixed-integer linear programming (MILP) optimization problem is proposed. The optimization problem considers three strategies, cold-line, hot-line, and run-to-failure (RTF), assigned to each failure mode. Besides, the possibility of implementing cold-line repairs overlapping with the upstream grid's scheduled outages and the availability of several maintenance crews are taken into account. The objective function is to minimize the total maintenance costs, which include operation, equipment, energy not supplied (ENS), expected energy not supplied (EENS), and future corrective maintenance costs. The proposed approach is implemented on a real distribution system. The results indicate that the proposed RCM framework leads to a 26.32 % reduction in the EENS compared to selecting the RTF strategy for all components. Besides, the proposed optimization-based method leads to a 29 % lower objective function than the business-as-usual maintenance planning, and the proposed three-stage RCM framework outperforms a previously published state-of-the-art method by decreasing the objective function and the EENS. [ABSTRACT FROM AUTHOR]

Although several approaches have been proposed in the literature to utilize inverter-based distributed energy resources (DERs) in the secondary frequency control (SFC), challenges related to practically implementing SFC with inverter-based DERs have not been considered. These challenges include response time of DERs, the communication environment, and emulation of the actual Automatic Generation Control (AGC). This paper develops and implements a coordinated operation and control for below the substation resources such as inverter-based DERs and a utility-scale battery energy storage system (USBESS) to participate in the secondary frequency control. A linearized optimization problem is formulated to simultaneously determine optimal setpoints of participating resources and satisfy AGC requests in real time for the secondary frequency control. To mimic the actual process of AGC, a hardware- and software-in-the-loop-based experimental setup is developed with the integration of real-time digital simulators (RTDS), a centralized controller at the substation, and gateways as IoT devices, which are commonly used in practice to interface DERs to control and monitoring systems. The controller remains in listening mode until it receives an AGC signal. When it receives an AGC signal, it optimally dispatches the USBESS and DERs and monitors the change in power flow at the substation. The controller iteratively dispatches the participating resources considering their response time until the AGC request is satisfied. The proposed control is implemented on an actual feeder configuration located in Las Vegas, Nevada, in collaboration with NV Energy—the largest public utility in Nevada. The results illustrate that USBESS and DERs can be coordinated and dispatched to satisfy AGC requests for SFC. • Novel linearized optimization-based secondary frequency controller • High fidelity prototype for practical implementation of AGC on real system • Combined hardware-and software-in-the-loop-based real-time laboratory setup for AGC [ABSTRACT FROM AUTHOR]

• The AC interference model of high-speed railway to buried pipeline is established. • Simulates the mechanism of dynamic AC interference caused by high-speed railway. • Calculates the influence of various factors on the AC interference of pipelines. The large-scale construction of high-speed railways and buried pipelines has led to the parallel or intersection of these lines over long distances in some areas, resulting in dynamic AC interference to buried pipelines. In this paper, the modeling method of the AC interference from high-speed railway employing auto-transformer (AT) power supply mode to the buried pipeline was investigated, and the accuracy of the modeling method was verified by the simulation calculation of the actual field case and the comparison with the field data. Through modeling and calculation, the influence of train running position, rail to ground transition resistance and crossing angle on AC interference of high-speed railway is discussed. Based on the above research, it is analyzed that the dynamic AC interference is caused by the change of current distribution and the train load current. The main mechanism of AC interference caused by high-speed railway operation on nearby pipelines is inductive coupling. Especially when the rail to ground transition resistance is less than 50 Ω km, due to the unbalanced distribution of power supply circuit current, the peak AC interference voltage appears on pipeline where the train is located. [ABSTRACT FROM AUTHOR]

• Proposal of SOP-based SSM, IPM and MCM considering the requirements of load static voltage characteristics. • Formulation of the different SOP-based DSR models as mixed integer nonlinear programming problems. • Convexification of the original optimization model with a static voltage load model. • SOP-based MCM outperforms the others in continuously supplying critical loads. Soft open points (SOPs) can perform load shifting and voltage improvement, and are critical to improving distribution service restoration (DSR) during power outages. Although multiple DSR strategies utilizing local resources have been reported, their effectiveness has not been sufficiently studied. To solve this problem and utilize the flexibility of SOP, a comparative study of different strategies for SOP-based DSR is presented in this paper. First, various SOP-based DSR models, including single-source, single-island model (SSM), islanding partition model (IPM) and multi-source collaborative model (MCM), are proposed and formulated as mixed-integer nonlinear programming (MINLP) problems, incorporating static voltage characteristics of loads. Second, to enhance the solution efficiency, mixed-integer second order cone programming is introduced to convert the MINLP problems into easily solvable convex optimization problems. A restorative index is defined to evaluate the effectiveness of various SOP-based DSR strategies. Finally, a comparative simulation analysis of the proposed models on the IEEE 33-bus system illustrates that SOP-based MCM achieves an 94 % power output for distributed energy resources, while exhibiting the lowest RI for the total loads, standing at just 9.5 %. Furthermore, the RI for critical loads consistently remains at 0, demonstrating the superiority of SOP-based MCM in comparison to other strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

• A chance-constrained power balance model is introduced for the IES fault recovery. • The IES fault recovery strategy is proposed considering natural gas delay. • The developed model is converted into a solvable second-order cone problem. After the integrated energy system (IES) encounters extreme disasters, the uncertainty of renewable energy may lead to the imbalance of power supply and demand. This makes the IES fault recovery strategy very complicated. Considering the influence of the electric-gas coupling characteristic of natural gas delay, this paper proposes a fault recovery strategy, including the load recovery and economic efficiency of the operation of the IES. In the recovery stage, a chance-constrained power balance model is employed to solve the power supply and demand imbalance caused by uncertainty. Next, the chance-constrained power balance model is processed via distributionally robust optimization, and it is reformulated into a second-order cone programming (SCOP) problem by dual transformation and conditional value-at-risk approximation. To deal with nonlinear terms, the piecewise linearization method is used to model the load recovery result, renewable energy output, and total operation cost of each period during the fault. Finally, the effectiveness of the proposed strategy is verified by an IES composed of an IEEE 39-node electricity subsystem, a 20-node natural gas subsystem, and a 6-node thermal subsystem. [ABSTRACT FROM AUTHOR]

• This paper shows how artificial neural networks can be used to determine overvoltages in power system. • The primary contribution of this paper is a novel method based on artificial neural networks for classification of overvoltages in power systems. • This approach consists of a few steps, as follows: • Modelling of power system components for transient studies in EMTP. This means developing two different models, one for switching overvoltages, and the other one for fast front overvoltages. • Creating and deploying JavaScript to automate the simulation process and parametric analysis. • Overvoltage feature extraction from generated overvoltage waveshape using harmonic analysis in MATLAB. • Overvoltage classification using neural network in MATLAB. Numerous factors, including sudden load reductions, switching transient loads, lightning strikes, and malfunctions of control devices, can result in overvoltage. Overvoltage can harm associated power supply components and result in insulation failure, electronic component damage, flashovers, etc. A machine learning technique called a "neural network" estimates computation results that depend on a lot of inputs. For a variety of reasons, neural networks have recently been used to manage and optimize the power system. This paper presents an artificial neural network (ANN)-based approach to determining overvoltages in power systems. To simulate overvoltages, many simulations were performed in Electromagnetic Transient Program (EMTP). Variations of parameters of interest that have an influence on overvoltages were made using JavaScript that was connected to EMTP models. The extraction of characteristic parameters from overvoltage waveshape is a demanding task, and it was conducted in MATLAB, as was a overvoltage classification methodology based on neural networks. Results were presented and discussed. [ABSTRACT FROM AUTHOR]

Highlights • Control of parallel-connected voltage source converters. • Voltage control loop affects synchronous reference frame inverter output impedance. • Mathematical modeling of error in power sharing between parallel inverters. • Designing dq virtual resistive, inductive, and capacitive impedances. • Experiments validate resistive, inductive, and capacitive droop control in dq-RF. Abstract This paper investigates dq -reference-frame (dq -RF) self and cross-coupling output impedances of the islanded voltage source converter (VSC), by considering the controller impacts. The dq -RF impedances for the closed-loop system are designed to exhibit the desired resistive, inductive, or capacitive characteristics, and are employed in the power control of VSC. The effects of these impedances and connecting lines impedances on the power control of islanded parallel connected VSCs, for different impedance characteristics, are also studied. It is shown in this paper that the unbalanced impedance significantly affects the performance and power control of these parallel converters. Besides, virtual impedance based active and reactive power control of the parallel converters in the dq -RF, for resistive, inductive, and capacitive cases, are designed and implemented. The numerical and experimental results verify the analysis presented in this paper about the dq -output impedance and the virtual impedance based power sharing control. [ABSTRACT FROM AUTHOR]

Passive distribution networks are rapidly transforming to active networks due to ever growing penetration of mainly renewable distributed energy resources. The integration of these resources has positive impact from environmental perspective but their penetration has raised serious issues on secure and reliable operation of a network, owing to their intermittent and not dispatchable output. To maintain an optimal operation of a network, extensive research studies have been carried out under the theme of network management. This paper discusses the concept of losses management, which falls under the same theme, in active distribution networks. The methods related to modelling of such systems and end-users, numerical tools required for system analysis, active network management schemes for losses minimization and fair losses allocation to passive and active consumers are reported and investigated. Therefore, the aim of this paper is to provide a concise yet comprehensive comparison of the most recently proposed losses management approaches and strategies. [ABSTRACT FROM AUTHOR]

This paper proposes a frequency-adaptable method for computing the phase associated with the positive sequence components from the measured grid voltages. It relies on a simple procedure in which the positive sequence is separated from the negative one through a suitable decomposition of the synchronous voltage vector onto the stationary αβ frame. The procedure performance is enhanced by means of an one-cycle Fourier filter. The positive sequence voltages are then handled by a synchronous-reference frame phase-locked loop (SRF-PLL) algorithm. The structure composed of the positive-sequence estimator and the SRF-PLL is called a one cycle Fourier PLL (OCF-PLL). The OCF-PLL is robust against voltage harmonic distortions due to the OCF frequency-response characteristic. The frequency adaptability is obtained through the series connection of two OCF-PLL blocks. In the first block the fundamental frequency is computed by the SRF-PLL. This frequency is supplied to the second OCF-PLL block which computes the positive phase of the original measured voltages. Also, in this paper, the frequency adaptability is mathematically demonstrated. The method is initially evaluated by means of simulated voltages. Then, an experimental setup has been designed, in which the proposed method has been implemented in a digital signal processor (DSP) and tested on voltages produced by a programmable power supply able to emulate distorted and unbalanced voltages. The results prove the technique efficacy. [ABSTRACT FROM AUTHOR]

• A fast and non spurious IDT using a modal voltage signal has been presented. The islanding/non-islanding condition has been detected without directly impacting the system operation. • The proposed method is well competent in ascertaining the islanding below 2 s in the case of a zero power deficit. • The analysis of NDZ of the proposed VMD based IDT is also carried out using anti-islanding requirements specified by UL 1741 Std. • The proposed IDT is applicable for all types of DG. • A real-time simulation and validation of the proposed method has been carried out on the RTDS/RSCAD and dSPACE platform to reaffirm its efficacy and feasibility on real world problems. Ascertaining unintentional islanding conditions is a challenging task for power utility operators due to the pervasive penetration of Distributed Energy Resources (DER). The presence of DER has a significant adverse impact on islanding detection schemes for various types of Distributed Generators (DG) and inverters. This paper addresses the passive islanding detection mechanism based on the mode energy index using Variational Mode Decomposition (VMD) in an Active Distribution Network (ADN). The prime attributes of VMD are noise immunity, robustness, and non-recursive signal processing, making it more promising and competent for signal decomposition than other extant signal processing methods. In this paper, three-phase instantaneous voltages at the target DG end have been acquired to compute modal voltage signals, and VMD has been utilized to decompose the obtained signals into four modes. Thereupon, the energy was calculated for the selected mode. In the context of threshold selection, a series of simulation is carried out for various islanding and non-islanding events. The energy threshold is then selected by implementing "Otsu thresholding method". The estimated energy index has ultimately been utilized as an islanding detection indicator. In this work, two different test systems have been modelled and simulated using EMTDC/PSCAD. The simulation result outcomes asserted that the developed approach effectively ascertains the islanding and non-islanding events. Furthermore, the proposed islanding detection technique has been validated using the Real-Time Digital Simulator (RTDS) and dSPACE MicroLabBox based co-simulation platform. [ABSTRACT FROM AUTHOR]

• In this study, an emergency decision-making system framework based on big data platform is designed, which is combined with the actual application scenario after extreme disasters. It is an important tool to obtain the fault information through data-driven method, and this paper only conducts relevant researches from the perspective of theoretical analysis and functional design. • In this paper, a two-stage MILP based co-optimization model of fault repair and service restoration which aims to maximize the economic benefit of distribution network, and to minimize the traveling time of repair crews in transportation network is developed based on the previous work of fault information acquisition. Optimal dispatching of repair crews after an extreme disaster is proposed considering real-time traffic conditions, traveling time and emergency resources constraints. • At the same time, considering the time-varying operation status of the distribution system and the cascading coupling of fault repair and power supply restoration, the modeling and solution time dimensions are taken into account, and the power supply restoration plan for subsequent periods is revised on a rolling basis according to the repair progress. In this paper, a fault repair and service restoration framework in response to extreme disasters is proposed from the perspective of combined data-driven and knowledge-driven. Firstly, theoretical analysis on fault information acquisition is conducted and an emergency decision-making system based on big data platform is designed. Secondly, a two-stage mixed integer linear programming (MILP) based mechanism model is propounded. The first stage is to cluster repair tasks considering geographical distance and relevant constraints. The second stage is to solve the co-optimization problem of fault repair and service restoration, which is formulated as a bi-level model. The dispatching of repair crews is optimized in lower-level model, and the network reconfiguration plan for maximizing economic benefits is proposed in upper-level model. The service restoration plans for subsequent periods are revised dynamically according to the process of repair work. Finally, the PG&E69-bus system is taken as an example to verify the effectiveness of the model. [ABSTRACT FROM AUTHOR]

Ferroresonance in single-phase, line-to-line connected transformers in an ungrounded distribution system with delta-connected capacitors is possible but has not been reported in recent literature. In this paper, a high voltage event that actually occurred in an ungrounded distribution network with multiple distribution transformers has been simulated for lessons learned. The hypothesis was that ferroresonance was the cause of the overvoltage event in the network after a single-phase event led to sustained voltages of 1.45 p.u. Simulations were performed and ferroresonance was found to be the possible cause for the overvoltages. One of the prevention solutions found to avoid the overvoltages was to balance the loads on the three phases. The increased deployment of CVR/VVO strategies leads to circuit configurations similar to that studied in this paper and could lead to an increased likelihood of ferroresonance, if it is not fully understood and addressed. The impact of additional single-phase solar inverters on the low voltage side of the transformers was also studied. The results obtained show that the effective loading of the transformers, which is the difference in the actual load connected and the output from the DER, proved to be the deciding factor for initiation of ferroresonance in such networks. • Overvoltage event observed on a utility's ungrounded distribution system. • Ferroresonance was the cause based on electromagnetic transient simulations. • Distributed Energy Resources (DER) added to study impact on ferroresonance. • With DER connected, overvoltage observed at higher values of transformer loading. • Phase balancing and capacitor bank switching avoided overvoltage event. [ABSTRACT FROM AUTHOR]

• This paper provides a comprehensive review on sub synchronous oscillation (SSO) in large asynchronous machines connected to high voltage transmission lines with thyristor controlled series capacitor (TCSC). • The SSO occurrence is analysed on the simulation of a 250 MW DFIM based on a hydropower system with a series-compensated transmission line. • To validate the simulation results, a scaled-down laboratory prototype has experimented with a 2.2 kW DFIG system. • Further, the state-of-the-art SSO reduction methods are discussed with their benefits and drawbacks. Hydropower is a leading energy resource amongst the world's renewable energy capacities. According to the International Hydropower Association Status Report 2018, hydropower contributes 16.4% of total electricity production. To achieve proficient generation in the arena of the hydropower sector, a widespread design with recent trends and developments in technology is obligatory. Asynchronous machines are now extensively used in non-conventional energy resources due to their reduced cost and size, ruggedness in performance, ease of maintenance, partly rated power converter interface, and intrinsic short-circuit and overload protection. Asynchronous machines of large capacity (e.g. 250 MW) need further research to address redundancy in converter control circuits and also to identify the amount of compensation in transmission lines in view of variable speed of operation. This paper provides a comprehensive review on Sub Synchronous Oscillation (SSO) in large asynchronous machines connected to high voltage transmission lines with Thyristor Controlled Series Capacitor (TCSC). Methodologies used for SSO analysis are discussed. A simulation of a 250 MW doubly fed induction machine (DFIM) based on a hydropower system with a series-compensated transmission line is carried out in MATLAB/Simulink. A hardware prototype of a 2.2 kW DFIM system is used to test the results. Further, the state-of-the-art SSO reduction methods are discussed with their benefits and drawbacks. [ABSTRACT FROM AUTHOR]

• The quantitative expression of the current phase difference between both sides of the PV transmission line for faults with transition resistance is analyzed. • A Dice similarity coefficient-based pilot protection method for 500 kV transmission lines is proposed, considering the angle difference and magnitude difference between currents on both sides of the line. • The proposed method has a higher sensitivity than existing protection methods and performs better to transition resistance. • The effectiveness and accuracy of the proposed method under different fault locations, fault types, transition resistances, fault inception angles, line lengths, PV power supply capacities, have been verified by simulation and field data tests. Due to the shortage of fossil fuel resources and energy transformation efforts, the installed capacity of photovoltaic (PV) power supplies has been steadily increasing, resulting in the problem of low sensitivity for PV transmission line segregated-phase current ratio differential protection. Furthermore, there are increasing cases of large-scale gigawatt-level PV power supply integrated into the 500kV grid, bringing new challenges to the security and stability of the grid. In this paper, according to the fault characteristics of photovoltaic power supply, the current phase characteristics on both sides of the line are quantitatively analyzed during internal faults with transition resistance, and then the phase and amplitude differences of the currents on both sides of the line are used to propose a Dice similarity coefficient-based pilot protection method for photovoltaic transmission lines. PSCAD/EMTDC simulation and field data test results show the proposed method can accurately identify internal faults under the conditions of different fault locations, fault types, transition resistances, fault inception angles, line lengths, PV power supply capacity, and levels of noise. The method also performs well with CT saturation, simultaneous faults, evolving faults, and channel asymmetry. Additionally, the proposed method has a fast operation speed and a great performance to transition resistance. [ABSTRACT FROM AUTHOR]

Residential communities are increasingly adopting renewable energy sources (RES) to minimize energy consumption costs. However, these RES are weather-dependent and uncertain, posing challenges to ensuring reliable operations. Addressing the uncertainties in power supply management becomes a critical research question. Energy storage systems play a crucial role in providing battery-powered supply for residential loads under uncertain conditions. The operation of microgrids is directly influenced by uncertainties. This paper proposes data-driven-based net load uncertainty quantification fusion mechanisms for cloud-based energy storage management with renewable energy integration. Firstly, a fusion model is developed using SVR, LSTM, and CNN-GRU algorithms to estimate day-ahead load and PV power forecasting errors. After that, two mechanisms are proposed to determine the day-ahead net load error. In the first mechanism, the net load error is directly forecasted, while in the second mechanism, it is derived from the forecast errors of load and PV power. The net error analysis is conducted with a statistical mean and standard deviation, resulting in different uncertainty-bound confidence intervals around the forecasted value. Subsequently, the cloud energy storage system operation cost is calculated with the best uncertainty quantification mechanism for two different case studies. This approach allows for better management of uncertainties in energy storage systems and enables more informed decision-making under varying conditions. • Learning-based fusion algorithm for net load forecasting. • Develop uncertainty mechanism for uncertainty quantification. • Economic assessment of cloud energy storage. [ABSTRACT FROM AUTHOR]

• Consensus-based distributed control methods in DC microgrids are investigated. • Recent literature on consensus-based distributed secondary control is reviewed. • Various types of consensus algorithms are compared through simulations. • Insights into future research directions are provided. Secondary control (SC) is the middle layer of the well-known hierarchical control structure, which plays an essential role in maintaining the desired operation of microgrids (MGs). Generally, SC layer is divided into three categories of decentralized, distributed, and centralized control schemes. Among them, distributed control strategy is superior to the decentralized and centralized ones in terms of effectiveness, reliability, and scalability. Accordingly, this paper presents a comprehensive overview on distributed secondary control (DSC) schemes in DC MGs, specifically focusing on consensus-based cooperative DSC schemes. In this overview, the consensus-based DSC methods are classified into five groups of dynamic consensus, leader-follower consensus, finite-time consensus, PI consensus, and event-triggered consensus. These consensus-based DSC strategies are investigated, reviewed, and assessed in detail. Furthermore, different case studies are provided to compare the performance and merits of different consensus-based cooperative DSC structures using time-domain simulations in MATLAB/Simulink environment. Key findings are provided, and finally, challenges ahead of future research are highlighted. [ABSTRACT FROM AUTHOR]

The wide-area damping controller (WADC) is a centralized measurement-based controller to maintain small-signal stability in interconnected power systems. Due to its centralized structure, a communication network is needed to send the control signal to the actuators. A communication network has parameters such as time delay, packet dropout, and bandwidth limitations, which worsen with communication network congestion. Therefore, reducing the communication network usage can help to deal with them. In this paper, an event-triggered wide-area damping controller (ETWADC) is proposed to tackle this challenge and additionally save energy for the resources. In this approach, first, the inter-area oscillation modes of the system are determined through the fast Fourier transform (FFT). Next, based on system identification using measurement data, a multi-input multi-output (MIMO) model for the interconnected power system is obtained. Then, by applying the residue analysis, the optimal control loop is selected. Finally, an ETWADC is designed to dampen the inter-area oscillation of this optimal loop. To evaluate the proposed controller, two case studies i.e. two-area system and IEEE 39-bus system in the Matlab/Simulink platform have been studied. Using the proposed controller, the utilization of the communication network to send the control signal is significantly reduced, as shown through simulation results. • Optimal performance achieved through the implementation of the LQR method. • Integrating an optimal control loop to reduce communication requirements. • Introducing an event mechanism in the path from the controller to the actuator. • Ensuring asymptotical stability. • Provision of theoretical proof of the Zeno-free property. [ABSTRACT FROM AUTHOR]

• A novel stochastic-robust approach is developed for energy communities. • Individual and collective assets are considered and analysed. • The problem is solved using a novel three-stage procedure. • Operating cost is incremented 77$ when the degree of robustness grows. • Collective storage systems help to reduce unserved demand and wasted generation. This paper presents an extended model for aggregation of operational settings of droop-controlled Distributed Energy Resources (DERs) in Microgrid (MG) planning, thus deriving in a novel problem named Optimal Siting, Sizing and Setting (OSSS) of DERs. The proposed approach precisely deals with the power flow formulation for autonomous MG as an essential constraint for accurate results. Furthermore, the proposed OSSS model considers the frequency and voltage dependence characteristic of loads. The problem casts in multi-objective formulation to consider different technical, power quality and controlling aspects. This will help the designer to provide efficient decision for allocation of DERs. The effects of realistic load model as well as power sharing error index are elaborately investigated in simulation results. The model is thus further validated and its usefulness demonstrated. Finally, the performance of multi-objective OSSS model is verified by comparing the results with the previous simplified models presented in the recently published literatures. [ABSTRACT FROM AUTHOR]

In the modern-day distribution network, converter-based distributed generators (DGs) are increasingly employed to supply power from renewables. One of the prominent issues in the use of decentralized control for this purpose is the inaccurate real power sharing amongst these DGs due to the voltage drops associated with the feeder/line impedances. The use of virtual voltage drop in the controller of these DGs is a popular approach to mitigate the impedance mismatch effects. This impedance shaping technique demonstrates improved power sharing, however, the selection of an appropriate value for it is a big challenge. This paper elaborates upon a droop-based VI shaping technique for converter-based DG through a non-linear variation for islanded networks which are predominantly resistive. Performance evaluation of this technique for a wide variety of loads including balanced (constant impedance), constant power, unbalanced, non-linear, and induction motor loads is done through detailed simulations. The proposed method is also tested for a mesh network. DG plug-and-play functionality performance and load variation on a modified 13-bus network is verified using the proposed control scheme. The range for control parameters for stability is verified through modeling and eigen value analysis. Experimental validation on a laboratory setup for the same has also been presented. • A non-linear relation between the output current and virtual impedance values is proposed to improve the proportional power-sharing of the DGs. • Improved proportional power-sharing is achieved by keeping the PCC voltage under acceptable limits and the non-linear parameter is also adjusted automatically. • The scheme idea is designed for low-voltage islanded systems and isolated systems where the DGs operate in inverse drop control. [ABSTRACT FROM AUTHOR]

• The proposed method derives a non-iterative holomorphic embedding load flow method (HELM) for area interchange control in the multi-area interconnected system. • Based on the participation factor of each regulating bus, all of the generators can take part in the adjustment even though only one variable is added for each control area. • The proposed approach is compared with the conventional NR approach by studying cases on the 4-bus system, IEEE 118-bus system, the Polish 3012-bus system and 25,000-bus system under different operating conditions. • The results show that the proposed approach is superior to the conventional NR approach in terms of computation efficiency in small and midsize system. This paper proposes a new approach to realize area interchange control based on the non-iterative holomorphic embedding load flow method (HELM) in a multi-area interconnected system. In this approach, the area interchange equations are firstly incorporated into the power flow equations and then the extended power flow equations are embedded by holomorphic functions. Furthermore, the adjustable generators participating in automatic generation control are considered as active power resources to control interchange among areas. A participation factor matrix is integrated into the HELM to distribute active power injections among multiple adjustable generators. To evaluate the performance of the proposed approach, comparative studies were conducted on various power systems, including the 4-bus system, IEEE 118-bus system, Polish 3012-bus system, and 25,000-bus system, under diverse operating conditions. The obtained results demonstrate the effectiveness and computational efficiency of the proposed non-iterative area interchange formulation in small and midsize power systems, in comparison with traditional iterative methods such as Newton's method. However, for large-scale systems, further improvements in computational efficiency and convergence performance are required. [ABSTRACT FROM AUTHOR]

• The XGBoost junction temperature calculation model is used to improve the junction temperature calculation efficiency and reduce the influence of IGBT parameter deviation on the junction temperature calculation accuracy. • A data-driven IGBT reliability evaluation method is proposed to realize the quantitative evaluation of IGBT reliability in PV inverter when photovoltaic power supply participates in reactive voltage regulation in distribution network. • The voltage/var optimization model of the distribution network considering the reliability of the PV inverter is established, which significantly improves the reliability, minimum lifetime and average lifetime of the PV inverter. • DDPG algorithm is used to realize the voltage/var optimization of distribution network considering the reliability of the PV inverter, which effectively improves the solution speed of the voltage/var optimization model and lays a foundation for realizing online optimal voltage/var control. Fully exploiting the reactive power support capability of the distributed photovoltaic power supply is helpful to solve the problems of voltage fluctuation, voltage overlimit and new energy consumption in the distribution network. However, the reactive power output of the photovoltaic power supply will seriously threaten the reliable operation of the photovoltaic inverter. Therefore, this paper proposes a data-driven voltage-reactive optimization control strategy considering the reliability of the photovoltaic inverter. Firstly, the data-driven model is used to calculate the insulated gate bipolar transistor junction temperature, which improves the calculation efficiency of the insulated gate bipolar transistor junction temperature and reduces the dependence of the evaluation accuracy on the insulated gate bipolar transistor parameters. Then, the voltage-reactive optimization control model of the distribution network considering the reliability of the photovoltaic inverter is established, and the average junction temperature and junction temperature fluctuation of the insulated gate bipolar transistor are introduced into the model optimization goal. The optimization model is transformed into the reinforcement learning task, and then the deep deterministic policy gradient algorithm is used to realize voltage-reactive control. According to the simulation of IEEE 33 node distribution system, the proposed strategy can increase the minimum and average insulated gate bipolar transistor lifetime of all nodes by 6 years and 4 years. At the same time, it can reduce the minimum and average levelized cost of energy of all nodes by 0.1095 $/W and 0.0318 $/W. [ABSTRACT FROM AUTHOR]

• The planning scenarios for island microgrids are categorized into three types, and selection methods are proposed for each type of scenario. • Establishing the unified GES model, which includes transferable load, reducible load, P2G-GS-MT, and energy storage. • Considering the impact of typhoons and utilizing GES, a planning model for pelagic island microgrids is developed, and a solution method for this model is presented. Stand-alone microgrid system consist of hybrid wind/photovoltaic/energy storage is one of the effective approaches to solve the problem for future pelagic island power supply. Also, the frequent typhoons have brought serious impact to the pelagic island microgrids. In this context, a multi-scenario planning model for pelagic island microgrid with generalized energy storage (GES) is proposed to address the issues of high-impact, low-probability typhoon events and insufficient flexibility in low-impact, high-probability situations. Given the impact of typhoons, the planning scenarios of island microgrids are divided into regular, typhoon and typhoon early warning scenarios. Meanwhile, the selection method for each type of scenario is given. In addition, this paper establishes the unified GES model which includes power to gas-gas storage-micro gas turbine (P2G-GS-MT), transferable loads, reducible loads, and electric energy storage. The proposed methodology has been validated on an enhanced microgrid, resulting in a cost reduction of 11.9% compared to traditional method. The results demonstrate that this approach reduces the planning capacity of equipment, cost reduction, and ensure uninterrupted power supply to important loads even during typhoon conditions. [ABSTRACT FROM AUTHOR]

• Proposed two new indicators for distribution network vulnerability analysis. • Applied deep learning and Internet of Things to vulnerability analysis. • Applied dynamic thermal rating to vulnerability analysis. The integration of distributed energy resources and electric vehicles has made the distribution network more complex and uncertain. In response to these challenges, researchers have proposed various evaluation methods and indicators to uncover the vulnerability of the distribution network and provide improvement measures. Firstly, this review categorizes factors influencing the vulnerability of distribution networks into internal and external factors. Moreover, the three research objects of vulnerability analysis are elucidated. Secondly, the paper summarizes the evaluation criteria for vulnerability and discusses existing vulnerability assessment methods and indicators. Through research analysis, it is proposed that the remaining-life of lithium-ion batteries and the Expected Energy Not Supplied (EENS) can be used for the vulnerability analysis of distribution networks. Additionally, this research investigates the utilization of Internet of Things (IoT) technology and deep learning algorithms, such as Long Short-Term Memory (LSTM), for vulnerability analysis. The objective is to facilitate data collection and predict the remaining-life of lithium-ion batteries. The findings of our studies demonstrate that by incorporating the proposed evaluation index and evaluation method, the implementation of Dynamic Thermal Rating (DTR) technology can improve EENS evaluation, which also enables real-time monitoring and assessment of vulnerable components and potential failure risks. [ABSTRACT FROM AUTHOR]

• A multiple criteria analysis method is proposed to compare renewable energy and traditional solutions for off-grid island power supply. • Life cycle cost is used to build the economic model. • The fuzzy analytic hierarchy process is used to quantify the risk level. • A simulation platform is built to obtain the energy utilization. • Applied to the actual project to verify the feasibility of the method. Renewable energy microgrids are a new option for powering remote islands. To explore the feasibility of constructing island microgrid in China, based on the failed Dongfushan Island Demonstration Microgrid Project caused by equipment failure, low economic benefits, low residents' satisfaction, and poor power supply stability, this paper compares two power supply methods, microgrid and submarine cable. A systematic multiple criteria analysis method is established to compare these two methods, including economic analysis, risk assessment, energy spilled and energy shortage. Net present value and the life-cycle cost method are used to establish the economic cost model. Fuzzy analytic hierarchy process is used to establish the risk assessment model. Additionally, the simulation using PVsyst software is used to calculate the energy spilled and energy shortage. Furthermore, future trends are predicted with data to provide suggestions for decision-makers. Multiple criteria analysis results showed that energy spilled and shortages are inevitable for the use of microgrid on seasonally tourist islands like Dongfushan Island, with energy spilled and shortages rate as high as 50.11% and 37.57% in the worst case. The microgrid risk level is relatively low risk, higher than the lowest risk level for submarine cables. At full capacity, the cost of microgrid (34.03 million yuan) is comparable to submarine cables (30.31 million yuan), making the latter more suitable for power supply due to its better reliability. [Display omitted] [ABSTRACT FROM AUTHOR]

• To detect islanding, the 4th harmonic is injected into the output current. • A modified Goertzel filter is employed to measure the harmonics of voltage. • The method is robust to variation of load quality factor and resonant frequency. • The impact of reactive power on frequency after islanding is compensated. • The method is fast and detects islanding within two cycles of fundamental frequency. Islanding occurs when a utility-interactive distributed generator (DG) is disconnected from the utility grid and continues to supply power to local loads. This condition has several consequences including damage to the equipment and personnel safety risks. Therefore, it is required by utility interconnection standards for the DG to stop energizing local loads in the case of islanding. In this paper, an active islanding detection method (IDM) based on injecting a disturbance into the phase-locked loop (PLL) of a grid-connected photovoltaic (PV) inverter and monitoring the harmonic components of the point of common coupling (PCC) is proposed. A modified Goertzel algorithm is utilized to detect the injected harmonic which is effective for a wide range of load conditions in terms of load quality factor, resonant frequency, and reactive power. The simulation results in MATLAB/Simulink show that the proposed technique is fast with minimum side effects on power quality features such as output current total harmonic distortion (THD). This method is implemented on a single phase 5 kW grid-tied PV inverter and is tested experimentally. The experimental results verify that the proposed technique is fast with zero non-detection zone (NDZ) which is effective for a variety of load conditions. [ABSTRACT FROM AUTHOR]

• Random-fuzzy multi-objective optimal power flow. • Transmission and distribution interaction. • Security region constraints. In order to deal with the static voltage stability region problem of the power system caused by the penetration of distributed energy resources, this paper presents an interactive random-fuzzy optimal power flow method for transmission-distribution network considering security region constraints. Firstly, based on the random-fuzzy theory, the output of wind power and multi-energy coupling energy hub connected to transmission-distribution network are obtained. On this basis, the security region model of transmission-distribution network is established. As the interaction and cooperation between multiple distribution networks and transmission network throughout the system are described, the global random-fuzzy model of transmission-distribution interaction is established. Then, the security domain opportunity constraints are incorporated into the multi-objective optimization model of transmission-distribution network. Finally, based on the improved IEEE30 bus transmission system and IEEE33 bus distribution system, the power flow of transmission-distribution interactive network under the proposed model is calculated. The simulation results validate the effectiveness of the proposed model and algorithm. The safe operation distance of the power grid system can be improved and the active power network loss and power generation cost can be reduced. [ABSTRACT FROM AUTHOR]

With the development of virtual synchronous generators (VSG), microgrids can choose a synchronous generator (SG) or a virtual synchronous generator (VSG) as the main power supply of an isolated island system. The governor of a synchronous generator and the active power control loop of a virtual synchronous generator may cause the transient power angle instability of the system, while the excitation device and reactive power control loop may cause the transient voltage instability. At present, there have been many studies on these two aspects. However, when a synchronous generator and a virtual synchronous generator are used as the main power sources to supply power to the isolated island system, the mutual coupling between the synchronous generator and the virtual synchronous generator may cause transient power angle and voltage instability. At present, there is little research in this field. Therefore, this paper focuses on the influence of the parallel mutual coupling of synchronous generator and virtual synchronous generator on the system stability, derives the mutual coupling model of a parallel system, it is also revealed that the coupling relationship between the SG and VSG parallel systems will produce a positive feedback mechanism that will be constantly amplified, which will greatly affect the system's stability. At the same time, the influence of coupling on the stability of a parallel system is carefully analyzed using large signal analysis, and the corresponding coupling suppression strategy and adaptive inertia control (AIC) is proposed. Finally, the correctness and feasibility of the proposed method are verified by time-domain simulation, and the experimental results are analyzed. [ABSTRACT FROM AUTHOR]

• Novel protection technique for microgrids with inverter-based resources. • Effective both in grid-connected and islanded modes of operation unlike other relays such as differential relays. • Not affected by inverter-type and its control strategy, microgrid topology and level of generation. Due to the unavailability of a suitable relay for microgrid protection, various utilities are fitting available IEDs for the protection of microgrids. At present, microgrid protection is achieved using a combination of conventional numerical relays. These numerical relays are not suitable for all kinds of microgrid architectures and do not provide complete protection with inverter-based generators. Since these relays were designed considering the fault characteristics of synchronous generators, they fail to respond to the fault characterized by inverter-based generators. This paper proposes a new protection technique that is independent of the type of generating sources, control philosophy of inverters as well as microgrid architecture. Simulations are performed using PSCAD/EMTDC and performance of the protection scheme is also evaluated in real-time using RTDS. Pertinent results are presented which demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

From the perspective of power balancing, we consider in this paper the timescale of real-time dispatch in power systems with high penetration of intermittent power sources. Due to the integration of intermittent power sources, real-time dispatch must be employed in the process of power balancing. The hierarchy of power system operation is typically comprised of the short-term scheduling, the real-time dispatch, and the automatic generation control (AGC). Therein, the AGC is the last-level defense of the systemwide power balancing, which has limited power adjustment capability. Consequently, the real-time dispatch must eliminate as much power imbalance as possible, and its capability of doing so depends on its timescale. Based on the statistical forecast uncertainty functions, a quantified relation between the uncertainty level of the power system and the critical timescale for real-time dispatch is established in this paper. Simulations demonstrate the effectiveness of the proposed formula. [ABSTRACT FROM AUTHOR]

To improve the power supply availability in an island microgrid, this paper proposes a new approach that integrates distributed energy sources economically, reliably and efficiently. In an island mode, a microgrid must ensure its self-sufficiency of energy production since it cannot make an energetic exchange with a main grid. However, in this mode, the random behavior of the resources affected by meteorological factors presents a major constraint. The challenge related to the power availability in microgrids is to find a solution that faces the operation of intermittent power sources. The microgrid should guarantee a useful power management in order to achieve a high availability of energy. In this paper, we present a mathematical model to describe the influence of the meteorological factors on the sources production. We propose a multi-agent control strategy based on the production forecasting and load shedding for a high availability of the microgrid power supply. The proposed multi-agent system uses the master-slave model in which the communication and negotiation between the defined agents are performed by a concept of tokens. The developed control system is implemented on Spartan 6 FPGA-Board. The paper's contribution is applied to a Tunisian petroleum platform where several blackouts are recorded between 2012 and 2014. Simulation and experimental results show clearly a high availability as a performance of the proposed control strategy. [ABSTRACT FROM AUTHOR]

The increasing applications of renewable energy resources and energy storage units (ESU) raise the necessity for reliable, efficient, and economical power systems. However, the charge/discharging power loss of ESUs cannot be ignored in the islanded microgrid. This paper focuses on the economic dispatch (ED) problem of ESUs in DC microgrids to reduce charging/discharging power loss, meet the power balance requirement, and against communication delays. Specifically, the distributed cooperative control algorithm designed in this paper forces incremental costs of all ESUs to a consistent value to minimize the sum operation loss of all ESUs in the small time scale. Meanwhile, power imbalance auxiliary variables are added to the control algorithm to satisfy the power balance constraint in the control process. Moreover, the ubiquitous time delay effect of communication links on the dispatch performance is solved by presenting an aperiodic sampled data-driven control method. The control parameters are determined by solving strict linear matrix inequalities, and the system stability analysis is also presented through the Lyapunov–Krasovskii functionals. Compared with the traditional control methods, the provided algorithm can overcome the negative effect of communication delay and save 16.94% of the sum ESUs operation loss under the given scenario. • An economic dispatch optimization algorithm for energy storage units is proposed. • The power balance constraint can be satisfied during the control process. • Develop a buffer-based waiting time strategy to avoid the effect of time delay. • The stability of the presented closed-loop system is proved. [ABSTRACT FROM AUTHOR]

The advent of distributed energy resources (DERs) in microgrids has provided significant benefits. University campus microgrids can manage their DER efficiently to minimize consumption, energy losses, and environmental impacts. Thus, to boost the transition from a traditional university campus to a sustainable and smart campus, this paper proposes an optimal siting and sizing study of photovoltaic systems and electric vehicle charging stations for a microgrid of a Brazilian university. This problem is formulated as mixed-integer nonlinear programming and is carried out in two stages. The first stage minimizes grid losses by locating and sizing photovoltaic panels, while the second stage minimizes the grid losses and maximizes the proximity of charging stations to the load centers by optimizing the place and sizing of charging stations. In addition, this work considers load uncertainty through the Monte Carlo method with a scenario reduction technique. The results estimate that photovoltaic systems can reduce 13.48% of the monthly electricity cost. The optimal charging station location is usually nearby the photovoltaic system siting or the substation. However, the increase in the number of chargers in buses with high consumption causes an increase of around 5% in grid losses. Furthermore, this paper discusses possible scenarios for photovoltaic systems and charging station installation based on the benefits of the transition to a sustainable and smart campus, considering Brazilian electricity sector policies. • Perform a scenario reduction to deal with load and generation curves uncertainties. • Minimize electrical losses by optimizing the siting and sizing photovoltaic systems. • Perform multi-objective optimization for siting and sizing charging stations. • Sensitivity analysis for distributed energy resource installation. • Discuss the advent of distributed energy resources to university campus. [ABSTRACT FROM AUTHOR]

The number, layout and configuration of black-start power supplies will directly affect the recovery process of the power system after power outage. A scientific and reasonable black-start deployment optimization scheme can greatly accelerate the grid recovery process and reduce the duration of power outage. In this paper, based on the basic principles of power system partition recovery, we divide the power system recovery partition based on improved label propagation algorithm, which is used to guide the deployment optimization of multiple Black-start power supplies sources. Subsequently, based on the important nodes and key lines of the grid, a mathematical model of multiple black-start power supplies deployment optimization considering the shortest restoration time is established, taking into account various constraints. Finally, the traditional coyote optimization algorithm is improved by improving the coyote growth model, introducing adaptive Lévy flight and chaotic optimization perturbation mechanism, and applied to the solution of multi-Black-start power supplies deployment optimization model. The effectiveness of the proposed partition recovery method and the adaptability and superiority of the multi-black-start power distribution optimization method are compared and analyzed by arithmetic examples in Matlab simulation software. The simulation results show that the proposed multi-black start power distribution optimization method with zonal recovery can reduce the outage duration and improve the recovery efficiency. [Display omitted] In this paper, we divide the power system recovery partition based on improved label propagation algorithm and the basic principle of power system partition recovery. And then we improve the solution of traditional coyote optimization algorithm for multiple Black-start power supplies deployment optimization model by changing the coyote growth model and introducing adaptive Levy flight and chaotic optimization perturbation mechanism. [ABSTRACT FROM AUTHOR]

• Application of the ampacity control system is necessary for wind energy integration. • DLR application reduced the time in which wind farms were out of service by 4100 h in 44 months. • DLR application increased the energy supplied by wind farms by 70.9 GWh in 44 months. • DLR application saved more than 7800 t of CO 2 in 44 months. The total renewable wind energy capacity of Spain currently accounts for more than 20% of the total installed energy capacity, which makes integration into the grid challenging for wind farm owners as well as Distribution System Operator (DSO). Electrical companies require new techniques to integrate renewable energies safety and with low investment costs. Dynamic line rating (DLR) is one of these techniques, and is used by DSOs to maximise the capacity of existing infrastructure. This paper presents a successful case of DLR application by a DSO over several years to reduce the time that wind farms were out of service due to an excess of electrical energy generated. Over the period from January 2015 to September 2018, the application of the DLR technique prevented 4,100 hours of out-of-service time, increasing the energy supplied by the wind farms by 70.9 GWh and by extension saving 7,800 tons of CO2. [ABSTRACT FROM AUTHOR]

The integration of Distributed Energy Resources (DERs) in distribution networks comes with challenges, like power quality concerns, but also opens up new opportunities, e.g., DERs can offer competitive energy prices for final users by leveraging time arbitrage. A suitable method to fully exploit such opportunities is to compute the optimal DER schedule, either with a full three-phase network model or a more computationally efficient single-line equivalent. This paper presents under which conditions a single-line equivalent can and cannot be used to properly represent a modern and unbalanced power distribution network able to dispatch high levels of DER integration optimally. Results show that single-line equivalents might be helpful when the problem objective function limits counterflows, for example, when minimizing active power losses. Moreover, single-line equivalents might be helpful for low levels of DER integration. However, enabling single-line equivalents results in a lower hosting capacity for high levels of DER integration. • Three-phase models ensure safe network operation, but with more computation time. • Increase of Distributed Energy Resources may increase unbalances in the network. • Maintaining balanced conditions may require more curtailment. • Single-line equivalent models are effective when minimizing network losses. • Case studies include 144 simulations on the 34 node IEEE test feeder. [ABSTRACT FROM AUTHOR]

This paper presents a model for photovoltaic (PV) distributed generators that operates in abnormal electrical voltage scenarios — Voltage Ride Through (VRT), following the Brazilian standard NBR 16149 of 2013. The model includes various modes of operation, such as interruption of energy supply, disconnection, and reconnection of the PV system to the grid. Two types of simulations were performed to test the model's performance: the first involved using a ramp function to test the activation of different operating modes, while the second connected the PV model to a distribution feeder and tested its response to a short circuit. The results showed that the model met the requirements established by the standard and was efficient in representing the behavior of the PV system in real-world scenarios. • Photovoltaic solar energy has been gaining considerable space. • Dynamic modeling of photovoltaic generators. • The recommendations of the Brazilian standard RS 16149 for PV connections. • The simplified generator model reduces computational costs. [ABSTRACT FROM AUTHOR]

In this paper, an alternative approach to power loss calculation in a transformer supplying a nonlinear load is presented. The advantage of the proposed approach is that it relies on readily available transformer technical data in contrast to the data required by the methodology described in IEEE std. C57.110–2018. Experimental verification of the proposed approach was carried out using a 4.5kVA laboratory dry type power transformer. The results obtained experimentally show high compatibility with theoretical model featuring an error margin smaller than 0.2%. [ABSTRACT FROM AUTHOR]

• To solve the issues related to ignoring network constraints in the peer matching process, we apply NUF based on sensitivity analysis to evaluate the impact of each agent's equivalent load on network constraints. The proposed NUF can fully and fairly diagnose the portion of each agent on power loss, congestion and voltage violation. • This work extends the existing primal-dual subgradient algorithm by adding Peer-to-Grid (P2G) energy trading and NUF. • The proposed TEM framework would innovatively ensure the individual TE agent privacy while facilitating energy trading. • As part of the proposed TEM framework, the DSO operation (e.g., VVC and network reconfiguration) is considered, which may assist in providing the optimal network topology to facilitate peer matching and minimize interference with the scheduling of the TE agents. A growing number of distributed energy resources (DERs) connected to the distribution network presents operational challenges. Therefore, it is crucial to develop an effective framework to address these challenges. In this paper, a novel transactive energy market (TEM) framework is proposed in two levels based on the concept of a network usage fee (NUF) to address technical issues. We perform the peer matching process using a primal-dual algorithm at a lower level. We consider distribution system operation (DSO) operations (e.g., Volt/VAR control and network reconfiguration) and NUF to maintain network constraints and to provide an optimal network topology to facilitate energy trading. The proposed framework has been tested on an IEEE 33-bus distribution network. A key issue relating to the coordination of DERs in distribution networks is addressed in the results. In the proposed NUF, the sensitivity analysis is used to fully diagnose the portion of each TE agent in power loss, congestion, and voltage violations. A fair penalty or incentive signal can be generated to ensure that the network operates within the limits. Furthermore, the proposed framework ensures that the privacy of agents is protected. DSO operation facilitates the trading of energy and minimizes interference with their schedules. [ABSTRACT FROM AUTHOR]

• This paper focuses on boosting the diesel generator (DG) set's utilization by exploiting the solar photovoltaic plant (SPVP) power converter's available capacity as DSTATCOM. The key highlights of this work are as follows. • The power factor of the DG set is regulated at unity irrespective of the SPVP generation or load behavior, enhancing the efficiency of the diesel engine and electric generator. Consequently, fuel consumption is decreased, lowering the cost of electricity. • The SPVP carries the burden of the entire load's reactive power. Hence, the DG set's surplus capacity, initially reserved to supply the reactive power to the load, can be utilized now to commit the additional load on the same rating system. • Due to the DSTATCOM operation, the SPVP operates 24 hours, raising the overall utilization factor of the SPVP. Hence, the payback time is less compared to the existing system. • The DSTATCOM operation of the SPVP boosts the power quality performance of the microgrid without causing any high additional costs to the system. Thus, the IEEE std. 519 [21] is followed at POI, with improved utilization of the microgrid. • A least mean 2L th (LM2L) rule-based adaptive filter has been developed for a quick and accurate estimation of the load's fundamental component current. It is a hybrid adaptive filter algorithm that uses the conventional normalized least mean square (N-LMS) and normalized least mean fourth (N-LMF) algorithms to improve the steady state and transient response. In the existing solar photovoltaic (SPV) and diesel generator (DG) based standalone microgrid, the power factor of the DG set reaches around 0.5-0.6. Further, it encounters poor power quality performance due to harmonics currents of the local loads, coupled at the microgrid's point of interconnection (POI). All these issues significantly affect the DG set performance, causing additional losses and reducing its fuel efficiency. In addition, the SPV plant does not provide any ancillary services in the existing system and remains ideal most of the time, causing the under-utilization of microgrid's power converters. In this context, this work presents a least mean 2L th (LM2L) rule-based adaptive filter-controlled SPV system, where its power converters are regulated to deliver multifunctional capabilities such as enhancing the DG set's power factor and power quality performance. As a result, the DG set power factor improves to unity, and the %THD value of its voltage and current reduce to below 5%. Hence, the fuel efficiency of the DG set is improved, line losses are decreased, and the additional load can be committed to the DG set capacity, which is kept reserved to supply reactive power to the load. Moreover, the modifications, which are earlier required in the DG set design to accommodate the distortion in its voltages and currents due to the nonlinear load, can be avoided. The LM2L algorithm is used as a prefilter for the measured load currents and determines their fundamental component. It has two operating rules, which decide the fundamental component's estimation depending on the system conditions. As a result, it demonstrates an improved steady state and dynamic performances compared to the existing adaptive filter algorithms. Test results verify the control and design of the microgrid on a laboratory prototype. [ABSTRACT FROM AUTHOR]

• A method to preplan segmentation of power distribution system into MGs with flexible boundaries to enhance resiliency. • A three-stage algorithm to enable resiliency of the PDS subjected to natural disasters and/or multiple faults, using MILP. • Assessed the impact of the controllable MGs with flexible boundaries on power system resiliency performance with a composite metric. With the increased frequency of adverse weather and manmade events in recent years, the issue of the power distribution system (PDS) resiliency has become drastically important. Microgrids with various types of distributed energy resources (DERs) have capabilities to enhance the PDS's resiliency against high impact low probability (HILP) events. Resiliency is defined as the ability of the system to keep supplying critical loads even during and after extreme contingencies. This paper presents a systematic method to segmentize parts of a PDS into microgrids with flexible boundaries to enhance resiliency and mitigate negative impacts from anticipated threats. The method is aimed at anticipation and preparation to HILP events in advance: alternative flexible boundaries of the microgrids must be preplanned during normal operation and dynamically changed prior to or during disturbances. The Mixed-Integer Linear Programming (MILP) is formulated and applied to select switching actions to adjust microgrids' boundaries as well as to supply critical loads, while meeting system constraints. Networked microgrids are merged and reconfigured as necessary to maximize supply to critical loads, driven by a factor-based resiliency metric, which is obtained using the Analytical Hierarchy Process (AHP). The modified IEEE 123 bus system was utilized for validation of the proposed method. Compared with the traditional fixed-boundary microgrids, this approach determines the most resilient network configuration to supply high-priority critical loads. The developed method can be employed in power system planning, operation, and in decision-making to enhance operational resiliency and invest in system upgrades appropriately. [ABSTRACT FROM AUTHOR]