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• The compressed sensing algorithm is introduced to process the electrical quantity information and improve computing efficiency. • Introducing Bayesian networks to handle switch quantity information can narrow the fault range and improve the locating efficiency. • A fault location method is proposed. Dempster-Shafer's (DS) evidence theory was adopted to achieve accurate fusion. • This paper proposes a method based on an evidence similarity matrix combining a quadratic fusion strategy to realize deep information fusion. When a DC distribution network fault occurs, it is difficult to locate the fault information of a single switching quantity or electrical quantity, so this paper proposes a Fault location method for DC distribution network based on multivariate information fusion. Firstly, the compressed sensing algorithm is introduced to process the fault electrical quantity information and obtain the fault current amplitude of the component. Secondly, Bayesian network is introduced to process the fault switch quantity information and obtain the fault degree of the component. Finally, a quadratic information fusion method based on evidence similarity matrix discrimination is proposed. By establishing a similarity matrix between the evidence information of electrical quantity and switching quantity, this method can overcome the problem of inaccurate positioning caused by evidence conflict between suspected faulty components by mode solving and mode discrimination. At the same time, the collision caused by uncertain subsets can overcome the influence on the accuracy of fault location, so that the fusion can obtain more accurate fault location results. The simulation experiments on the simulation software show that more accurate positioning results can be obtained by the fusion of electrical quantity and switching quantity in this paper. [ABSTRACT FROM AUTHOR]

• At present, there is no systematic analysis of the causes of overheating in the research on connection fittings for extra-high voltage direct current transmission lines both domestically and internationally. Only through simulation of overheating defects, the impact of overheating on transmission lines has been studied, and no systematic investigation plan for related defect problems has been proposed. • The model proposed in this paper can be used for analyzing problems related to ±800 kV extra-high voltage DC overhead transmission lines, as well as for ultra-high voltage DC overhead transmission lines such as ±500 kV, and has strong universality. • This paper propose a systesmatic troubleshooting plan for related defect issues, which has important reference and guidance significance for such line fault problems. This paper studies the overheating defect of an extension rod in a ± 800 kV extra-high voltage direct current overhead transmission line, and proposes various factors that affect the overheating of the extension rod. Establish an equivalent model of an extra high voltage DC transmission line based on equipotential point and line parameter analysis, and calculate the model parameters. The proposed model can also be applied to ultra-high voltage DC overhead transmission lines such as ± 500 kV, and has strong universality. Simulation experiments show that if the equivalent resistance value of the split wire side is reduced by 0.01Ω, the power loss on the extension tie rod can be increased to 380.951 W; if the equivalent resistance value of the jumper side is increased by 0.01Ω, the power loss on the extension tie rod can be increased to 273.41 W. Combined with theoretical analysis and simulation verification, it is concluded that the main factor affecting the overheating of the extension rod is the change in the resistance value on the jumper side caused by the increase in contact resistance. A systematic troubleshooting plan for related defect problems is proposed, which has important reference and guidance significance for such line fault problems. [ABSTRACT FROM AUTHOR]

Optimal Power flow (OPF) problem is a nonlinear nonconvex optimization problem. It faces three challenges when solving the algorithm based on traditional optimization methods, namely, global convergence, solving efficiency and global optimization. For complex and large-scale power systems, global optimization of algorithms is more difficult to achieve than global convergence and solution efficiency. Therefore, this paper proposes a method for finding the global optimal solution to the OPF problems. This method first transforms the OPF problem into a relaxed OPF problem. Then, by using the transformation function max { ⋅ } , the relaxed OPF problem is decomposed into two subproblems. Finally, the global optimal value and solution of the OPF problem are obtained by solving two sub problems using the generalized gradient Newton method and the smooth Newton method, respectively. Numerically in the experiments, we compare the proposed method with the interior-point method, the commercial solver SNOPT, NLP(KNITRO) and ESLP2. The results show that under the same order of magnitude of computational efficiency, the method proposed in this paper has more advantages. • The OPF problem is relaxed into an optimization problem with only inequalities. • Introduce estimation parameters to estimate the global optima objective value of the OPF problem. • Decompose the OPF problem into two sub problems: single variable root finding and box constraints only. • Provide sufficient and necessary conditions for the global optimal value of the OPF problem. [ABSTRACT FROM AUTHOR]

This article introduces an innovative approach for online detection and localization of forced oscillation (FO) in power systems with significant integration of wind turbine generation (WTG). The synergistic combination of Multichannel Prony analysis with Periodogram and dissipating energy flow (DEF) approach is proposed in this paper to overcome the challenges inherent in detecting FO amidst the complexities introduced by WTG integration. An adaptive version of multichannel Prony analysis is proposed in this paper that dynamically estimates Prony's system order via the recursive process. It estimates the frequency and damping ratio of all oscillatory modes, which is used to identify low damping modes that are potentially attributed to FO. Leveraging this information, the proposed method enhances both FO detection and source localization capabilities. The proposed method is verified on measurements taken from IEEE benchmark 4-machine, 11-bus system and 10-machine, 39-bus system with high wind energy penetration. Comprehensive testing demonstrates the proposed approach's effectiveness across various FO scenarios, including governor valve malfunction, exciter malfunction, and cyclic loads. Furthermore, the methodology is evaluated under resonant conditions and scenarios involving the simultaneous identification of multiple disturbances. • Detection & source location in WTG integrated power system. • MDMMO for dynamic estimation of Prony model order. • OFDM using Periodogram technique. • OFSLM using dissipating energy flow method. [ABSTRACT FROM AUTHOR]

• A micro-measurement method based on the IPDA. This paper uses a low-pass filter to process the zero-mode current to obtain the characteristic components. Then, by calculating the second derivative of the filtered part, the selection of the inflection point dense area (IPDA) at the microscopic level is achieved. This physical significance of IPDA is used to effectively express the feature that the zero-mode current direction of the faulty feeder is entirely opposite to that of the healthy. • It is proposing an ultra-high-speed protection scheme for DC distribution networks. In this paper, only 20 sampling points within the IPDA are processed, and the selection of the data window length can be adjusted according to the system sampling frequency and other factors. It meets the requirements of DC distribution networks for protection speed and selectivity, and the algorithm can correctly detect faulty feeders in a high resistance state, with little influence from external factors. A flexible direct current (DC) distribution network based on modular multilevel converter (MMC), with the advantages of no phase change failure and fewer current conversion links. It has gradually become the development trend of future medium voltage distribution networks. However, when a single-pole ground fault occurs in the feeder, the converter's low inertia and weak damping characteristics lead to a fast-rising fault current with a high peak value, which is harmful to the system. In this paper, for the difficulty of accurately selecting the faulty feeder when a single-pole ground fault occurs in a radial DC distribution network, a detection method based on the zero-mode current within the inflection point dense area (IPDA) for the fluctuation characteristics of concave and convexity (FCCC) is proposed. Firstly, the zero-mode current of each feeder is processed using a low-pass filter to select the eigen-components; Then, taking second order derivatives of the eigen-components, and the IPDA is established, to find a period in micro measurement to achieve accurate direction correspondence with opposite directions; Again, the data within IPDA is normalized; the criterion is constructed by determining each feeder's FCCC. Finally, the simulation model is built by Power Systems Computer Aided Design to verify that the method can identify the faulty feeder in various situations. Compared with existing methods, the fault detection method proposed in this paper has good stability and can withstand large grounding resistances. [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]

• 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]

• Proposes an improved YOLOv5s model which combines the GIoU, Mish, and CBAM modules. • The improved algorithm can effectively detect different-size insulator defects under different environmental backgrounds. • The AP value in detecting insulator defects can be improved by 5 %. As one of the most important components on the transmission line, the insulator is prone to failure, which affects the safe operation of electrical power system. Hence, it is crucial to accurately detect the insulator defects for further maintenance in time. Recently, with the development of artificial intelligence and target detection algorithms, the insulator defect detection has received more and more attention. However, there are still existing some difficulties: insufficient samples and low detection accuracy. To improve the accuracy of insulator defect detection, this paper proposes an auto-detection method based on an improved lightweight YOLOv5s model. First, this paper introduces the basic network frame of YOLOv5s and proposes an improved algorithm by utilizing the GIoU loss function, Mish activation function, and CBAM module. Then, performs data enhancement in the insulator dataset to enhance the robustness of the model. Finally, trains and tests the improved YOLOv5s model, and compares it with traditional target detection algorithms. Compared with traditional target detection algorithms, the AP value of the proposed algorithm in detecting insulator defects can be improved by 5 %. The results demonstrate the improved algorithm proposed in this paper can effectively identify and position the insulator defects. [ABSTRACT FROM AUTHOR]

• This paper conducts tests on porcelain insulators to study their electric field signals during pollution flashovers at various levels. • In order to predict pollution degrees accurately, a method combining neural networks and signal monitoring is proposed. • The study finds that higher pollution levels correlate with increased electric field values, leading to distortion in the signal waveform and higher total harmonic distortion rates. The online monitoring of insulator surface pollution states is crucial for predicting/preventing pollution flashover accidents. This paper conducts artificial pollution tests on porcelain insulators at five pollution levels to obtain the electric field signal during the flashover process. Subsequently, the time-frequency performance of the electric field signal waveform at various discharge stages is discussed in detail. Finally, a method for predicting pollution degrees by combining back propagation (BP) neural networks and non-contact electric field signal monitoring is proposed and validated. Research results indicate that during the pollution flashover process of the porcelain insulator, the peak value of the electric field signal shows an upward trend in sections. As the equivalent salt deposit density (ESDD) increases, the curves of electric field values rise. The development of dry-band arcing clearly distorts the electric field signal waveform at its crest and trough parts, increasing the total harmonic distortion (THD) rate. The THD can reach 100–130 % when closing to flashover, with the third harmonic acting as the main component. By taking k max (the rising rate of the E-field signal amplitude), g (the ratio of E max to E rms), K3 (the third harmonic coefficient), and THD as inputs to the BP neural network model, an ESDD prediction with a relative error lower than 10.63 % is realized. This research can offer novel technical support for predicting pollution degrees. [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]

• The coordinate transformation stability criterion (CTSC) is derived by constructing the SISO model of the GCI system in αβ domain. This approach provides a simple and intuitive form while minimizing conservatism. • The average parameter assessment metric (APAM) is proposed based on CTSC to evaluate the impact of each parameter over a wide range. • The joint parameter assessment metric (JPAM) is proposed to simultaneously adjust multiple parameters on stability. • System stability can be effectively improved by selecting parameter tuning through parameter assessment metrics. The negative resistance of grid-connected inverter (GCI) and the increasing number of GCI in power grid pose great challenges to the stability of GCI. This paper proposes a coordinate transformation stability criterion (CTSC) based on the single-input single-output (SISO) impedance model for GCI system. A low complexity fractional polynomial model of GCI is derived by the Pade approximation and the SISO impedance model in the αβ domain. CTSC is proposed by applying the Nyquist stability criterion, which simplifies the graph trajectory criterion to a numerical criterion. Since the effect of parameter on stability is usually limited to the neighborhood, average parameter assessment metric (APAM) is proposed based on CTSC to evaluate the impact of each parameter over a wide range. Additionally, joint parameter assessment metric (JPAM) is proposed to simultaneously adjust multiple parameters on stability. Finally, compared with the three criteria for conservatism analysis, CTSC possesses the lowest conservatism. The theory proposed in this paper is verified by experiment. [ABSTRACT FROM AUTHOR]

• Analyzing reliability of a distribution company by data envelopment analysis. • Obtaining distribution companies' reliability targets using best past performance. • Estimation of reliability target level by machine learning methods. • Incorporation of outage characteristics for reliability target estimations. Electrical distribution system (EDS) reliability has always been a critical subject due to the considerable share of distribution systems in power interruptions to end-users. Meeting regulatory service quality standards requires distribution companies to achieve defined reliability levels for performance improvement. Conventionally, specialists determine target reliability based on experience, experimental knowledge, and rules of thumb. However, these methods are error-prone and may result in suboptimal investments, economic inefficiency, and inadequate resource allocation in EDS operation and planning. Accordingly, this paper presents a machine learning-based method to determine the target level for EDS's reliability indices based on its historical performance. The approach involves comprehensive analysis of historical EDS reliability data, followed by a data envelopment analysis (DEA) to assess performance across subdivisions like substations or feeders, identifying the most effective units. Subsequently, machine learning models—Random Forest (RF), Support Vector Machine (SVM), and Radial Basis Function (RBF) network—are trained on optimal subdivisions from the DEA stage. These models accurately estimate target reliability for all subdivisions, contributing to the overall determination of the EDS target reliability level. A three-scenario case study validates the proposed method, suggesting its potential applicability as a valuable tool for regulatory agencies in setting EDS reliability targets. While admitting the potential challenges, notably the method's reliance on the quality and completeness of the historical data collected by distribution companies, the paper emphasizes the importance of collaborative efforts to ensure data accuracy and sufficiency. The proposed method leads to a fair mechanism to determine the target level for a real EDS's reliability indices in comparison with a business-as-usual scenario. Moreover, it provides a reliability performance ranking for the EDS's subdivisions. [ABSTRACT FROM AUTHOR]

• The feasibility of the ICOG corona ring is verified by simulation analysis. • The opening distance, installation orientation and insulating layer thickness of the opening corona ring are simulated and analyzed, and the parameters of the ICOG corona ring are determined. • The electric field of the ICOG corona ring in the case of bird droppings is simulated and analyzed. • Through the bird droppings simulation test, the anti-bird performance of the ICOG corona ring is verified. In the bird-related faults of transmission lines, the bird droppings flashover fault caused by the short-circuiting of bird droppings to the corona ring is extremely significant. To decrease the flashover probability of bird droppings and improve the convenience of installation, this paper proposes a method of coating the insulating layer on the open-gap corona ring, and verifies the insulation performance of the insulation coated open-gap (ICOG) corona ring through simulation and experiment. In this paper, the feasibility of corona ring coating insulating layer is verified by finite element simulation, and the influence of ICOG corona ring structure on the surface electric field distribution of composite insulator is studied. Finally, the impact of various bird droppings parameters on the flashover of the ICOG corona ring is investigated through experiments and compared with the flashover of an ordinary corona ring. The simulation results show that when the opening distance is 50–70 mm, the opening is toward the tower side, and the thickness of the insulating layer is 5 mm, the surface field strength of the composite insulator is the smallest. The experimental results show that the flashover probability of bird droppings increases with the increase of conductivity and viscosity of bird droppings. After the open-gap corona ring is coated with the insulating layer, the area where the bird droppings flashover occurs is reduced by about 20 %, which can better play the role of anti-bird flashover and has better convenience. This paper provides a certain reference for the anti-bird control of transmission lines. [ABSTRACT FROM AUTHOR]

This paper aims to address the bidding strategy optimization in the real-time multi-participant electricity market with short-term load dynamics. In order to avoid the sub-optimal solution and the dependence on the complete information in traditional mathematical programming methods, an electricity market bidding strategy optimization algorithm based on deep reinforcement learning (DRL) is developed. While conventional reinforcement learning algorithms (e.g., Q-learning and deep Q-learning) are only capable of handling simple problems in discrete state spaces, the proximal policy optimization (PPO) algorithm is implemented in the bidding strategy optimization since it can optimize the bidding strategy in the continuous action and state spaces. In order to substantiate the aforementioned perspective, this paper conducts a two-part experimental study. First, experiments which consider the fixed demand load of market participants show that the developed method can reach the Nash equilibrium just like the bi-level optimization, and higher profits can be achieved by adjusting hyperparameters. Then, complex experiments which consider the time-varying demand load verify the DRL-based electricity market bidding strategy performs better than bi-level optimization-based methods and increases the profits of generators. • A PPO-EMBSA is proposed to overcome the limitations of the MPEC-based in two distinct aspects. First, PPOEMBSA does not need to transform the lower-level problem of the bi-level programming to the corresponding KKT condition. Second, agents select appropriate strategies by PPO-EMBSA in an environment with incomplete information and optimizes the present strategy for future rewards. • The PPO-EMBSA improves the accuracy and the stability of RL-based-electricity market bidding strategy. • Experiment results show that the PPO-EMBSA derives appropriate bidding strategies in situations of both fixed demand load and time-varying load, and the proposed method is more competitive than bidding algorithms based on Q-learning, DQN and A3C. In particular, additional ablation studies discuss the sensitivity of PPO-EMBSA to some hyper-parameters. [ABSTRACT FROM AUTHOR]

• This paper proposes a reliability evaluation method considering the static frequency regulation for overcoming the shortcoming of the traditional reliability method. • This paper presents a failure restoration mode integrated into the reliability evaluation through designing system load curtailment, frequency restoration, and load restoration. • This paper establishes a series reliability calculating models which depend on the different failure restoration conditions. The adequacy of power system can be elevated with the increasing grid-connected capacity of wind farm, and meanwhile, the power system reliability is also affected by the intermittent power fluctuation of wind farm. However, the traditional reliability evaluation technique cannot take the power fluctuation into account. Therefore, for considering the positive and negative influence of wind energy on the power system reliability, this paper proposes a reliability evaluation technique through considering static frequency regulation and failure restoration process. A failure restoration strategy which can be integrated into the reliability evaluation model is presented through designing system load curtailment, system frequency restoration, and system load restoration strategies. A series reliability calculating models which depended on the different failure restoration conditions are established. Case studies for different systems are investigated, and the results verify that the proposed method can consider both aspects of the positive and negative influence of wind farm on the power system reliability. [ABSTRACT FROM AUTHOR]

• This paper takes the community electricity trading market with multiple prosumers participating at the distribution network level as the research object, fully considering the impact of the psychological gap effect of prosumers on system operation from a micro-perspective, and proposes a distributed electricity market trading mechanism based on the Stackelberg game, which in order to provide new ideas for the improvement and optimization of the distribution-side electricity market trading system, and the core findings of the paper are as follows:. • The trading mechanism proposed in this paper could better schedule translatable loads and energy storage units, reduce the fluctuation amplitude of the load curve while performing peak cutting and valley filling, stimulate the flexibility of user-side resources, and ensure the stability of system operation. • The trading mechanism proposed in this paper could obtain more evidence-based and reasonable prices for purchasing and selling electricity within the region, ensuring that the distribution network operator could obtain considerable profits while effectively improving the profits of prosumers, which is conducive to improving the economic efficiency of system operation. • In terms of the impact of the gap effect on the energy utility and profits of prosumers, the larger the gap effect coefficient (prosumers are more sensitive to expected deviations), the lower their electricity utility and overall profits, and when the individual electricity utility and overall profits of prosumers are too low, they may withdraw from market transactions. Therefore, government departments could implement policies, such as providing subsidies and adjusting taxes, to further stimulate the enthusiasm of prosumers to participate in distributed market transactions. With the large-scale customer-side development of distributed energy and continuous advancements in power market reform, the market-oriented trading of distributed power generation with the participation of prosumers has gradually become an important solution to promote the consumption of distributed energy. In addition, prosumers exhibit obvious bounded rationality characteristics; therefore, the design of efficient and reasonable trading mechanisms determines the efficiency of the market. From this perspective, a distributed electricity market trading mechanism based on the Stackelberg game is proposed for the community electricity trading market, with multiple prosumers participating in the distribution side. Firstly, the trading architecture of the community electricity market was established under the distribution network level. Secondly, the pricing strategy of the distribution network operator and the quantitative strategy of community prosumers were analysed; on this basis, the characteristics of the bounded rationality of prosumers were considered, and the impact of the psychological gap effect of prosumers on their energy utility was introduced into the objective function of prosumers. This facilitated the construction of a Stackelberg game model in which distribution network operators lead and community prosumers follow. Thirdly, the Stackelberg equilibrium was proven to exist and be unique, which was then solved by the distributed algorithm – combining the evolutionary algorithm and quadratic programming – which improves the solution efficiency and effectively protects the privacy of prosumers. Finally, the effectiveness and feasibility of the proposed trading mechanism were verified through numerical examples. [ABSTRACT FROM AUTHOR]

• A comprehensive FRT scheme by using an RC-crowbar and matching control strategy. • Resonance issues were considered in the capacitance design of the RC-crowbar. • Improved the control strategy for stator side and rotor side converters. • The proposed FRT scheme can dynamically switch based on the degree of fault. This paper compares the problems existing in the current fault ride-through (FRT) schemes of the doubly-fed induction generator (DFIG), and deeply analyzes the transient characteristics of DFIG during FRT. A comprehensive FRT scheme is proposed to improve the FRT capability by using an RC-crowbar and matching control strategy switching. The main innovation of this scheme lies in the consideration of resonance and other factors in the capacitance design of the RC-crowbar. To ensure that the DFIG still has good FRT capability after the RC-crowbar is cut off in advance in the later stage of FRT, an improved rotor side converter (RSC) control strategy is proposed for this situation. At the same time, to balance the reactive power on the stator side and accelerate the recovery of stator voltage throughout the entire FRT period, the control strategy of the grid side converter (GSC) is also improved. The comprehensive FRT scheme proposed in this paper can dynamically switch based on the degree of fault so that it still has good FRT ability when applied to different degrees of faults. Finally, the correctness and effectiveness of the proposed comprehensive FRT scheme were verified through simulation experiments. [Display omitted] [ABSTRACT FROM AUTHOR]

• Establishment of comprehensive Database : through extensive lightning impulse flashover tests on 110 kV insulators, a robust database for U 50 % and volt-time characteristics was created, providing a solid foundation for analysis. • Superior performance of PSO-RF in U 50 % Prediction: comparative analysis revealed that the PSO-RF model exhibited the lowest prediction error and highest accuracy among other models such as BP and SVM. Its exceptionally low e MAPE of 1.17 % makes it the optimal choice for constructing U 50 % prediction models, particularly suitable for high-dimensional data with a small sample size. • Innovation in Volt-time characteristics Prediction: this study introduces regression prediction for insulator volt-time characteristics, showcasing the superiority of intelligent models over traditional approaches. Comparison with existing standards and literature validates the efficacy of these models under different operating conditions. • Practical Implications: the predictive models developed in this study offer practical utility in analyzing flashover characteristics of 110 kV insulators under diverse conditions. Their implementation ensures the safe and stable operation of transmission lines, thereby enhancing overall system reliability. The lightning flashover criteria of insulators vary significantly under different conditions, and it is impractical to exhaustively enumerate all the criteria through extensive tests. Therefore, this paper aims to explore the intelligent prediction of lightning flashover criteria for 110 kV insulators using a data-driven approach. Initially, a test database comprising 4,978 high- and low-altitude test data of 110 kV insulator lightning impulse flashover is established. Subsequently, relevant characteristic values are extracted from the database as inputs for the prediction model. Various machine learning algorithms, such as the BPNN, SVM and RF algorithms, are employed to construct prediction models for the U 50 % and volt-time characteristics of 110 kV insulators under lightning impulses. The results demonstrate that the RF algorithm yields an average absolute percentage error of merely 1.17 % for the U 50 % prediction model. Additionally, the RF and BP algorithms achieve the highest prediction accuracies of 10.7 % and 6.5 %, respectively, for the volt-time characteristics at high- and low-altitude. This validates the feasibility of substituting many traditional tests with more accurate flashover criteria predicted through a data-driven approach. This paper provides a novel concept for predicting the lightning impulse flashover criteria of insulators under different working conditions. Reducing the need for repetitive tests is expected to acquire the high-precision intelligent prediction of insulator lightning impulse flashover criteria. [ABSTRACT FROM AUTHOR]

• The impacts of faulty cables on their neighboring metallic buried pipelines may be greater if these pipelines pass next to the underground power cables. • This article presents a study of the influence of the presence of metal pipes near underground power cables, specifically in the event of line to ground faults in these cables, as well as the use of barrier mediums to reduce this effect, which is not covered in previous articles. • In this paper, the conduction currents generated in metal pipes as a result of faults in cables were studied. To reduce the induction voltages affecting the cables, it was proposed to use a barrier between the cable and the gas pipes. • The effects of the type of barrier material, its thickness, and its distance from the cable on both the induction voltages and currents generated on the metal pipes are investigated. In this paper the impacts of faulty underground power cables on their neighboring metallic buried pipelines have been investigated, specifically in the event of line to ground faults of these cables, as well as the use of barrier mediums to reduce this effect. In this paper, the conduction current generated in metal pipeline as a result of faults in underground cables is studied. To reduce the induction voltages affecting the metallic pipelines, it is proposed to use a barrier between the cable and the metallic gas pipes. The effects of the type of barrier material, its thickness, and its distance from the cable on both the induction voltages and currents generated in the metal pipes are investigated. It is found that the use of XLPE barrier with thickness of 5 mm at 600 mm space from the pipeline reduces the induced voltage to be 40.02 % - 40.6 % of its value when concrete barrier is employed and 98.6 % - 98.5 % with the use of copper barrier respectively. Similar results proved that the increase of the barrier thickness is effective in reducing the induction voltage. The metal barrier has proven to be the best in reducing the effect of the induction voltage resulting from the line to ground faulty underground power cable on the neighboring metal pipes. [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]

• Protection for inverter-based resources (IBRs) based systems has many challenges. • Developed superimposed quantity-based protection elements for a system with IBRs. • Protection elements are tested in a modified IEEE 9-bus system. • Evaluated system resilience with various maximum current limits in PV controllers. The increasing penetration of inverter-based resources (IBRs) to the power grid brings challenges to protection systems. IBRs may not provide sufficient fault current to trip protective relays, leading to delays in fault isolation and increased risk of equipment damage. To overcome the challenges, superimposed quantity-based elements are developed in this paper for transmission line protection in a power grid with IBRs. The characteristics of the designed protection system are tested under fault conditions in a modified IEEE 9-bus system that includes solar photovoltaic (PV) generation, and evaluated with different maximum current limits in solar PV controllers. The applied method in this paper makes contribution to the protection application for IBR-penetrated transmission systems. Simulation results show that the modeled protection system works effectively with different penetration of solar PV, and the system resilience is enhanced under fault conditions considering the tripping response and reclosing of circuit breakers. [ABSTRACT FROM AUTHOR]

Power system reliability evaluation has been conducted based on steady-state analysis approaches such as optimal power flow calculations with minimum load curtailments. These approaches assume that a power system would return to a stable operating state after a contingency (faults, short circuits, etc.), i.e., power system dynamics are not considered. Although this assumption has been widely accepted for conventional power systems, microgrids are more vulnerable to large disturbances than conventional power systems are. In other words, the likelihood of an unstable transition from pre-event to post-event conditions is higher in the case of microgrids than in the case of conventional power grids. Therefore, it has become important to consider both generation adequacy and transient stability in microgrid reliability evaluation. This paper develops an integrated transient stability and reliability assessment approach for microgrids to capture both inadequacy and instability conditions. A Lyapunov function-based approach is developed to determine the stability region for each contingency in calculating the reliability indices. Also, a linearized AC optimal power flow model is developed for composite system reliability evaluation. This paper also provides a set of indices to quantify the impact of transient instability on the reliability of microgrids. The proposed approach is applied to the IEEE 33-bus system in the islanded mode using sedumi and YALMIP optimizers in MATLAB. The results show that 29.19% of the contingencies for which the microgrid is deemed reliable based on steady-state analyses causes unstable conditions, which justifies the need for integrating steady-state and transient conditions in microgrid reliability evaluation. • Integrated framework for microgrid reliability and transient stability assessment. • New transient energy function for large-scale microgrid stability assessment. • Introduced stability-reliability indices for microgrid analysis. [ABSTRACT FROM AUTHOR]

Given the increasing penetration of Inverter-Based Resources (IBR) and the impacts of these generators on existing fault location functions, this paper explores the potential of Machine Learning (ML) for designing one-terminal fault locators applied to systems with IBRs. For the studies, a system with a widely used topology for IBR interconnection to a transmission grid is modeled in PSCAD software, considering fault scenarios on the interconnection line with varying fault parameters, in addition to different IBR controls/topologies, grid short-circuit levels and signal noise levels. Besides the investigations on correctly choosing the attributes extracted from the signals for training ML methods, which introduces the concept of learning based on the existing method's response, the studies cover performance assessments of 35 ML methods for the fault location task, indicating the most suitable ones, and studies about the influence of the training set size on the ML methods performance. Moreover, comparative performance analyses are conducted between the ML-based methodology and state-of-the-art fault locators, highlighting the benefits of the ML-based approach in reducing errors obtained in the fault location task. Finally, the paper recommends stages for applying ML-based methods to real systems, besides providing insights and recommendations on such practical applications. • IBR significantly impacts traditional one-terminal phasor-based fault locators. • Machine learning methods can be adopted to minimize errors in the fault location task. • A new learning concept based on the response of existing methods is presented. • The practical implementation bias of machine learning methods is explored. [ABSTRACT FROM AUTHOR]

• Combined with the daily operation mode of WPC, the operation mechanism of wind-pumped storage-thermal integrated energy system with integrated consideration of PSPS and WPC is proposed. The operational decision-making of pumped storage units is designed from the viewpoint of giving full play to the regulation performance of pumped storage and enhancing wind power accommodation. • The wind-pumped storage-thermal generation is arranged according to the principle of energy-saving power generation scheduling, considering the scheduling sequence. The complementary characteristics of wind-pumped storage-thermal are fully utilized to coordinate the safety, economy and environmental protection of the system in the implementation of the multi-objective optimization. • In terms of model solving, this paper adopts inter-temporal coupling unit combination optimization to reduce the computational complexity. In adherence to the overall energy-saving principle, the sorting index is considered and the priority ranking method is used in the start-stop optimization process of thermal power units. Then, the load allocation is optimized by the improved NSGA-II algorithm. With the rapid access of wind power clusters (WPC), it is difficult for the traditional active scheduling mode to take into account the security, economy and environmental protection of the power system. Pumped storage power station (PSPS), with its flexible regulation characteristics, can reduce the volatility of wind power and enhance the capacity of wind power accommodation to a certain extent. Therefore, this paper proposes an environmental and economic scheduling strategy for the wind-pumped storage-thermal integrated energy system, and rationally arranges the sequence of the units based on the principle of energy saving and emission reduction. The scheduling strategy involves optimizing operational decision-making for pumped storage units to enhance their regulation performance. Firstly, a pre-scheduling of the wind-pumped storage bundling system is carried out, aiming at achieving the highest wind power accommodation rate, the smallest output fluctuation and the lowest pumped storage scheduling cost. Next, the joint scheduling of the wind-pumped storage-thermal system is carried out, and the priority ranking method is used to arrange the generation schedule of the thermal units according to the optimal wind-pumped storage joint output. Finally, the proposed environmental-economic scheduling model is solved by the improved NSGA-II algorithm to verify the effectiveness of the scheduling strategy. [ABSTRACT FROM AUTHOR]

• Novel in the field of power systems. • Fill the missing data for monitoring systems. • Using state-of-the-art neural network model to achieve good results in data filling. With the continuous expansion of the subway scale, a large number of stray currents invade the grid grounding transformer, resulting in a serious problem of magnetization to transformer DC bias, in order to analyze the DC bias need to use sensors to monitor the transformer operating status. In the actual monitoring process, the monitoring system is susceptible to electromagnetic interference and other environmental influences, resulting in abnormal sensor data, making the data missing, and thus affecting the operation and maintenance of the equipment decision-making. In this paper, a medium and long-time-series data-filling model for transformers based on Res-CNN-BiLSTM (abbreviated as RCBiLSTM) is proposed. In order to verify the effect of the model, the data are firstly processed as missing to simulate the problem of monitoring data missing caused by the sensor failure, and then six kinds of neural network models are respectively used to fill the missing data. The results show that with the increase of missing values, the prediction value error gradually increases and the data becomes scattered, but the model proposed in this paper can effectively reduce the impact of cumulative error on the prediction results and has an advantage in improving the accuracy of the prediction data. [ABSTRACT FROM AUTHOR]

This paper presents a novel microgrid secondary control method based on distributed sliding mode control, addressing the issue of reactive power sharing in islanded microgrids. Acknowledging the complications posed by feeder impedance mismatch, the traditional droop control mechanism fails to facilitate efficient reactive power sharing. Utilizing a distributed framework, this paper initially introduces a reactive power ratio observer, enabling the observation of global average reactive power without the need for precise reactive power calculation as required in a conventional centralized control setup. Subsequently, employing the devised reactive power ratio observer, sliding mode control is integrated to achieve effective reactive power sharing. Furthermore, this paper broadens its scope to encompass both reactive power sharing and voltage restoration, resulting in the design of a comprehensive controller. Notably, the proposed distributed sliding mode controller not only achieves accurate reactive power sharing but also exhibits significant resilience in the face of load disturbances. The simulation results conducted under various scenarios effectively validate the efficacy of the proposed distributed sliding mode control strategy. • A distributed sliding mode control for microgrid secondary voltage control. • Reactive power ratio observer for global reactive power calculation. • Comprehensively consider average voltage restoration and reactive power sharing. [ABSTRACT FROM AUTHOR]

• Electrical Power Systems Research. • This paper proposes a joint planning scheme for soft open points and energy storage to address the issue of unbalanced supply and demand in distribution networks, aiming to enhance the system's economic efficiency and stability. • This paper evaluates the proposed scheme in comparison with other literature under different electricity price conditions. The results indicate that as the electricity price increases, the economic growth rate of the proposed scheme in this paper is lower than that of the schemes in other literature, further confirming the advantages of this scheme. • This paper takes full account of the uncertainty of distributed power sources, adopts a two-stage robust model, and provides reasonable values for robust control parameters based on the planning results. With the increasing penetration rate of renewable energy, the uncertainty of its output has exacerbated power imbalances among different distribution networks. In this paper, we propose collaborative planning of soft open points and energy storage systems to balance a distribution network with source-load imbalance, aiming to improve the economy and reliability of the distribution network. Firstly, considering that distributed generation has uncertainty, the K-means is used to construct a typical day scenario, on the basis of which a collaborative planning model is established with the objective function of minimizing the annual integrated cost. Then, the original nonlinear nonconvex model is transformed into a mixed-integer second-order conical planning model by Big-M and second-order conical relaxation, and a two-stage robust optimization is used to seek the planning solution with the lowest operational cost under the worst-case scenarios, aiming to enhance the robustness of the planning model. Finally, the feasibility of the proposed planning model is verified on two source-load unbalanced IEEE 33-node active distribution network arithmetic cases. [ABSTRACT FROM AUTHOR]

• Provide an overview of NMG as a cyber-physical system and power balance methods. • Comprehensive review of hierarchical EMS for NMG and bidirectional PX scenarios. • Discuss the future hierarchical EMS trends for NMGs. A networked microgrid (NMG) is a novel cyber-physical system that provides power to urban and rural communities. The benefits of NMG that coupled with hierarchical energy management system (EMS) include increased renewable energy utilization, reliability, system efficiency, and flexibility in inter-microgrid (MG) power exchange (PX). Nevertheless, achieving secure and optimal NMG operation would require hierarchical EMS strategies that can manage uncertainties such as renewable generation fluctuations, load variation, energy prices, and flexible bidirectional PX. This paper outlines the NMG concept and various power balance methods. Subsequently, a comprehensive review of hierarchical EMS designs for NMG is presented. Four NMG models are introduced, and a comparison of various EMS strategies based on objectives, constraints, and optimization methods is also elaborated. Additionally, this paper addresses flexible bidirectional power flow between multiple MGs and the utility grid (UG) within three PX scenarios (MG-to-MG, MG-to-UG, and UG-to-MG). The advantages and challenges of hierarchical EMS for NMG with bidirectional power flow are also discussed considering grid stability, economic viability, and environmental impact. Finally, future research directions for enhancing the NMG model for optimal inter-MG PX are established. It highlights the efficient hierarchical EMS strategies and optimization algorithms for more reliable, affordable, and sustainable NMG operation. [Display omitted] [ABSTRACT FROM AUTHOR]

• This paper presents a novel technique which will significantly reduce the operating time of the distance relay for second zone internal faults over the conventional schemes. • The proposed method is capable of selecting single pole as well as three-pole breaker operation according to the faulted phases. • The proposed method has the capability to sense RCBO even during occurrence of a pole jam situation in case of three-pole breaker operation. • The technique is validated by performing Hardware-in-Loop using real time digital simulator and real time automatic controller (RTAC). The proposed algorithm is programmed in RTAC using IEC 61,131–3 industrial automation programming language. An algorithm for second zone acceleration of the distance relay utilising the sequence voltages along with healthy phases impedances is presented in this paper. Specifically, the algorithm employs variation in sequence voltage ratio indices to sense the single-pole remote circuit breaker operation (RCBO), while utilising both magnitude and angle of the healthy phase impedance for sensing three-pole RCBO operation. Additionally, the developed algorithm can also identify the faulty phases based on variations in impedance magnitude. To avoid false-trip during transient faults, impedance of the faulted phase before RCBO is compared with its value after RCBO. Performance of the proposed approach is validated for various internal and external faults covering addition of parallel link, presence of noise, different load angle, fault location, fault inception angle, fault impedance, source impedance and errors in measurement/transmission line parameters on an existing 230 kV transmission line modelled in PSCAD/EMTDC software. The results, obtained from both simulation as well as Hardware in Loop (HIL) simulation through laboratory prototype, designate that the proposed approach performs appropriately regardless of power flow direction, fault resistance magnitude, and light load conditions. The results also reveal that the suggested approach is able to accelerate trip within a cycle after RCBO event, which is comparable to or faster than many existing methods. Compared to several existing approaches in the literature, it also outperforms in terms of sensitivity, reliability and selectivity. [ABSTRACT FROM AUTHOR]

• 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]

• Absence of centralized control; different energy carriers may be owned by different entities. • Crucial to develop market-based approaches facilitating trading of various energy carriers. • Proposes Cournot game model to minimize operating costs of three interacting energy hubs. • Introduces butterfly flame optimization algorithm to discover optimal production levels. In response to the escalating demand for sustainable energy solutions, the integration of diverse energy sources has gained prominence. Energy hubs, facilitating the amalgamation of multiple sources, enhance system efficiency and flexibility. Yet, coordinating the operation of such multi-energy systems remains challenging due to complexity and uncertainties, especially with renewable sources. This paper introduces a Cournot model-based approach for optimizing three interconnected energy hubs. The objective is to minimize total operating costs while ensuring reliability and efficiency. Leveraging the Cournot model, commonly employed in energy studies for competition and pricing, we capture the strategic behavior of energy hubs. The proposed solution employs a modified butterfly flame heuristic algorithm to navigate the non-linear and non-convex optimization problem, efficiently seeking global optimal solutions. Numerical experiments on a three-hub test case validate the method, demonstrating a 3.5 % reduction in total operation costs compared to the base case and over 2.5 % cost reduction for each hub. The proposed algorithm outperforms traditional methods in terms of convergence speed and solution quality, offering a promising avenue for optimizing the operation and management of multi-energy systems. In summary, this paper introduces a novel approach grounded in the Cournot model and a hybrid heuristic algorithm for optimizing three interconnected energy hubs, effectively addressing uncertainties associated with renewable sources and ensuring reliable and efficient system operation. [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]

• Proposing a smart-grid technology based power system scheduling model. • Integrating DLR and DTR and their coordinated operation into the model. • Modeling of transformer insulation degradation and LOL in the proposed OPF. • Economic and sustainable operation of power system with zero wind power curtailment. Integration of wind power generations within today's power has faced power grid operators with challenges such as variable power generation and congestion issues. To settle these problems, the power system operators can make use of smart-grid technologies, one of which is dynamic rating of power equipment. In this paper, optimal day-ahead scheduling of wind-rich power systems is implemented at the presence of dynamic line rating (DLR) and dynamic transformer rating (DTR). Employing DTR brings about higher loading of transformer endangering its lifetime as costly instrument; hence, the thermal modeling of the transformer has been incorporated into the proposed model of this paper to avoid transformer's loss of life (LOL). All the constraints of the day-ahead AC optimal power flow have been considered to compose an optimization model which is programmed in the GAMS and optimized by appropriate solvers. Several experiments have been accomplished on the IEEE 24-bus system where the simulation results clearly demonstrate efficacy of the conducted approach. [ABSTRACT FROM AUTHOR]

The electric power sector is experiencing a rapid shift towards renewable energy resources. To accommodate this transition, the transmission system requires significant upgrades. Although enhancing grid capacity through transmission network expansion is always a solution, it can be very costly and requires a protracted permitting process. Grid-enhancing technologies (GETs) encompass a broad range of hardware and software tools that enable reconfiguration of the transmission grid and adjustment of its parameters. The proliferation of such technologies enhances transfer capability over the current transmission network, thus reducing the need for grid expansion. This paper offers a comprehensive review of grid-enhancing technologies. The paper discusses definitions of transmission flexibility and presents methods that are developed to quantify grid flexibility. The paper offers a comprehensive review of an extensive range of grid-enhancing technologies, including both principles of operation and state-of-the-art developments. Environmental impacts of grid-enhancing technologies, including renewable energy curtailment and carbon emission reduction, are also discussed. In addition to technical aspects of grid enhancing technologies, the paper also reviews the literature on the incentive challenges facing GETs adoption and efficient. Overall, the paper offers a comprehensive review of the advancements in grid-enhancing technologies, discusses the remaining critical challenges, and identifies directions for future research. • Grid-enhancing technologies (GETs) are necessary for the future grid. • GETs can enhance the transfer capability up to 50% over the existing grid. • While some GETs rely on mature technology, industry adoption remains rather limited. • GETs integration within energy management systems faces modeling challenges. • Current market and regulatory structures provide little to no incentive for adoption and efficient operation of GETs. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper addresses a comprehensive review on various adaptive grid-following inverter control schemes developed for enhancing the power quality in renewable energy generation systems (REGS). The grid interfacing inverter with various adaptive control schemes has been well researched in recent years and their performance has been found with better characteristics compared to the conventional control schemes. Better fundamental component separation (FCS), dc offset rejection, grid synchronization, amplitude tracking, frequency tracking, phase angle estimation, and low complexity are the few silent features of the adaptive-based control schemes. This survey is very useful for researchers who are working on power quality, AC and DC Microgrid, grid-connected inverter control, multilevel inverter, power electronics, and other related research areas to select the suitable controller for grid interfacing inverter. This paper also focuses the power quality issues, basic standards, power quality monitoring schemes, and solutions. Moreover, power quality improvement techniques by using the power quality conditioners with adaptive control schemes are discussed in the paper. Finally, an extensive comparative study of the recently developed control techniques is performed to select a suitable controller in terms of better FCS, dc offset rejection, grid synchronization, amplitude tracking, frequency tracking, phase angle estimation, and low complexity for grid-following inverter in REGS applications. [ABSTRACT FROM AUTHOR]

• A method to correlate indirect lightning strokes and flashovers is presented. • The method focuses on the ratio between current peak and distance from the line. • The results provided by Rusck's and Darveniza's formulas and LIOV code are compared. • The minimum collecting area for calculating the lightning performance is addressed. Lightning location systems provide an estimation of both lightning current peak amplitudes and stroke locations, which are useful information to correlate lightning strokes and faults in power distribution networks. The paper presents a novel method for assessing the correlation between a lightning-induced flashover and the lightning current-peak-to-distance ratio of indirect lightning events. This is motivated by the consideration that a minimum threshold/value of the ratio between current peak and stroke distance from the line must be reached for an insulation flashover to occur. The proposed procedure uses existing equations and models that relate induced voltage peak amplitudes, distance, current peak and other parameters. Specifically, the paper compares the results predicted by Rusck's and Darveniza's formulas with those provided by the more detailed model implemented in the LIOV code. It is found that a minimum lightning current-peak-to-distance ratio must be exceeded to trigger an insulation flashover and that Rusck's and Darveniza's formulas may be too conservative in estimating such a threshold value. The paper provides guidelines for properly estimating the minimum collecting area around the line including all hazardous events, as this information is essential for calculating the lightning performance of a power distribution line using a Monte Carlo-based approach. [ABSTRACT FROM AUTHOR]

• The improved thermal circuit model proposed in this paper exhibits a relative error of approximately 1.5 % compared to the results obtained using the finite element method. In comparison to the IEC thermal circuit model, the maximum discrepancy is 123A, with a maximum relative difference of 12 %. • The variation in seawater temperature, salinity, and pressure adjusts the thermal parameters of seawater, thereby modulating seawater thermal resistance and convective heat transfer coefficient, consequently influencing the current-carrying capacity of the submarine cable. Hence, laid cables are most affected, buried cables in less impact. • Without considering the variability in seawater properties, the calculated current-carrying capacity tends to be higher than the actual values, with a maximum error of approximately 5.5 %. Temperature has the most significant impact, accounting for 3.3 %, while the influences of salinity and pressure are around 1.1 %. The IEC 60287 standard, when calculating the steady-state current-carrying of DC submarine cables, does not take into account the influence of seawater property variations on changing the heat transfer efficiency of seawater, thereby affecting the current-carrying capacity of the cable. resulting in deviations in the calculated ampacity results. This paper considers the influence of seawater heat transfer characteristics on cable heat dissipation efficiency based on heat transfer theory, and Proposes an improved thermal circuit model for submarine DC cables that takes into account variations in seawater properties. Taking the example of a 160 kV submarine XLPE cable, the current-carrying capacity results of the improved model have an error of no more than 1.9 % compared to finite element simulation results. Under identical environmental conditions, the maximum deviation between the improved model and the IEC thermal circuit model is 123A, confirming the necessity of considering variations in seawater properties in the improved thermal circuit model. The seawater property variations studied in this paper include changes in seawater temperature, salinity, and pressure. If the impact of seawater property variations on submarine cable current-carrying capacity is not considered, the obtained current-carrying capacity results are higher, with a maximum error of 5.5 %. Among these variations, temperature has the most significant impact, with an error reaching 3.3 %, while salinity and pressure have relatively smaller impacts, with errors of 1.1 % each. [ABSTRACT FROM AUTHOR]

In this paper, the authors have adapted existing thermal models for the calculation of conductor temperature for use in electrical distribution systems for railway applications in multi-train environments. For this purpose, the authors have used existing standards such as IEEE 738 for overhead lines and have proposed a resolution methodology based on the difference equation model for cables. The authors have opted for a simplified method since the priority in this case is the resolution in systems with multiple stations, lines, and trains. For this same reason, they have chosen to decouple the electrical and thermal calculations so that the electrical variables calculated through load flows constitute the input to the thermal calculation problem. The paper reviews the existing formulation and proposes models for specific use in railway applications in a multi-train environment. A detailed analysis of the results obtained in a real case study is presented as a validation element. • Thermal model of DC conductors applicable to overhead wires and cables. • Adaptation of the model for the use in electric railway distribution system. • Application of the model to be used in a multi train environment. [ABSTRACT FROM AUTHOR]

Power system protection is crucial for maintaining the stability and reliability of the electricity grids and preventing costly disruptions. Conventional protection devices operate on pre-defined fixed settings and are no longer sufficient to ensure system stability and reliability in today's dynamic and complex electricity grids. With the rise of distributed renewable energy sources and the ability to reconfigure network topologies, an adaptive protection scheme has become necessary to quickly respond to changes in network configuration. This paper provides a state-of-the-art review of research efforts in the field of adaptive protection schemes, including the use of the IEC 61,850 protocol to incorporate automation opportunities. The IEC 61,850 protocol provides a standardized approach for communication between protection devices and the overall control system, enabling more efficient data sharing and reducing the need for manual intervention. This review paper is helpful for researchers, engineers, and policymakers involved in the development and implementation of adaptive protection schemes, enabling them to make informed decisions about the most effective strategies for ensuring the stability and reliability of modern power systems. [ABSTRACT FROM AUTHOR]

This paper introduces an advanced co-simulation environment developed to assess the cyber resilience of active distribution grids, with a focus on demand side management concepts. By integrating energy systems, communication networks, and operational technologies, the framework evaluates the impact of cyber threats on the functionality and stability of distribution grids. The focus of this paper is the newly introduced communication simulator, which provides a solution to simulate the communication flow between the different actors with a generalised representation of the protocols used. This approach enables the investigation of system architectures without requiring the specific implementation of, for example, protocol stacks. Utilising the STRIDE framework for comprehensive threat modelling, the framework then simulates cyber–physical disruptions in an abstract manner, thereby allowing for a nuanced understanding of potential vulnerabilities and resilience strategies. A case study demonstrates the application of the framework, highlighting its potential to enhance grid resilience through strategic simulation of various cyber attack scenarios. • Co-simulation to investigate the cyber resilience of demand side management. • Flexible solution for attack simulation based on threat modelling concepts. • Case study investigating a resilience enhancing fallback mechanism. [ABSTRACT FROM AUTHOR]

• Uncertainties in the power system make its state unpredictable. • Power system predictability can be improved by optimal tap setting of transformers. • Increasing predictability helps the operator to make decisions with high assurance. • power system predictability can be improved without considerably affecting losses. In recent years, renewable energy sources (RESs) such as wind turbines (WTs) have received much attention in both the operating and planning of power systems. These sources have caused many uncertainties in the operation of power systems due to their unpredictable nature. Mentioned uncertainties besides load demands uncertainty, and possible failures in power system components, make the system state unpredictable. The operational decisions are completely challenging in these situations. Any efforts to increase the network operator awareness from the system state will be completely valuable for making accurate decisions. This paper tries to increase the predictability of the power system state through optimal regulating of the voltage setpoint of automatic tap changer transformers and generators besides the reactive power of shunt capacitors. However, conventional objectives such as decreasing losses are considered, simultaneously. This paper uses the K-medoids data clustering method to evaluate the effect of uncertainties. Also, the correlation between input uncertain variables is considered and handled by the Cholesky decomposition technique combined with the Nataf transformation technique. The multi-objective optimization problem is tackled using an improved version of the non-dominated sorting genetic algorithm (NSGA-II). To ensure for validity of the results, studies are repeated using the multi-objective particle swarm optimization (MOPSO) algorithm as another evolutionary-based method. The proposed approach is applied to the IEEE 14 and 30 bus standard system. The results showed that the predictability of the power system can be considerably increased while keeping the losses approximately at its minimum amount. [ABSTRACT FROM AUTHOR]

• Importance and challenges of relay coordination in Microgrid. • Overview of different adaptive schemes opted for relay coordination. • Different optimization techniques which have been used for the calculation of relay settings. • Evolvement of algorithms from conventional to Hybrid methods which combines two different metaheuristic methods to solve a complex, non- linear optimization problem in an efficient way for optimized relay coordination. • Future directions of research for further modifications possible in Algorithms are stated at the end. Concept of microgrids (MGs) have gained significant attention in order to enhance the resilience and efficiency of modern Power Systems. MG offers bi-directional power flow so an effective protection and control becomes a vital requirement to ensure the reliable operation of MGs. Relay coordination being an integral part of the protection system, plays a critical role in prevention of power disturbances and equipment damage due to the presence of bi-directional power flow. This review paper focuses on the optimization of relay coordination in MGs, and highlights the importance of adaptive and intelligent approaches involved for the efficacy of MG operation. This paper overviews different schemes used to adapt while determining the DOCRs settings with different contingencies considered. The paper depicts the key challenges associated with relay coordination in MGs; varying fault currents, and bidirectional power flows. To overcome these challenges, recent researches have explored advanced techniques that includes intelligent algorithms to operate on collected real-time data. Additionally, the impact of communication technologies for relay coordination in real-time has been discussed for Grid connected and Islanded mode of operation. This review covers a wide range of optimization methods such as; Traditional, Meta-Heuristic, and Hybrid algorithms, which allows adaptive and reliable protection schemes during different modes of MG operations. [ABSTRACT FROM AUTHOR]

• An analytical criterion to examine the transient synchronization stability of the island 100 % RPG system connected to the sending-end of Zhangbei MTDC network is proposed. • The paper reveals that excessive reactive current generated by the wind farm may cause the loss of synchronization of the island 100 % RPG system during the fault. • The current limiter's parameters in the grid-forming MMC and the current injections of the wind farm during the fault should be coordinately determined in order to maintain the transient synchronization stability of the island 100 % RPG system during the fault. This paper examines the transient synchronization stability (TSS) of an island 100 % renewable power generation (RPG) system that is connected to the Zhangbei multi-terminal direct current (MTDC) system. A large-signal model of the system is derived, based on which an analytical criterion for evaluating the TSS of the system is proposed. From the proposed TSS criterion, the current injection of the RPG, the current injection of the MMC, the parameter settings of the PLL, and the fault ground resistance and distance are identified and examined as four key factors affecting the system TSS. In addition, analysis in the paper highlights the importance considering the reactive current generated by the RPG during the fault, because excessive reactive current may causes the instability of the island 100 % RPG system. To demonstrate and evaluate the proposed TSS criterion and the analytical conclusions made, study cases to examine the TSS of the island 100 % RPG system connected to the Zhangbei MTDC are presented in the paper. [ABSTRACT FROM AUTHOR]

• In response to the reviewer's valid concerns, we have introduced a clear and comprehensive note in the paper, elucidating our deliberate departure from the conventional theoretical approach traditionally embraced by the industry, which predominantly centres around the lightning current sharing rule (50:50). • This advanced modelling approach stands out for its capability to meticulously scrutinise a multitude of parameters and explore diverse what-if scenarios. By doing so, we not only elevate the precision and depth of our analysis but also broaden the scope of our investigation to encompass a more comprehensive range of potential factors and conditions. • The focus of our paper is primarily on emphasising the approach to mitigate the risk of voltage stress across insulation flanges, particularly examining the influence of connecting lead lengths. It's crucial to interpret the absolute values in the results with care, as they are indicative of an extreme scenario involving high impulse current (200 kA) and steepness (20 kA/μs). While these values represent an extreme case, the main takeaway from our calculations remains valid. There is a quantifiable reduction in the range of 34 % when implementing the proposed mitigation measures, signifying a substantial contribution to risk mitigation. • We have incorporated a dedicated section into the paper, labelled as 4.1 sensitivity analysis. Insulating flanges serve as crucial components, strategically positioned between two segments of a pipeline to ensure effective electrical isolation. These elements play a vital role in facilitating the optimal performance of the cathodic protection system of buried pipeline networks. Moreover, an isolating spark gap is commonly integrated between adjacent pipeline sections to mitigate the stress voltage induced on the insulating flange during lightning strike events.. Despite this protective measure, certain scenarios may arise where the voltage drop across the isolating spark gap's connecting cables surpasses the insulating flange's dielectric strength, leading to undesirable failures. The magnitude of this voltage drop is contingent upon various factors, including the parameters of the incoming surge as well as the length of the connecting cables. In this paper, we present both straightforward theoretical calculations and intricate modelling techniques that can be employed to assess the lightning risk associated with the insulating flanges of pipelines that incorporate isolating spark gaps. [ABSTRACT FROM AUTHOR]

• This research paper proposed a novel computational technique for evaluation of the corona generated ionized electromagnetic field environment which initiates serious ill health environment under EHV/UHV DC transmission lines. • The proposed new computational technique was developed by modelling the dynamic behavior of the corona discharge phenomenon using gas ion bimolecular collision theoy concept which offers program less simple equations. • This developed computational technique offers unique equation solution which estimates corona generated ionic currents for any existing and upcoming HVDC transmission lines. This new computational analysis offers economical benefits to the line design engineers. • Actual experimental investigations are carried out at extra and ultra high potential levels to validate the accuracy of the proposed computational technique. • The proposed computational technique offered high computational accuracy compared to other techniques which are proposed elsewhere in the world and the computed results shown exact measured values. Corona on UHVDC transmission line conductors initiates corona power loss and the inevitable ionic current flow environment at ground level. To limit this substantial flow of ionic current at ground levels, it is necessary to establish an appropriate line design configuration, including the diameter of the line conductor and the height level above the ground. It is a tedious and expensive process to establish this appropriate line design solely based on experimental findings. Hence, the computational based numerical analysis with the support of final experimental validation aids in arriving at a safe and optimal transmission line design dimension configuration. Thus, the ionic current flow environment of UHVDC transmission lines may be characterized by ionized space charge density, ionic current flow, and electrical field distribution. To estimate this ionic current flow, it is necessary to estimate the ionized space charge density in the ionization region, which incorporates the solution of the Poisson's equation. It is intricate to solve Poisson's equation with known boundary conditions: as ionization process depends on the atmospheric parameters also. Multiple computational techniques are developed to estimate the corona generated ionic current environment under the HVDC lines by waiving these atmospheric parameter effects and claims the lack of computational accuracy. In this paper, the unipolar corona equation, usually called Poisson's equation was solved by estimating the space charge ion density using the concept of gas bimolecular collision theory. The gas bimolecular collision theory inculcates the procedure to estimate the collisional reaction rate constant between the gas molecules at given atmospheric temperature and pressure parameters. Therefore, this paper developed a unique equation solution for the estimation of transition of the ionic current magnitudes at known atmospheric temperature and pressure ambient conditions. This unique equation solution prevents the multiple actual testing procedures offers to obtain safe and optimal line design dimension configurations. Multiple experimental studies are carried out up to ± 900 kV to compare the computed results in the outdoor and indoor climatic conditions at the ultra-high voltage laboratory, CPRI. Also, the computed results are compared with the results published in the literature. Based on the comparison of results, the developed computational technique exactly matches the experimental results and claims improved accuracy compared to other computational techniques. [ABSTRACT FROM AUTHOR]

• A new flexible lexicography method for multi-objective optimization problems in DNR is introduced. • The proposed method increases the flexibility of the operator to better control the electrical indices of the network by distribution network reconfiguration. • The effect of nonlinear load and harmonic DG injection in DNR is investigated. • The effect of unbalance in line, loads, and single-phase DGs in DNR is studied. • The distribution system operator should consider network unbalance in the reconfiguration to more reduction of power losses. Reconfiguration is a low-cost method to reduce power loss in distribution network (DN). Harmonics and unbalancing cause additional losses in DNs. Therefore, it is necessary to consider these two factors in distribution network reconfiguration (DNR). In this paper, the effect of reconfiguration in two harmonic polluted medium and large scale DN is evaluated. In addition, the effect of harmonic injection of distributed generation (DG) is studied. Moreover, the effect of reconfiguration in unbalanced DN in the presence of single-phase DGs is investigated, and it is concluded that distribution system operator (DSO) should consider network unbalance in DNR to more reduction of power losses. Furthermore, a new flexible lexicography method is introduced to solve multi-objective problems, especially in DNR. In the proposed method, the DSO determines the priority of each goal in comparison to the other goals, instead of using weighing factors of them. This method is effective for power quality goals which cannot be illustrated as cost function. In this paper, validation of the proposed method in IEEE 69 bus and 95 bus practical harmonic polluted DN and 25 bus unbalanced DN in presence of three-phase and single-phase PVs are investigated. Results show the effectiveness of the method in increasing the flexibility of DSO in DNR to improve power quality goals such as harmonics and unbalance, as well as reduce power losses. [ABSTRACT FROM AUTHOR]

This paper studies a privacy-preserving distributed state estimation (SE) problem in smart grid systems with an AC power flow model. To enhance the precision of SE, a sensor data fusion approach is employed to integrate the sampled data from supervisory control and data acquisition (SCADA) and phasor measurement units (PMUs). Then, through iterative information exchange among local and neighboring areas, all interconnected areas can achieve consensus on unbiased estimations while avoiding the issue of excessively large data dimensionality caused by centralized data acquisition. In addition, the proposed approach combines with the average consensus algorithm, significantly reducing the computational burden and enabling real-time distributed SE, and the incorporation of differential privacy further mitigates potential privacy leakage risks during the information transmission process. Simulation results on IEEE 14-bus and IEEE 118-bus systems demonstrate that the proposed approach not only achieves excellent estimation accuracy but also significantly reduces the convergence time, while maintaining enhanced the capability of privacy-preserving. • The model developed in this research is more closely with the operational patterns of real-world systems. • The distributed algorithm proposed in this paper does not rely on local observability or a central coordinator. • The proposed internal-merger and external-modification (IMEM) algorithm significantly reduces the number of iterations during simulation. • Differential privacy further enhances the security of local private data. [ABSTRACT FROM AUTHOR]

This paper presents an original energy management methodology to enhance the resilience of ship power systems. The integration of various energy storage systems (ESS), including battery energy storage systems (BESS) and super-capacitor energy storage systems (SCESS), in modern ship power systems poses challenges in designing an efficient energy management system (EMS). The EMS proposed in this paper aims to achieve multiple objectives. The primary objective is to minimize shed loads, while the secondary objective is to effectively manage different types of ESS. Considering the diverse ramp-rate characteristics of generators, SCESS, and BESS, the proposed EMS exploits these differences to determine an optimal long-term schedule for minimizing shed loads. Furthermore, the proposed EMS balances the state-of-charge (SoC) of ESS and prioritizes the SCESS's SoC levels to ensure the efficient operation of BESS and SCESS. For better computational efficiency, we introduce the receding horizon optimization method, enabling real-time EMS implementation. A comparison with the fixed horizon optimization (FHO) validates its effectiveness. Simulation studies and results demonstrate that the proposed EMS efficiently manages generators, BESS, and SCESS, ensuring system resilience under generation shortages. Additionally, the proposed methodology significantly reduces the computational burden compared to the FHO technique while maintaining acceptable resilience performance. • Proposing a resilient EMS utilizing BESS and SCESS for modern ship power systems. • Proposed EMS tackles practical ESS constraints (SoC balancing, SCESS SoC priority). • RHO enhances ESS-GEN coordination, addressing real-time, large-scale challenges. [ABSTRACT FROM AUTHOR]

The protection of high-voltage direct current (HVDC) grids is a crucial aspect in ensuring the reliable and efficient operation of modern electrical energy transmission systems. The high amplitude and rate of change of fault current as well as the presence of multiple paths for fault current contribution of voltage-sourced converters make the protection of HVDC grids with meshed configuration a challenging task. This paper develops a protection scheme for these grids that has three modules: (i) low-resistance fault detection module based on the amplitude of the voltage across the current limiting reactor (CLR) at the line terminal, (ii) high-resistance fault detection module based on quantifying the severity of the CLR voltage signal change, and (iii) fault classification module. No need for communication links increases the reliability and operating speed of the proposed scheme. Moreover, severity measurement based protection increases the sensitivity of fault detection. The ability to faulty line identification in the meshed configuration verifies the selectivity of the proposed scheme. In addition, its robustness is verified due to low susceptibility to measurement noise, DCCB operation, AC fault, various CLR sizes, and power reversal. Several pole-to-pole and pole-to-ground fault scenarios with various fault resistances at different fault locations are conducted to verify the reliable performance of the proposed HVDC protection scheme. • The paper develops a single-end protection scheme for VSC-HVDC grids. • It is based on processing the voltage across current limiting reactors (CLRs). • It can detect both severe and high-resistance fault conditions. • It is robust to the measurement noise, DCCB operation, AC fault, various CLR sizes, and power reversal. • It does not require a high sampling rate. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy sources (RESs) in the global power grid is transforming the traditional landscape of power generation. This shift from rotating synchronous generators to inverter-based RESs presents a unique challenge in maintaining the grid frequency stability due to the decline in system inertia. The stochastic nature of power generation, load demand, and grid inertia poses further challenge in ascertaining the frequency stability. This paper addresses this challenge by proposing indices that assess the sensitivity, resiliency, and permissibility of grid frequency under different RES penetration levels. These indices provide valuable insights into the stability of power grids and highlight the increased vulnerability of grid frequency to disturbances with increased RES integration. Monte Carlo simulation (MCS) is used to incorporate intermittencies and uncertainties associated with the load demand and RES generation. Furthermore, the paper presents a methodology to determine the required level of inertial support for maintaining the frequency reliability in the presence of RESs. The application of the proposed stability indices and methodology in a case study, which utilizes a modified IEEE 39-bus test system emulating a real-world power grid with diverse load types and RESs, validates their effectiveness. • Introduced indices for grid frequency stability in varying RES conditions. • Proposed a daily grid stability framework considering RES/load uncertainties. • Methodology presented to assess inertial support needs with RES integration. [ABSTRACT FROM AUTHOR]