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This document is a guest editorial from the journal IET Generation, Transmission & Distribution. It emphasizes the need to improve the reliability and resilience of modern power systems in the face of various threats. The editorial highlights the importance of modeling, assessing, and enhancing the reliability and resilience of power grids that are increasingly incorporating grid-edge resources. The document also provides a summary of the papers included in a special issue of the journal, which cover topics such as planning reliable energy systems, analyzing power grid operations, and enhancing service restoration and grid-support load response. Additionally, the text discusses the issue of equity in power distribution system restoration processes and proposes a model called the equity-aware power distribution system restoration model. The model aims to balance equity and resilience in restoring power after outages by focusing on fair distribution of energy resources while maintaining operational efficiency. The text also includes brief biographies of several authors who have contributed to the field of power electronics and power system reliability. [Extracted from the article]

Multi‐terminal high‐voltage direct current technology based on voltage‐source converter stations (VSC‐MTDC) is expected to be one of the most important contributors to the future of electric power systems. In fact, among other features, it has already been shown how this technology can contribute to improve transient stability in power systems by the use of supplementary controllers. Along this line, this paper will investigate in detail how these supplementary controllers affect electromechanical oscillations, by means of small‐signal stability analysis. The paper analyses two control strategies based on the modulation of active‐power injections (P‐WAF) and reactive‐power injections (Q‐WAF) in the VSC stations which were presented in previous work. Both control strategies use global signals of the frequencies of the VSC‐MTDC system and they presented significant improvements on transient stability. The paper will provide guidelines for the design of these type of controllers to improve both large‐ and small‐disturbance angle stability. Small‐signal stability analysis (in Matlab) has been compared with non‐linear time domain simulation (in PSS/E) to confirm the results using CIGRE Nordic32A benchmark test system with a VSC‐MTDC system. The paper analyses the impact of the controller gains and communication latency on electromechanical‐oscillation damping. The main conclusion of the paper is that transient‐stability‐tailored supplementary controllers in VSC‐MTDC systems can be tuned to damp inter‐area oscillations too, maintaining their effectiveness. [ABSTRACT FROM AUTHOR]

Electric power information has garnered particular interest in conventional electrical power systems because it plays a crucial role in the electric power industry. Additionally, electric power communication networks ensure the overall power system's reliability and safety. The concepts and techniques used in digital twin (DT)‐based online tools for electric power communication networks are introduced in this paper. Moreover, online DT tools are proposed as daily learning and training resources for both new staff and communication commissioners, which can be used for the internet and the company intranets. Users can control DT and physical equipment simultaneously, and device status can be seen in real time. The design, modelling, control principles, data collection, and visual display of the DT tools are all covered in this study. To validate the applicability of the proposed framework, a case study for optical fibre damage and the recovery process in a typical communication interruption malfunction is investigated. The research presented in this paper has the potential to provide useful tools and new paradigms for designing online DT training and education systems. [ABSTRACT FROM AUTHOR]

An introduction is presented which discusses various reports published within the issue including microgrid and virtual power plant for power supply, voltage reactive power control of a power system, and virtual power plant real-time energy management along with a brief profile of guest editors.

Reactive power management (RPM) in electric power systems is usually based on a rule‐based control derived from the transmission system operator's (TSO) experience. This approach faces challenges as the number of decisions and the complexity of the system operation is increasing. With the increasing generation from renewables and the evolution of electricity markets, the available resources must be optimally utilized. This paper compares the optimization‐based approach (OBA) and the experience‐based expert approach (EBA) for RPM. The OBA is based on security‐constrained optimization with minimum redispatch cost as the objective function for a reference contingency. In contrast, the EBA's actions are based on the system operator's experience. Comparison is made in terms of the generator redispatch cost, active and reactive power redispatch volume, active power losses, nodal voltages, and the number of actions to ensure secure operation. The analysis using a reduced model of an actual transmission system shows that OBA is more beneficial than EBA, with up to 22% and 42% reduction in redispatch cost and volume, respectively. Moreover, the control decisions from both approaches are seen to be similar. This study aims to show the usefulness of the OBA and motivate TSOs to move towards optimization‐based reactive power management. [ABSTRACT FROM AUTHOR]

The locational marginal price (LMP) theory is the foundation of nowadays electricity markets. With the rapid growth of intermittent renewable generation, new features are emerging in power systems, such as the uncertainty of power supply, the scarcity of flexibility, and the increase of distributed generation. In this situation, the electricity pricing scheme needs to be augmented with new features to meet requirements of incentive compatibility, cost causation‐awareness, revenue adequacy, and transparency in a new market environment. Though a broad spectrum of literature has investigated extensions of the LMP addressing different challenges, a panorama of these extension directions is absent. To this end, this paper provides a systematic review of existing LMP extension research from four aspects, including pricing with non‐convexity, pricing with multiple intervals, pricing with uncertainty, and pricing in distribution systems. These extension directions are derived from the impacts of the power system evolution on dispatch and pricing models. For each extension direction, the motivation and basic problem setup are introduced, followed by a critical survey of related research progress. Future directions and research gaps of the LMP extension are also indicated in this paper. [ABSTRACT FROM AUTHOR]

Earlier works have reported that rectifier AC faults also can cause commutation failure during fault‐off recovery process. Whereas the occurrence of CF is merely ascribed to inverter AC faults in conventional wisdom. Note that the existing CF mitigation approaches are designed mostly by the evolution of inverter electrical quantities, which will fail to take action to CF caused by rectifier faults, posing threat to the operation of power system. Thus, the paper firstly presents the essential reasons for CF caused by rectifier ac faults, combined with the fault information transmission process and control response. It is found that DC current surge and improper control interaction are the main reasons. Accordingly, a novel current cooperative optimization (CCO) control strategy is proposed, which aimed at reducing the risk of CF caused by rectifier ac faults. Simulation results verify the correctness of the mechanism and the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including dynamic synchrophasor estimation, voltage controllability and renewable energy.

Voltage stability in general is of paramount importance with increasing penetration levels of variable-speed wind power generators (VSWGs) in power systems. Limited knowledge exists considering the impact of VSWGs on long-term voltage stability (LTVS) of power systems, focusing on doubly fed induction generators and full-converter wind generators. This paper presents the results of a comprehensive study on the impact of VSWGs on LTVS. Integration of wind generators while operating the existing synchronous generators improves the LTVS. However, it is unlikely that power systems will retain all existing synchronous generators operating, with high wind penetration levels. Therefore, this study compares the capability of the synchronous generators and VSWGs on LTVS by considering the dynamic reactive power capabilities. The significance of overload capability of synchronous generators on LTVS is highlighted. It is also illustrated that integrating wind farms at remote and local locations from load centres has distinct impacts on LTVS. Replacement of synchronous generators located in close proximity to load centres has a detrimental effect on LTVS. Furthermore, this study demonstrates the impact of different wind generator loading levels on LTVS. The study outcomes highlight several distinct factors which influence the LTVS of power systems with high wind penetration levels. [ABSTRACT FROM AUTHOR]

Conventional approaches for measurement-based load modelling uses measured voltage (V) as the input to calculate the load model output - P and Q powers. This assumes that the P and Q response is a function of V. In fact, there is an inherent interaction among the three variables (P, Q, and V) especially when motor load occupies a large proportion. With increased penetration of wind power, the fault-induced dynamic voltage response is becoming a serious concern given the low-voltage-ride-through (LVRT) requirement of wind turbines. This paper firstly shows that given different load model parameters, the V responses can vary significantly. Then, an improved method is proposed for more accurate measurement-based load modelling. The proposed method incorporates the V response into the load model output, therefore is able to accurately reflect the dynamic voltage trajectories. Given the load model parameters, the system responses of P, Q, and V are all simulated via time-domain simulations using industry-grade software, and problem is to search the load model parameters to minimise the fitting error between the simulated and measured system responses. A trajectory sensitivity index is used to identify the well-conditioned parameters, and a parallel-differential evolutionary algorithm is designed to solve the model. [ABSTRACT FROM AUTHOR]

This paper proposes an intelligent Deep Learning (DL) based approach for Data‐Driven Security‐Constrained Unit Commitment (DD‐SCUC) decision‐making. The proposed approach includes data pre‐processing and a two‐stage decision‐making process. Firstly, historical data is accumulated and pre‐processed. Then, the DD‐SCUC model is created based on the Gated Recurrent Unit‐Neural Network (GRU‐NN). The mapping model between system daily load and decision results is created by training the DL model with historical data and then is utilized to make SCUC decisions. The two‐stage decision‐making process outputs the decision results based on various applications and scenarios. This approach has self‐learning capabilities because the accumulation of historical data sets can revise the mapping model and therefore improve its accuracy. Simulation results from the IEEE 118‐bus test system and a real power system from China showed that compared with deterministic Physical‐Model‐Driven (PMD)‐SCUC methods, the approach has higher accuracy, better efficiency in the practical use case, and better adaptability to different types of SCUC problems. [ABSTRACT FROM AUTHOR]

The rampant growth in penetration of gas‐fired distributed units (GFDUs) is recasting the role of the integrated energy service provider (IESP) as a price‐maker player. Nevertheless, it is threatening the well‐being and reliability of the natural gas networks (NGNs). In this regard, this paper investigates the strategic participation of integrated 20‐node NGN and an 33‐bus active distribution system (ADS) in the day‐ahead wholesale market (WM), which consists of a six‐bus transmission network (TN), through a bi‐level optimization framework. The upper‐level objective is to minimize the operational costs of the IESP as well as the cost of energy that is purchased/sold in day‐ahead WM. The lower‐level problem models the optimal response of the wholesale market operator (WMO) that has the objective of maximizing social well‐fare by clearing the day‐ahead wholesale market. To alleviate the NGN's pipeline congestion, the linepack capability of the pipelines is deployed, while demand response program (DRP) and interruptible loads (IL) are integrated into the ADS side. As a computationally efficient method, robust optimization (RO) is utilized to handle the uncertainties. The results emphasize the necessity of integrating NGN into this problem. Eventually, different case studies illustrate the impact of line pack and DRP in reducing market‐clearing price. [ABSTRACT FROM AUTHOR]

Due to the growing proportion of uncertain and fluctuating renewable energy sources in the power system, reasonable generation expansion considering the uncertainties is desperately needed. This paper proposes a novel three‐stage wind‐thermal generation expansion planning model based on representative day unit commitment that incorporates the uncertainty of wind power and load and the probabilistic reliability criteria. The probabilistic reliability criteria are considered by simulating random outage events of thermal units using a robust approach. The consequent robust reliability model is reformulated as mixed‐integer linear programming models and integrated into the multi‐stage generation expansion planning model. A decomposed strategy based on the Benders decomposition is adopted to tackle with the large‐scale original model. Case studies are performed on both the revised IEEE 14‐bus and IEEE 118‐bus test systems to validate the effectiveness of proposed model and method. Numerical results show that the proposed generation planning method balances the economy and reliability of the system. [ABSTRACT FROM AUTHOR]

High‐voltage direct current breaker is among the essential components of high‐voltage direct current grids. Such a breaker generally needs a direct current reactor to reduce the fault currents rate. However, direct current reactors have destructive effects on the multi‐terminal high‐voltage direct current grid dynamic stability, and in such a system, despite the variety of controllers, the system dynamics are highly sensitive to the operating point. Therefore, additional damping control will be needed. This paper proposes a modification to be applied to the traditional droop controller of high‐voltage direct current grids to cope with the influence of these large reactors, improving the direct voltage stability and decreasing power variations in the transient events by introducing a direct current power system stabilizer. The proposed method for direct voltage control has been investigated through the analytical model of the system. Stability improvement has been studied following the application of the proposed method by investigating zeros, poles, and frequency response analysis. Moreover, a method is proposed for optimal design and optimal placement of direct current power system stabilizer. The system analysis and time‐domain simulations demonstrate a decent damping improvement attained by the proposed method. All simulations and analytical studies are conducted on Cigré DCS3 test high‐voltage direct current grid in MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

In the power system, the harmonic is one of the important concerns of power quality, which has a significant impact on the safe operation of power grids and the energy efficiency for users. When there are not enough special harmonic monitoring devices installed on public transport, it is important to identify the harmonic source and assess the harmonic contribution based on the load data of the user's electricity meter. This paper proposes a data selection and matching idea based on change‐point monitoring (CPM), canonical correlation analysis (CCA) and dynamic adjusted shape context (DASC) for determining the harmonic contributions of individual customers and utilities. In the proposed approach, the CPM is used to select the valuable data by detecting the violent fluctuation area of harmonic voltage and the DASC to determine the harmonic contribution of individual customers by matching the user load sequence and harmonic voltage sequence based on CCA, filtering the harmonic contribution from the utility side. Simulation data is used to evaluate the performance of the method and a real‐world case study is also conducted. It is found that the proposed technique can be used to reveal the harmonic impact of the loads if data is selected resonably. [ABSTRACT FROM AUTHOR]

Reliability is one of the most important factors to judge a power system. So, assessing reliability is an important task in power system planning. Many techniques have been developed to enhance the reliability of a power system. Some of those techniques depend on integrating new components and other techniques depend on changing some characteristics of existing components. One of the techniques depending on integrating new components is to integrate an energy storage system (ESS) with a power system. If the ESS is optimally sized to minimise the investment and operating cost, it enhances the reliability of the power system with a notable difference. This paper illustrates how to optimally size an ESS to be integrated with a gridconnected microgrid using the mixed-integer linear programming method. Moreover, load uncertainty is considered and the optimisation problem is solved using two different approaches to optimally size the ESS. Reliability indices of the microgrid are calculated before integrating it with the ESS and after integrating it to illustrate the enhancement of the reliability indices. Simulation results depict the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The data is not always shared among sub-networks due to concerns about information privacy or difficulties in synchronous information exchange. It is difficult or even impossible to obtain the probabilistic power flow (PPF) by the centralised analysis. In this paper, an equivalent model considering static power-frequency characteristics (SPFCs) and renewable uncertainties is proposed. In this model, SPFCs of equivalent loads and generators are derived to retain SPFCs of original external loads and generators, respectively. In addition, probabilistic characteristics and correlations of equivalent loads are formulated based on Cholesky decomposition to preserve original external renewable uncertainties. The proposed model is further applied to PPF and then PPF can be solved via Monte Carlo simulation method, which makes that the PPF results can be obtained when the detailed data of the original external network cannot be shared. Owing to efficiently preserving the external SPFCs and renewable uncertainties in the proposed equivalent model, the accuracy of PPF results can be guaranteed. Simulation results of IEEE 14-bus and IEEE-118 bus systems demonstrate the effectiveness and superiority of the proposed equivalent model and its applications to PPF, compared with existing well known equivalent models and their applications to PPF. [ABSTRACT FROM AUTHOR]

This paper focuses on the impact of control system on small-signal stability of the Hybrid Multi-Infeed HVDC(H-MIDC) system, in which the Line-Commutated-Converter based HVDC (LCC-HVDC) and Voltage-Sourced-Converter based HVDC (VSC-HVDC) links feed into an AC system in close mutual proximity. A comprehensive linearized small-signal model is developed for an H-MIDC system. Based on the eigenvalue analysis and participation factor analysis, the inherent oscillatory modes of the H-MIDC system are revealed. Then, the impact of the most sensitive control system parameters on the leastdamped modes are investigated. The studies show that (i) the proportional gains of PLL functions of LCC and VSC stations, and AC voltage outer loop controller of VSC station are highly coupled, and presents the most sensitivity to the least damped modes; (ii) parameters of PLL in LCC station, and outer loop of AC voltage control and PLL in VSC station can highly impact the damping of the oscillatory modes and even cause instability, and (iii) smaller PLL gains in LCC and VSC stations, and smaller proportional gain of AC voltage control of VSC station are preferable and can enhance damping of dominant modes. [ABSTRACT FROM AUTHOR]

The concept of flexibility is defined as the power systems' ability to effectively respond to changes in power generation and demand profiles to maintain the supply–demand balance. However, the inherent flexibility margins required for successful operation have been recently challenged by the unprecedented arrival of uncertainties, driven by constantly changing demand, failure of conventional units, and the intermittent outputs of renewable energy sources (RES). Tackling these challenges, energy storage systems (ESS) as one important player of the new power grids can enhance the system flexibility. It, therefore, calls for an efficient planning procedure to ensure flexibility margins by considering ESS's role in modern power systems. This paper proposes a novel mixed integer linear programming (MILP) model for transmission expansion planning (TEP) framework taking into account the role of compressed air energy storage (CAES) integration on improvements in system flexibility. The proposed framework is housed with a quantitative metric of grid‐scale system flexibility, while a new offline repetitive mechanism is suggested to account for the N − 1 reliability criterion. The model is applied to different test systems, where the numerical results demonstrate the impacts of CAES units on system flexibility, investment plans, and the total costs. [ABSTRACT FROM AUTHOR]

Power flow calculations are an essential stage in many planning and control applications for distribution systems.To use these in control applications, however, the calculation time needs to be improved, and this can be done by the use of a trained ANN. This paper presents the considerations for constructing ANNs for DSs, and describes a method for training the system in order to support switching events representing a change in topology. The solutions for three DSs, balanced as well as unbalanced, are presented and the various considerations affecting the most appropriate ANN construction are discussed. The results are compared to the solution from the classical complex Newton‐Raphson and the fixed‐point iterative methods. The solutions have very high precision and good results are found for switched laterals. The computational performance is also compared and an improvement of two orders of magnitude is observed. [ABSTRACT FROM AUTHOR]

In a transmission line, sag is intentionally provided to relax the tension on the wire when placed between two terminals. However, thermal stress and extreme weather conditions can cause increases in transmission line sag, which can eventually damage transmission line infrastructure. In this regard, this paper examines a number of sag measurement techniques based on physical or optical properties and integrated with signal processing and communication technologies. The performance of different sag measurement methods is compared in terms of accuracy, precision and key feature. Several challenges and limitations of the existing sag measurement mechanisms are reported. A number of recommendations to address the identified challenges are made. Moreover, an efficient communication framework for sag related information exchange is proposed. This comprehensive review of the sag measurement techniques will facilitate the evolution of new and efficient real‐time sag measurement and monitoring methods. [ABSTRACT FROM AUTHOR]

Renewable‐dominant mixtures with hydrogeneration and variable renewable energies (VREs) have been the focus for decarbonization of power systems. Hydrogeneration with large reservoir becomes the main regulating source. The long‐term generation scheduling (LTGS) on monthly reservoir regulation for the approaching year becomes more significant because reserving adequate water storage is related to intramonth balance, considering that hydrogeneration has to supplement deficit energy of VRE generation. However, conventional LTGS method that is based on monthly averages overestimates the hydrogeneration's intramonth energy supporting capability, whereas rolling short‐term generation scheduling method cannot account the long‐term effect of reservoir regulation decisions. This paper proposes a new LTGS method accounting intramonth imbalance risk that the energy deficit of VRE generation exceeds the maximum supporting energy of hydrogeneration. Since intramonth imbalance risk is coupled with LTGS in an uncertain and implicit way, intramonth extreme scenarios are introduced based on distribution quantiles of natural inflow of reservoirs and VRE generation, and the probabilistic intramonth imbalance risk constraints can be transformed as the hydrogeneration must supplement energy deficit of VRE generation during the extreme scenarios. A case study is conducted on a Wind‐PV‐Hydro energy base of southwestern China. The proposed method is found able to improve the feasibility and reliability of LTGS compared to other LTGS methods. Moreover, the high calculation efficiency of conventional LTGS method is inherited. [ABSTRACT FROM AUTHOR]

With the advent of small‐scale heat and electricity producers in distribution energy systems, the interdependencies between energy carriers have been increased. Moreover, the rapid deployment of micro CHP, electric heat pumps, electricity‐to‐heat appliances etc., calls for new local market frameworks to be employed in distribution energy systems. In response, this paper presents a new energy market framework based on the concept of peer‐to‐peer negotiations to facilitate energy transactions between agents at the distribution level while addressing the interdependencies between different energy carriers. Moreover, linear optimization problems are proposed to investigate the optimal strategies of market participants with various configurations. These optimization problems not only obtain the optimum strategy of agents to participate in the day‐ahead peer‐to‐peer electricity market, the day‐ahead heat market, and gas distribution systems but also obtain their optimal operation scheduling for the entire next day. The numerical results successfully demonstrate the applicability and merits of the proposed market framework. [ABSTRACT FROM AUTHOR]

Due to the increasing interactions between the natural gas system (NGS) and electric power system (EPS), the failures of power‐lines or gas pipelines in one system may influence another system and consequently trigger widespread disruptions. Hence, identifying these critical components and protecting them from malfunctions are essential to prevent the collapse of integrated gas and power systems (IGPSs). Considering the effects of both network topologies and operational features on the resiliency evaluation, a novel assessment framework is proposed in this paper to screen out critical power‐lines and gas pipelines. First, the framework of IGPSs is introduced and an optimal energy flow (OEF) model is constructed to quickly obtain the operation states under various disturbances. Furthermore, the resiliency metrics (RMs) are developed from structural and operational perspectives respectively. Specifically, structural RMs consider the coupling topologies to capture the structure‐related resiliency, while operational RMs analyse the resiliency related to gas and power flow to capture physical operation characteristics. Finally, an assessment algorithm synthesizing all the metrics is proposed to quantify the comprehensive resiliency, based on which critical power‐lines and pipelines (CPPs) can be detected. The effectiveness of the proposed approach is validated by an IGPS test system. [ABSTRACT FROM AUTHOR]

In this paper a novel method is proposed to estimate the rotor speed of synchronous generators in steady state and dynamic conditions using phasor measurement unit's data. This method uses the synchronous generator model to find the relationship between generator rotor speed and frequencies at different buses of the power system. The principles of the proposed method are first presented through a simple network consisting a generator connected to a transmission line. Afterward the general formulation is developed. To demonstrate the effectiveness of our method, IEEE 9‐bus and IEEE 39‐bus power systems are used as the benchmark systems. Different tests are carried out under three conditions including, normal condition, presence of measurement errors and uncertainty of the power system parameters. As well, the estimation results are compared with the results of other estimation methods. The results show the high accuracy of the proposed method in different conditions. [ABSTRACT FROM AUTHOR]

Generation maintenance scheduling (GMS) is an important factor that can improve the reliability of power systems and decrease revenue achieved by generation companies (GenCos). Several GMS models, therefore, are based on these two crucial values. Nonetheless, there is no GMS problem that simultaneously considers unexpected failure of distributed generator (DG), financial return of GenCo, and reserve of system. This paper proposes the GMS model based on a global criterion approach to compromise functions that maximise the GenCo's annual return and probability that no DG fails unexpectedly. The system reserve (SR) is considered as a reliability constraint, while surplus reserve is exchanged with the main grid. To support alternative energy sources that have uncertain outputs and ensure continuous operation of DG, short‐term GMS model including power from wind farm, photovoltaic system, energy system storage, and demand response (DR) is also run by adding the SR and inconstant cost of DR. Effectiveness of the proposed model is examined using the IEEE 6 and IEEE 18‐bus test systems. Results show that not only the proposed model provides a better GMS solution for the GenCo, resulting in appropriate values of the two objectives, but also alternative energy sources are useful for the short‐term GMS. [ABSTRACT FROM AUTHOR]

Time of use pricing strategy can not only reduce the load fluctuation but also improve the power system reliability. Generally, before carrying out a time of use pricing optimization, it needs to perform a period partition optimization for dividing peak‐valley periods. In existing researches, however, the period partition optimization and the time of use pricing optimization are implemented independently. Although the output of period partition optimization is used as the input of time of use pricing optimization, the bidirectional feedback effect between period partition optimization and time of use pricing optimization is not considered, which will lead to the existing time of use pricing optimization may not be the globally optimal solution. Therefore, this paper investigates a new optimization method for time of use pricing optimization with the consideration of bidirectional feedback effect, establishes a comprehensive customer satisfaction degree model considering the customer load proportion coefficient, and defines an elastic cofactor to describe the electricity price response difference of multiple types of customers. The Roy Billinton test system is used to verify the correctness and effectiveness of the proposed method in this paper. [ABSTRACT FROM AUTHOR]

Future multi-terminal high-voltage direct current (HVDC) grids will be essential for the electric power system expansion. However, there are still several technical, economic and legal obstacles that interfere with the construction of those grids. One of the main technical issues is the interruption of DC currents when a fault occurs, due to the high values of DC fault currents that can exceed the DC circuit breakeŕs (DCCB) interruption capability in few milliseconds. In order to overcome that limitation, a superconducting DCCB (S-DCCB) is presented in this study. The proposed S-DCCB is based on the combination of a superconducting fault current limiter, a mechanical DC circuit breaker and a current limiter reactor. The presented S-DCCB is modelled and simulated by PSCAD/EMTDC software on a four-terminal HVDC system. Its behaviour is proven to be satisfactory for several fault scenarios. DC fault currents are initially limited and afterwards interrupted by the S-DCCB in an operation time that fulfils DC grids' protection requirements. [ABSTRACT FROM AUTHOR]

This paper outlines a Hamiltonian energy‐balance function for computing stable and unstable regions of power systems. Once the generator model is defined, a certain number of variables (holonomic constraints) specifies its state properties (prefault, fault‐on, and postfault) entirely. The change between the postfault (final) and prefault (initial) states is expressed by an energy balance equation (crucial for solving many dynamical problems). State equations (instead of swing equation) with the properties (or functions) of the system are built using the prefault and postfault energies (kinetic and potential) of the generators. When a large disturbance occurs, the 'migration' from one state to another is computed using concepts of least action principle, conservation, and dissipation of energy, perturbation theory and calculus of variations. The method is tested with two electric power systems, where the classical model represents the synchronous generators. Prefault, fault‐on, and postfault regions are clearly characterised on 3D energy surfaces indicating whether the generators remain (or not) stable after a fault in the power system. The trajectories of the Hamiltonian energies of the generators are projected on 2D planar projection maps. The results provided important insights into transient stability problems not seen so far. [ABSTRACT FROM AUTHOR]

For off-grid microgrids in remote areas (e.g. sea islands), proper configuring the battery energy storage system (BESS) is of great significance to enhance the power-supply reliability and operational feasibility. This study presents a life cycle planning methodology for BESS in microgrids, where the dynamic factors such as demand growth, battery capacity fading and components' contingencies are modelled under a multi-timescale decision framework. Under a yearly timescale, the optimal DER capacity allocation is carried out to meet the demand growth, while the investment decisions of BESS are made periodically to yield the optimal sizing, type selection and replacement plans of BESS during the entire lifetime of the microgrid. Then, under an hourly timescale, the long-term probabilistic sequential simulation is adopted to comprehensively evaluate the investment decisions and derive detailed operation indicators. Moreover, a decomposition--coordination algorithm is developed to address the presented planning model, which iteratively strengthens the feasible space of investment-decision model by substituting the operation indicators until an acceptable sub-optimal solution is obtained. Case studies on a wind--solar--diesel microgrid in Kythnos Island, Greece illustrate the effectiveness of the proposed method. This study provides a practical and meaningful reference for BESS planning in off-grid microgrids. [ABSTRACT FROM AUTHOR]

With an increasing number of renewable energy integrated into the power system, the impact of intermittent and random wind power and photovoltaic power on the power system is becoming larger and larger. To study the probabilistic correlation between wind power and photovoltaic power on different temporal and spatial scale, a joint probability model needs to be established. On the basis of the third-order Gaussian mixture model, a photovoltaic-wind joint power probability model is proposed in this study. By analysing the statistical probability characteristics of the measured power output data, this method avoids the error accumulation caused by the individual modelling of the wind and photovoltaic generators and considers the joint correlation between wind power and photovoltaic power. On the basis of this model, the corresponding time series of wind power and photovoltaic power is calculated. The results indicated that the coastal joint power probability model and the inland joint power probability model are quite different on the same time scale, the parameters of joint probability model on different time scales are close to each other. The effectiveness of the proposed method is verified by the measured data. [ABSTRACT FROM AUTHOR]

The reactive power optimization (RPO) problem of power systems is a mixed-integer nonlinear programming problem, which can be computationally expensive. This paper applies the alternating direction method of multipliers (ADMM) to solve it. By duplicating discrete control variables with one copy allowed to vary continuously, the RPO model is formulated as a modified model in which the objective function and constraints have a separable structure with respect to the continuous and discrete variables, except for the coupling constraint. We then applied the ADMM to solve this model with the separable structure, and hence the original problem is converted into two optimization sub-problems, which are nonlinear programming (NLP) and mixed-integer quadratic programming (MIQP) problems, respectively. To improve the convergence of the algorithm, we proposed an extended ADMM by adding the upper and lower limits on state variables into the MIQP sub-problem based on the sensitivities obtained in the NLP sub-problem. We also established a mechanism to filter out inactive inequality constraints in the MIQP sub-problem to improve computational speed. Moreover, numerical results tested on IEEE test systems and a real 739-bus system have shown the correctness of the proposed method and its adaptability for power systems with different sizes and configurations. [ABSTRACT FROM AUTHOR]

This study proposes an optimal voltage control scheme to deal with long-term voltage stability of power systems. The control of voltage is accomplished by model predictive control (MPC) scheme. The control objective function considers the control efforts and the difference between the predicted and reference voltages. Also, this study considers the detailed nonlinear dynamic model of the system including doubly-fed induction generator wind turbines, over excitation limiter and underload tap changer, which are important elements, should be considered in voltage stability evaluation of power systems. The proposed approach composed of the following two major stages at each time instance: first, the power system non-linear dynamic equations are linearized and optimal control laws are obtained by MPC technique; in the second stage, the system dynamic behavior is investigated via time-domain simulations by applying the attained optimal control signals at the first step. The proposed MPC-based voltage control scheme is implemented on a well-known test system, under variable wind speed and fault conditions. Also, this method's performance is compared with state feedback control technique. The obtained numerical results validate the capability of the proposed control scheme to preserve voltage stability at the presence of stochastic wind speed variations and severe disturbances. [ABSTRACT FROM AUTHOR]

Till this moment, the model of interconnected power systems in the automatic generation control (AGC) loops relies only on the synchronous generating units. In today's world, a high level of penetration of renewable energy sources (RES) is integrated to the power grids. This paper presents a novel power system model, which includes both conventional generating units and RES for studying the AGC problem of such systems. The control strategy in the AGC loops is based on the proportional-integral-derivative (PID) controller, which is optimally designed by the whale optimization algorithm (WOA). It represents a great challenge to this controller to deal with the RES uncertainties. The effectiveness of the WOA-based PID controller is compared with other computation evolutionary algorithms-based PID controller. The system performance is evaluated under different operating conditions. For achieving a realistic study, 1) real wind speed data that extracted from Zafarana location in Egypt are used, 2) solar irradiation and temperature data that extracted from a field test are implemented, and 3) an irregular wave energy condition is applied. The validity of the control strategy is verified using the simulation results, which are carried out using MATLAB environment. [ABSTRACT FROM AUTHOR]

Cyberattacks have emerged as novel threats to modern power systems. By exploiting the vulnerabilities of insecure devices, an attacker can inject viruses to lurk and collect system conditions through sniffing and then launch well‐designed attacks. Collaboratively applying bilateral cyber‐physical information can help to detect anomalous system states caused by sniffing, which can isolate virus impacts on the cyber side and ensure the stable operation of power systems. Here, a dynamic weight ensemble isolation forest algorithm is proposed to mine anomaly system states utilizing bilateral information based on the hypothesis that the fused cyber‐physical system state under assault has the shortest average path length in a constructed random forest. In addition, the proposed algorithm is able to realize improved performance in power system anomaly status mining and adapt to constantly changing power systems. The method is verified by simulations on a co‐simulation platform. The results show that the method outperforms other anomaly detection methods. [ABSTRACT FROM AUTHOR]

The high penetration of uncertain resources challenges the security of power system operation. By taking the impact of rescheduling under contingencies into consideration, reliability‐constrained unit commitment (RCUC) is developed to address this challenge. Although several efforts have been made in modelling reliability constraints, the existing methods can only manage oversimplified low‐order temporal‐independent contingencies without considering wide‐range contingencies or their state‐transition‐process issue. To quantify the impact of rescheduling on the normal‐state scheduling process denoted by UC problem, this paper builds up a Bayesian inference method for encoding reliability constraints in wide‐range temporal‐dependent contingencies. Three predictors, for example, expected‐generator‐rescheduling‐power, expected‐energy‐not‐serviced and lost‐of‐load‐probability, are selected to describe the possible corrective behaviours in rescheduling process and quantified by using Bayesian inference method. Then, these predictors are reformatted as a set of linearized constraints to be incorporated into UC. The proposed RCUC comprehensively considers the effect of rescheduling in wide‐range temporal‐dependent contingencies. Therefore, it can reveal the influence of generator rescheduling in wide‐range contingencies and keep better reliability performance than those methods reported in previous RCUC studies. The modified IEEE 30‐bus test system and IEEE 118‐bus test system are used to show the proposed model's effectiveness. [ABSTRACT FROM AUTHOR]

Short‐term load forecasting is essential to power systems management. However, most existing forecasting methods fail to fully consider how to rationally integrate the intrinsic time‐related dimensions of electric load data and the decomposition methods into machine learning models so that their prediction accuracy and robustness still have much room for improvement. To solve this problem, this paper proposes a decomposition‐based multi‐time dimension long short‐term memory (DB‐MTD‐LSTM) model for short‐term electric load forecasting (STELF). In DB‐MTD‐LSTM, empirical mode decomposition with adaptive noise (CEEMDAN) is first introduced to smooth non‐linear non‐stationary electric load data and constrain the modal aliasing or noise of decomposed electric load data in the traditional decomposed method. A joint relevant time dimensions method (JRTDM) is then developed using autocorrelation analysis to rationally extract the temporal characteristics of decomposed data in multiple time dimensions. An improved LSTM called MTD‐LSTM is developed by combining JRTDM with LSTM, which can effectively apply multi‐dimensional time characteristics of the decomposed load to improve the predictive accuracy and robustness. Several datasets from Australia and China are performed to check the predictive performance of DB‐MTD‐LSTM. Experimental results verify that DB‐MTD‐LSTM has better predictive accuracy and satisfactory robustness compared with state‐of‐the‐art and conventional predictive models. [ABSTRACT FROM AUTHOR]

This paper proposes a vehicle‐to‐grid (V2G) operation methodology of electric vehicles (EVs) for frequency regulation, EV charging, and state‐of‐charge (SOC) management. This V2G operation methodology exhibits multifunctionality in regard to instantaneous power adjustment of EVs for primary frequency control during charging. The proposed method can stabilize grid frequency under the high penetration of renewable energy by simultaneously managing the desired state‐of‐charge (SOC) of the batteries. The results indicate that both charging and charged EVs can assist in frequency regulation so that V2G services can help embracing renewable energy sources and stabilize a power system. The feasibility of this method is verified by a practical power grid model to demonstrate the efficacy of EV charging control for SOC management using DIgSILENT/PowerFactory. [ABSTRACT FROM AUTHOR]

Zero‐sequence currents in high‐voltage power systems during normal operation can have a significant influence on nearby infrastructure. It is therefore necessary to gain insight into typical levels of zero‐sequence currents in a variety of operational situations. Measurements can provide this insight. When performing measurements, one needs to know the uncertainty associated with the measurement to draw accurate conclusions. The measurement uncertainty associated with three different practical strategies to measure zero‐sequence currents during normal operation are studied: a direct and indirect measurement strategy using current clamps and oscilloscopes and a measurement strategy using phasor measurement units (PMU). Measurement uncertainty is studied using two methods: by analytical expressions and by Monte Carlo simulations. Both methods give consistent outcomes for the measurement uncertainty and show the same tendencies of the zero‐sequence current measurement uncertainty as a function of the positive‐sequence current. This paper studies measurement strategies with error sources based on realistic measurement devices that could be used in practice. The following outcomes were found: in the direct strategy, the primary current transformers are the largest uncertainty sources; in the indirect strategy, the current clamps are the largest uncertainty sources; in the PMU strategy, the PMU total vector error is the largest uncertainty source. [ABSTRACT FROM AUTHOR]

This paper presents the design of a non-linear recurrent artificial neural network (ANN) based load frequency control (LFC) of a two-area power system interconnected via HVDC tie-line in parallel with EHVAC line. The control design is based on the combination of robust LFC and optimisation of recurrent ANN so that designed LFC scheme is suitable to handle the diverse operating conditions of power system. The various structures of the state cost weighting matrix (Q), i.e. controllability and observability aspects which affect the dynamics of the power system are used for the LFC design. The feedback gains achieved by the implementation of robust LFC using the different structures of Q are used to effectively train the recurrent ANN-based LFC design and its performance is analysed with and without system non-linearity's for 1% step load disturbance in one of the control areas to show the superiority of one design over the others. The closed-loop system eigenvalues obtained for the system ensure the system stability. Furthermore, the recurrent ANN-based LFC performance is evaluated for the diverse system operating conditions and compared with multi-layer perceptron (MLP) ANN-based and conventional PI control schemes to demonstrate the effectiveness of proposed LFC design scheme. [ABSTRACT FROM AUTHOR]

This study presents a lifetime efficiency index model for substation equipment and proposes an appropriate method for the optimal maintenance of substation equipment. Along the substation equipment lifetime, due to ageing and daily operations, the failure rate increases gradually. So it is needed to do a maintenance strategy for the aim of reduction in the failure rate and improvement in the reliability of equipment. The maintenance strategy for substation equipment typically consists of preventive and corrective maintenance. By the lifetime efficiency index, one can analyse the lifetime of the equipment under the conditions of with and without maintenance. In this study, the failure rate of the equipment is modelled by the appropriate Weibull distribution. Maintenance can keep equipment in normal condition, but it incurs cost. The maintenance strategy should be optimised for the minimum maintenance cost under the required reliability condition. In order to solve this objective problem, a cuckoo optimisation algorithm (COA) is used and results are evaluated. The results based on an example show that the proposed COA was indeed capable of obtaining higher quality solutions than other methods for the optimal maintenance. [ABSTRACT FROM AUTHOR]

In an interconnected bulk power system, wide-area measurement system (WAMS) can provide abundant remote measurement for the coordinated control system. However, WAMS data have obvious time delays, which affect the performance of the control system and should be properly considered. Time-delay stability margin (TDSM) is an index to reflect the maximum delay that a time-delay system can sustain without losing its stability. To construct a coordinated control system based on WAMS data, it is crucial to accurately and rapidly determine the TDSM value. In this paper, a novel Jordan-Taylor-Schur (JTS) approach to determine the TDSM value of power system is proposed. It consists of three, Jordan standardization, Taylor separation and Schur simplification. With the three procedures of this method, the model dimension of time-delay system can be reduced, and the stability criterion derivation can be rebuilt to omit some unnecessary variables so that both the computational efficiency and accuracy can be boosted. Further, it is worth highlighting that the proposed method can be applied to various Lyapunov-based stability criteria to improve their efficiency with small errors. Finally, three power systems with time delays have been used to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper proposes a new assessment method for lightning trip‐out of transmission lines that includes an improved analytic hierarchy process (IAHP) algorithm based on a lift in association rules. First, the k‐means clustering algorithm is used to discretize the geomorphic information along transmission lines, and ten feature factors are obtained. Next, by analysing the correlation between each feature factor and a lightning trip‐out event using the lift algorithm, the strong correlation factors are extracted. On this basis, an IAHP algorithm optimized by lift is proposed to establish an objective judgment matrix. Then, multiple indexes are combined as a criterion layer of the IAHP, and a lightning risk assessment model of transmission lines is established. Finally, the proposed method is validated by simulations using 28 transmission lines with 220 kV voltage grade of a provincial power grid of China. An assessment model is established using the lightning trip‐out data in the period 2010–2014, and then this model is employed to estimate the lightning trip‐out risk in the period 2015–2018. Based on the number of phase faults, the agreement between the estimation results and the actual values is 76%. The proposed model provides a new method for the lightning risk assessment of transmission lines. [ABSTRACT FROM AUTHOR]

The electric power system is one of the most important critical infrastructures of a country. Recently, the number of natural and man‐made disasters is increased, which can impose extensive damages and costs to the power system. A resilient power system can withstand against, adapt to and recover from these disasters. Power system resilience is quantified by mathematical tools which are called "resilience metrics". Currently, a lot of resilience metrics are proposed in the power system literature. In this paper, based on the extensive research in the critical infrastructure resilience literature which specifically concentrates on the "area‐based" resilience metrics, a new area‐based resilience metric is proposed which can measure the power system resilience considering the government policymaker criteria, which are rarely noticed before. The proposed and conventional area‐based resilience metrics are evaluated based on the real data from the 2012 Superstorm Sandy in the USA, which led to significant damage to the power distribution system. The simulation results show that the proposed area‐based resilience metric is very simple, can successfully address actual power system performance curves and is more meaningful and tangible than the conventional area‐based metrics for the government policymaker. The proposed area‐based resilience metric has also a general form and can be used for other critical infrastructures. [ABSTRACT FROM AUTHOR]

As the penetration level of converter-based generators (CBGs) continues to grow in electric power systems, their impact on power system dynamics and control becomes increasingly significant. Maintaining a stable operation of the CBGs is becoming more and more critical. Since their controls and dynamic behaviour differ from synchronous generators, in this study, the transient stability mechanism of CBGs is analysed and the key influencing factors are identified and investigated. Moreover, a stability margin index, which can be obtained analytically, is proposed to identify potential transient stability issues of CBGs and can be used as a screening technique before conducting time-consuming electromagnetic simulation studies. This index can be used for both planning and operations studies and it outperforms the state-of-the-art index of short circuit ratio that is presently used to identify potential CBG instabilities due to weak grid scenarios. Dynamic simulations on a real power system model have been conducted to validate the accuracy and applicability of the proposed stability margin index. [ABSTRACT FROM AUTHOR]

The objective of traditional phasor measurement unit (PMU) placement approaches is to find the minimal number of PMUs to achieve full system observability. Very few consider the probability and the consequence severity of observability loss. For example, following cascading failures, lines are tripped, and the topology of the grid changes, which may result in observability loss for parts of the grid. With limited number of PMUs, it is desired that the PMUs should still sustain observability for the power grid after top-severe cascading failures, other than after those cascading failures of low severity. To address the above issues related with the consequence severity of observability loss, this study proposes a risk-oriented PMU placement approach. The proposed approach uses two indices, namely the probability of observability loss and the severity of its corresponding consequence to design the optimal PMU placement strategy. The authors show that the proposed approach is able to capture the critical events, while traditional approaches fail to do so. Extensive simulation results carried out on the IEEE 39-bus and 118-bus systems demonstrate the effectiveness of the proposed risk-oriented approach. [ABSTRACT FROM AUTHOR]

The objective of traditional phasor measurement unit (PMU) placement approaches is to find the minimal number of PMUs to achieve full system observability. Very few consider the probability and the consequence severity of observability loss. For example, following cascading failures, lines are tripped, and the topology of the grid changes, which may result in observability loss for parts of the grid. With limited number of PMUs, it is desired that the PMUs should still sustain observability for the power grid after top‐severe cascading failures, other than after those cascading failures of low severity. To address the above issues related with the consequence severity of observability loss, this study proposes a risk‐oriented PMU placement approach. The proposed approach uses two indices, namely the probability of observability loss and the severity of its corresponding consequence to design the optimal PMU placement strategy. The authors show that the proposed approach is able to capture the critical events, while traditional approaches fail to do so. Extensive simulation results carried out on the IEEE 39‐bus and 118‐bus systems demonstrate the effectiveness of the proposed risk‐oriented approach. [ABSTRACT FROM AUTHOR]

Distributed generators have grown in significance for the technical and financial operation of electric power systems in recent years. The integration of these generators into the electrical distribution network (EDN) has experienced rapid growth, primarily driven by advancements in renewable energy sources (RESs), particularly photovoltaic distributed generators (PVDGs). With the increasing implementation of solar energy as a RES, designing the optimal integration of PVDGs into medium voltage direct current (MVDC) networks is crucial to comprehensively analyzing technical and economic factors. To address this issue, a new multiple objective function (MOF) is proposed, which combines various techno‐economic parameters such as total active power loss (APL), voltage deviation (VD), and the investment cost of PVDGs (ICPVDG) installed in the test system. The objective is to minimize the MOF simultaneously to achieve the optimal incorporation of PVDGs. This study aims to solve the allocation problems related to the location and size of PVDG units in the modified MVDC test systems IEEE 27 and 33‐bus. Simulation results demonstrate the superior accuracy and effectiveness of the equilibrium optimization algorithm (EOA) in achieving the minimum MOF. The utilization of multiple PVDG units reduces overall active power losses and improves voltage profiles across all buses. [ABSTRACT FROM AUTHOR]

This study presents a novel faulted line identification method that is applicable in power systems with only sparse synchronised measurements, and at the same time, with significantly reduced computational burden so that it can be a competitive choice for wide-area backup protection schemes. By revealing the behaviour pattern of bus voltages from the perspective of high-dimensional unitary space, the method is enabled to avoid unnecessary computation and thus to remarkably improve its efficiency. Analysis in high-dimensional unitary space also gives a direct and feasible guideline for phasor measurement unit (PMU) placement, from which a PMU optimal placement strategy is developed. Performed on the IEEE benchmark systems of 39 and 118 buses, the proposed method gives encouraging results. [ABSTRACT FROM AUTHOR]

Curtailable loads (CLs) are regarded as one of the last lines of defence to maintain the security and stability of power systems. Nevertheless, if organised carefully, they can also be exploited as preventive security procurement measures for power systems. This is especially true for heavily loaded power systems in which the normal control schemes are already exhausted. In this study, a new power market approach is proposed to utilise CLs' potential in ensuring voltage stability margin (VSM) for heavily-loaded power systems. The proposed method aims to provide a mechanism to engage CLs as active players in the power market, and hence, minimise the disruptive effect of the load curtailment. Next, CLs participation in the power market is utilised to minimise the cost of achieving a desired level of VSM, at normal and N - 1 contingency conditions, in a preventive manner. The most efficient load curtailment and power generation pattern are determined, using a modified particle swarm optimisation algorithm, to minimise the system's total cost, while meeting grid's VSM requirements. The simulation results verify that the desired level of VSM can be effectively obtained using the proposed approach, with much less operational cost compared to the established methods. [ABSTRACT FROM AUTHOR]