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Cyber–physical distribution systems with renewable energy should have high resilience under extreme conditions. However, in a distribution system with deep cyber–physical coupling, the propagation of information risk impairs the resilience of the system. This paper proposes a strategy to improve the resilience of cyber–physical distribution systems that considers cross‐space propagation of information risk. First, the mechanism for interaction between the cyber space and physical space is analyzed, and an information risk cross‐space propagation model is proposed. Second, the risk status of key device nodes is quantified according to the risk propagation model, and an optimization strategy for information risk control is obtained, whose objective function is the minimum risk of the coupling network. Third, a fault restoration strategy that considers cyber space risk is proposed. Finally, the paper reports experiments using the modified IEEE 33‐node and 123‐node distribution networks to simulate the proposed strategy and verify its effectiveness. [ABSTRACT FROM AUTHOR]

Abstract Current transactive controls use marginal benefits and marginal costs to achieve an economic market efficiency during normal grid operations. However, the transactive mechanisms designed for normal economic operations cannot be applied directly for the contingencies because the grid operations during contingencies are often dictated by technical needs rather than purely economic criteria. For instance, one of the key technical requirements for the blackstart is to have at least one blackstart capable resource cleared which cannot be ensured by the transactive mechanism designed for normal economic operations because they work primarily based on the marginal benefit and marginal cost of the participants. This article presents one of the first attempts to develop a transactive mechanism to be used during grid contingencies. A distributed blackstart and service recovery is used as an example contingency to evaluate the performance of the proposed transactive mechanism. The performance of the proposed transactive mechanism is demonstrated for various use cases using a modified IEEE‐123 node test system. The simulation results demonstrated the proof of concept of applying a transactive mechanism to enable distributed blackstart and service recovery by engaging the mix of blackstart capable and non‐capable distributed energy resources.

Abstract Weak inertia characteristics of power systems with high penetrations of renewables have become a prominent problem for frequency security. To solve this problem, a convolutional neural network (CNN)‐based deep learning approach is applied to realize rapid frequency security assessment (FSA). First, the time series frequency security feature is autonomously mined from the wide‐area measurement data to serve as the input data. By doing so, the complex construction process of frequency security feature quantity is avoided. A deep learning structure is then used to establish a non‐linear mapping relationship between time series features and frequency security indicators to realize end‐to‐end power system frequency security prediction. Next, the evaluation accuracy of the proposed approach is optimized by tuning the key parameters in the CNN‐based evaluation model. Through data measurement error analysis and a wind penetration sensitivity study, the anti‐interference performance of the proposed evaluation model is demonstrated. Finally, the effectiveness of the CNN‐based FSA is verified by case studies of a modified 16‐machine 68‐node system and the China Southern Power Grid.

With the increasing risks of malicious cyber-physical attacks and natural disasters, it is urged for power grids to improve the resilience performance against such high-impact, low-frequency events. The critical component identification is an important problem for the effective planning, operation and asset management of power systems. Thus, it is highly necessary and beneficial to develop a resilience oriented critical component identification method for defending power systems against extreme events. In this paper, a tri-level optimization model is developed to identify the critical components while the coordinated cyber-physical attacks on power systems are formulated considering the resources of attackers, the optimal attack strategy, and the actions of the system operator to enhance the system resilience against potential attacks. Meanwhile, a distributionally robust optimization (DRO) based model is proposed to consider the impacts of distribution uncertainty of the resource or ability of the malicious attackers in the criticality identification framework. A constraint-generation based algorithm is developed to solve the overall multi-level DRO model with a master and sub-problem scheme. Further, a criticality index is proposed to quantify the importance of key components to the system resilience against malicious cyber-physical attacks. In order to validate the proposed method, case studies were conducted on the IEEE reliability test system (RTS-79). The obtained results show that the proposed critical component identification method can provide effective and robust importance evaluation of system components to bolster the grid resilience against potential cyber-physical threats. [ABSTRACT FROM AUTHOR]

Variable renewable generation technologies such as wind and solar photovoltaic have introduced new challenges in power system management. Grid operators have traditionally used ancillary services such as reserve and reactive power to help to maintain a secure and reliable power system. In addition, conventional synchronous generators have inherent characteristics such as inertial response, which help the power system to recover after an event. In Ireland and Northern Ireland, a weakly‐interconnected island system with a high penetration of wind, new ancillary or 'system' services have been devised to address the technical scarcities arising from the displacement of synchronous generation. Twelve system services addressing the frequency and voltage control needs have been procured to date, allowing the power system to be operated with up to 65% instantaneous non‐synchronous renewable power on the system. This study outlines the implementation of the innovative system services framework. It includes an overview of the services procured and examples of the changed behaviour of existing units in response to financial incentives. It also examines how new technologies have responded to the signals provided, questions how aspects of the arrangements may be further improved and details the challenges of integrating the use of these innovative services into operational policy. [ABSTRACT FROM AUTHOR]

In this study, a novel $H_\infty $H∞ predictive event-triggered load frequency control has been developed for a hybrid power system with renewable energy sources (RESs) to deal with denial-of-service (DoS) attacks, where the DoS duration (the time attack lasts) are boundless. A predictive event-triggered transmission scheme is built for the multi-area hybrid power systems under DoS attacks to reduce the load of network bandwidth while maintaining adequate levels of performance. Therefore, an observer-based predictive controller is developed in the presence of both external disturbances and DoS attacks by formulating the LFC problem as a disturbance attenuation issue. In the proposed method, a hybrid power system with RESs is used to achieve novel and better security strategies. Based on the new model, sufficient conditions are obtained using the Lyapunov stability theory to ensure a stable multi-area hybrid power system with a prescribed $H_\infty $H∞ performance. Moreover, an algorithm is provided to obtain the control strategy of DoS attacks. Finally, the simulation of a hybrid power system with RESs is presented to demonstrate the effectiveness of the proposed method in dealing with the DoS attacks. [ABSTRACT FROM AUTHOR]

To solve the problem of manpower and time consumption caused by power flow state adjustment in a large-scale power grid, a power system operation state adjustment method considering the static stability constraint based on parallel deep reinforcement learning is proposed. By introducing the process of adjusting the power flow state that satisfies static stability, the Markov decision-making process of adjusting power flow is constructed. Then, based on the positioning of the adjustment target, the selection of actionable devices and the calculation of the amount of action, a power flow state adjustment strategy is developed. The adjustment process is accelerated through sensitivity, transfer ratio and load margin. Then, a parallel deep reinforcement learning model is established, and it maps actions to power flow adjustment to form a pair of generator actions and realises parallel adjustment of multi-sectional objectives. In addition, the reinforcement learning strategy and the deep learning network are improved to promote learning efficiency. Finally, the New England 39-bus standard system and actual power grid are used to verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

The system equivalent inertia of the power grid is gradually decreased with the increasing penetration of renewable energy resources, which leads to a higher risk of frequency fluctuation after a major fault. For the frequency emergency control in the scenario of a high-voltage direct current (HVDC) line block fault, a novel criterion for enabling the fast response of user-end distributed loads is proposed in this study based on voltage feature identification and frequency drop detection. The reactive power to voltage sensitivity coefficient is combined with the Hausdorff algorithm to increase the accuracy of the calculation. The proposed criterion can realise the HVDC block fault identification at the end of the distribution grid, so as to achieve fast decentralised decision-making for distributed loads. This method may greatly reduce the need for high-speed communication and take actions faster than the primary and secondary frequency controls of the traditional units. The criterion makes it possible for low voltage small load in the user-end to be controlled precisely and selectively to fill the large power imbalanced caused by an HVDC block fault. The validity and superiority of the criterion are verified by simulation experiments using multiple test systems. [ABSTRACT FROM AUTHOR]

Modern societies these days are more dependent on electrical energy and they expect a continuous supply as per demand. In this regard, the complex power system is designed to supply electrical energy with a certain level of quality and continuity though it is still susceptible to vandalism, natural disasters, and extreme weather. The black sky event where the power grid goes down is more of a possibility nowadays than ever due to more frequent severe weather events. This in turn has increased the need to study resilience in the context of the power system. This study presents a comprehensive review of the literature on power system resilience from various perspectives. First, well-developed power system safety concepts are discussed and critically reviewed in view of large-scale power outages. Then, the various definitions and confounding features of resilience in the power system domain are presented. Subsequently, several frameworks, resilience curves, and quantitative metrics proposed in recent years for power system resilience are investigated, followed by a summary of hardening strategies. Next, a case study is presented to illustrate how the resilience of a 69-bus system is assessed against a hurricane. Finally, the study highlights challenges and proposes several future works to achieve a resilient power grid. [ABSTRACT FROM AUTHOR]

Power grids all over the world are nowadays facing high penetrations of renewable power generation. The converter‐based generation units play a major role in system behaviour and operation. Thereby, also the reliability of the power system is impacted in many different aspects. It has to be verified whether the frequency reliability assessment, which is often studied by simulations, is still accurate, every time a new control structure is considered. For this, the number of simulations should not be further increased if possible, in order to keep the computational efforts low. In this study, the authors verify that the assessment outcome will be accurate when the load duration curve (LDC) and wind power curve (WPC) of a system are described well enough. This is shown to be true for different frequency controls, implemented in wind power plants in the system. Besides, the effects of different LDCs and WPCs are analysed, as they can change over time. The used methodology is validated on the IEEE reliability test system (IEEE RTS). [ABSTRACT FROM AUTHOR]

In a DC microgrid, the anti‐interference ability of bus voltage can easily become vulnerable due to low inertia caused by a large number of power electronic converters. This has already challenged the system stability and practicability in DC girds. In this study, a flexible virtual capacitance (FVC) control strategy with multiple constraints (MCs) is proposed to guarantee the security and stability of the DC microgrid, where the system stability, dynamic characteristics, actual operation requirements and realisability are considered as MCs. The FVC controller, which mainly modifies the reference current in voltage source converter by flexibly regulating virtual capacitance value, is given to provide inertial support and improve voltage quality. The stable operating boundary calculation based on small signal model and key control parameters design are further introduced into the control loop. This can ameliorate the dynamic response of the microgrid and obtain the better engineering practicability. Finally, experiment tests on a controller‐level hardware‐in‐the‐loop simulation platform are carried out to verify the validity of the proposed strategy. [ABSTRACT FROM AUTHOR]

Security‐constrained unit commitment (SCUC) is one of the most important optimisation problems for operation planning of power systems. Indeed, with the fast expansion of power grids and the increasing growth of heterogeneous market participants in electricity markets, the day‐ahead SCUC continuously encounters significant performance challenges. To improve the computational performance of SCUC and achieve solutions of good quality, an integrated framework which combines a data‐driven approach and a variable‐aggregation method is presented in this study. The variable‐aggregation method effectively approximates the original network security constraints with a reduced number of variables. Moreover, as aggregated constraints could reduce the feasible region of the original SCUC and potentially degrade solution quality for certain SCUC instances, it is preferable to only apply such an aggregation approach towards difficult SCUC instances. Therefore, a data‐driven classification method, by adopting relevant SCUC input data as features, is integrated to first predict whether a SCUC instance is 'easy' or 'hard'. To this end, the integrated framework could improve the overall performance of SCUC instances, by and large, in terms of computational efficiency and solution quality. Numerical results illustrate the effectiveness of the proposed integrated framework. [ABSTRACT FROM AUTHOR]

Recent research on wind-farm control methods has focused until now on maximising the efficiency and durability of farm operations, as verified for a normalised electrical layout. However, with the increase of turbine size and capacity, it is necessary to develop modifications of the farm management plan that can support the increasing demands of the wind-turbine industry. Here the authors propose a modification that focuses on a proportional reactive power-dispatch method that is applied to radial offshore farm networks. They improve a previously developed method of proportionally distributing reactive power commands by considering the actual configuration of an offshore platform. To confirm the applicability of this method in transient state, they examine case studies using a time-varying signal for a reactive power reference under fluctuating wind. Electromagnetic transients using DC software tools are used to estimate the electrical loss and verify the efficiency of this strategy. [ABSTRACT FROM AUTHOR]

Over the last decade, the number of cyber attacks targeting power systems and causing physical and economic damages has increased rapidly. Among them, false data injection attacks (FDIAs) are a class of cyber-attacks against power grid monitoring systems. Adversaries can successfully perform FDIAs to manipulate the power system state estimation (SE) by compromising sensors or modifying system data. SE is an essential process performed by the energy management system towards estimating unknown state variables based on system redundant measurements and network topology. SE routines include bad data detection algorithms to eliminate errors from the acquired measurements, e.g. in case of sensor failures. FDIAs can bypass BDD modules to inject malicious data vectors into a subset of measurements without being detected, and thus manipulate the results of the SE process. To overcome the limitations of traditional residual-based BDD approaches, data-driven solutions based on machine learning algorithms have been widely adopted for detecting malicious manipulation of sensor data due to their fast execution times and accurate results. This study provides a comprehensive review of the most up-to-date machine learning methods for detecting FDIAs against power system SE algorithms.

Cyber attacks can cause cascading failures and blackouts in smart grids. Therefore, it is highly necessary to identify the types, impacts and solutions of cyber attacks to ensure the secure operation of power systems. As a well-known practice, steady-state analysis is commonly used to identify cyber attacks and provide effective solutions. However, it cannot fully cover non-linear behaviours and cascaded blackouts of the system caused by dynamic perturbations, as well as provide a post-disturbance operating point. This study presents a novel approach based on dynamic analysis that excludes the limitations of the steady-state analysis and can be used in the events of various cyber attacks. Four types of common attacks are reviewed, and their dynamic impacts are shown on the IEEE benchmark model of the Western System Coordinating Council system implemented in MATLAB Simulink. Then, recommendations are provided to enhance the security of the future smart power grids from the possible cyber attacks.

As the worst-case interacting false data to the power system state estimation (SE), cyber data attacks can avoid being filtered out by most bad data detectors. In this study, coordinated attacks (unobservable attack and logic bomb attack) and coordinated defences (honeypot and weakening vision) are used to analyse attackers’ and defenders’ behaviours, respectively. To quantify the potential physical influences (attack-and-defence) benefits, the residual of the expected state is devised. Subsequently, a zero-sum stochastic game is utilised to model the interaction between the cyber-physical power system and the external attack-and-defence actions. This game is demonstrated to admit a Nash equilibrium and the minimax Q-learning algorithm is introduced to enable the two players to reach their equilibrium strategies while maximising their respective minimum rewards in a sequence of stages. Numerous simulations of the stochastic game model on the IEEE 14-bus system show that while resisting the isolated or coordinated attacks, the optimal coordinated defences are more effective than those of isolated attacks.

As the power grid continues to evolve with advanced wide-area monitoring, protection, and control (WAMPAC) algorithms, there is an increasing need for realistic testbed environments with industry-grade software and hardware-in-the-loop (HIL) to perform verification and validation studies. Such testbed environments serve as ideal platforms to perform WAMPAC prototyping, operator training, and also to study the impacts of different types of cyberattack scenarios on the operation of the grid. In this study, the authors introduce pacific northwest national laboratory(PNNL) cyber-physical systems testbed (PRIME): the testbed that integrates real-time transmission system simulator with commercial industry-grade energy management system software and remote HIL (RHIL). PRIME is an end-to-end, modular testbed that allows high-fidelity RHIL experimentation of a power system. We present two detailed case studies (fault location and clearing in the transmission system and operator training) to show the capabilities of their PRIME testbed. Finally, we briefly discuss some of the potential limitations of their testbed in terms of scalability and flexibility to set up larger test systems and identify directions for future work to address these limitations.

Internet-connected devices will represent an increasing proportion of the load served by electric power systems. As these devices could conceivably be hijacked and controlled remotely by a malicious actor, they could represent a new threat vector against the dynamic security of a power system. Such attack strategies have not been considered in the existing literature on power system cybersecurity. As an initial scoping exercise, the present case study explores whether such devices could be remotely hijacked and then maliciously power-cycled at particular frequencies to deliberately provoke harmful oscillations in an electrical grid. To gauge the broad feasibility of this novel style of attack, dynamic simulations are performed on two representative test power systems, at differing levels of attacker and defender resources. These simulations show that power-cycling just 1% of consumer loads at a system's resonant frequency may sometimes provoke harmful electromechanical oscillations throughout a national grid. This novel simulation exercise, therefore, implies that cybersecurity vulnerabilities at the consumer side could jeopardise the physical integrity of a nation's entire electricity supply.

This study presents a hybrid data-driven physics model-based framework for real-time monitoring in smart grids. As the power grid transitions to the use of smart grid technology, it's real-time monitoring becomes more vulnerable to cyber-attacks like false data injections (FDIs). Although smart grids cyber-physical security has an extensive scope, this study focuses on FDI attacks, which are modelled as bad data. State-of-the-art strategies for FDI detection in real-time monitoring rely on physics model-based weighted least-squares state estimation solution and statistical tests. This strategy is inherently vulnerable by the linear approximation and the companion statistical modelling error, which means it can be exploited by a coordinated FDI attack. In order to enhance the robustness of FDI detection, this study presents a framework which explores the use of data-driven anomaly detection methods in conjunction with physics model-based bad data detection via data fusion. Multiple anomaly detection methods working at both the system level and distributed local detection level are fused. The fusion takes into consideration the confidence of the various anomaly detection methods to provide the best overall detection results. Validation considers tests on the IEEE 118-bus system.

The pervasive use of heterogeneous and non-proprietary information and communication technology exposes the power grid to cyber-attacks. In particular, monitoring-control attacks (MCA), which manipulate control decisions by fabricating measurements, are highly threatening, because MCA are difficult to detect and can coordinately inflict severe consequences at a large scale. To defend against MCA, a semantic analysis framework is proposed in complement to direct-setting intrusion detection. The proposed framework has the advantages of promising runtime and detection performance. The performance of the proposed framework is evaluated under different attack scenarios and compared with a direct-settings intrusion detection systems using a 6-bus test system and the New-England 39-bus test system.

Natural disasters, such as typhoons and earthquakes, pose great challenges to power system resilience and power supply reliability. It is widely acknowledged that critical transmission lines play a significant role in enhancing the resilience and reliability of power systems under severe natural disasters. In order to improve the disaster resilience of power systems with renewables, a critical line identification approach is proposed in this work based on the complex network theory. Firstly, the concept of core skeleton network (CSN) of power systems with renewables is introduced and a two-step strategy is presented to optimise the CSNs of the concerned power system considering the variable outputs of renewables. Then, a statistical salience method incorporating edge salience and the state-of-the-art null model in complex network theory is proposed to identify critical lines of each CSN and the concerned power system with renewables. Finally, the effectiveness of the proposed critical lines identification approach is verified by simulations on the modified IEEE 118-bus system with renewables, Guangdong Provincial Power System (GPPS) and Zhejiang Provincial Power System (ZPPS) in China. Simulation results show that by using the proposed approach, the critical transmission lines can be effectively identified, not requiring a predefined number of critical lines. [ABSTRACT FROM AUTHOR]

The increasing penetration of inverter‐based resources is affecting the overall power system security, so that effective tools are needed to provide system awareness and identify the most suited countermeasures. To tackle this problem, real‐time monitoring and assessment of transmission grids based on synchrophasor measurements have drawn the attention of many researchers over the last decade, thanks to the high temporal resolution of data provided by phasor measurement units. In this study, a new version of the dynamic mode decomposition (DMD) is proposed as a tool for the real‐time identification of electromechanical oscillations. This approach is able to provide information on the dynamic characteristics (frequency and damping) and the spatial correlation (mode shape) of the modes identified. Besides, an improved criterion is used to track and discern the dominant modes. The effectiveness of the DMD method has been tested on the two‐area Kundur system and validated using data from a real event on the European synchronous grid, giving promising results. Thanks to its reliability and robustness, the DMD is now implemented in the Terna (the Italian transmission system operator) Wide Area Measurement System in use in the control room. [ABSTRACT FROM AUTHOR]

Wind power uncertainties have made the large integration of wind power generating units in the power system highly challenging. One promising solution to overcome the challenges associated with the intermittency of the renewable energy resources (RESs) is to connect areas with diverse renewable energy portfolios via high voltage direct current (HVDC) transmission lines with controllable power transfer capability. The installation of HVDC transmission lines in the power system has resulted in the evolution of conventional alternating current (AC) networks to mixed AC‐HVDC power systems. In this study, to address wind power uncertainties in mixed AC‐HVDC multi‐area power systems, a modified robust optimisation (RO) model for the security‐constrained economic dispatch (SCED) problem is proposed. The proposed RO model is used to minimise the generation cost and wind power curtailment under the worst‐case scenario of actual wind power. Unlike the existing RO models, the proposed RO model considers a modified uncertainty set based on the wind power admissibility and addresses the budget of uncertainty more accurately to adjust the solution's level of conservatism. Extensive numerical studies demonstrate the economic and operational advantages of the proposed RO model for solving the SCED problem in mixed AC‐HVDC power systems with high penetration of RESs. [ABSTRACT FROM AUTHOR]

Power grid restructuring together with the integration of inertia less uncertain renewable generation, has resulted in depletion of inherent primary frequency response in the grid. Characterisation of inter‐area dynamics under uncertain generation and requisite reserve deployment strategies are not very well dealt with in the literature. Uncertainties in deregulated market demand proactive defence strategies to ensure stable and reliable power to consumers. This work depicts the inter‐area oscillation dynamics and proposes a proactive reserve deployment strategy based on probabilistic forecast error modelling. The model of oscillatory dynamics of deregulated power grids is established based on forecast error. The developed model could deliver better insight to wide‐area angular dynamics of the power grid. Reserve index developed on prior knowledge of this angular dynamics and probabilistic renewable generation serves as a key input to proposed proactive reserve deployment strategy defending the probable angular oscillations. WSCC 9‐bus system and IEEE 39‐bus system are adopted to analyse inter‐area angular dynamics as well as validate proposed proactive defence strategies in maintaining the reliable and secure operation of a deregulated grid. [ABSTRACT FROM AUTHOR]

Security constrained unit commitment (SCUC), with renewable resources integrated into power grid, is one core function in the day‐ahead market. However, it confronts with critical challenges as the heavy complicated security constraints are considered. Usually, it is observed that lots of security constraints are redundant, which can be identified and eliminated, so as to reduce the computational complexity. In this study, the authors first lift the uncertain feasible region of SCUC into a high dimensional space. Furthermore, a fast identification method is proposed to relax the original feasible region, which thus can be solved by the classical greedy algorithm. In order to prevent the over‐relaxation and find more redundant constraints, an efficient feasible‐based bound tightening strategy is utilised to provide a tighter bound. Numerical results on large‐scale test systems verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

By means of advanced information and communication technology, cyber‐physical power systems can attain real‐time monitor and control but have to suffer the damage caused by a cyber attack. In this study, the authors' define attack efficiency to evaluate attack paths that attacker may adopt to intrude systems, to find the most efficient attack paths (i.e. the most vulnerable paths). Based on the actual power grid and security stability control system, the coupling model of cyber‐physical power systems is established to analyse the propagation of cascading failure within and across the physical power grid and communication network. In the attack model, the attack cost matrix is built to describe the cost between directly connected nodes in a communication network. Furthermore, considering the probability that control commands are successfully transmitted from router nodes to generator/substation nodes, the total attack cost from the communication network to the physical power grid is figured out. To search for the most vulnerable attack paths in systems, the attack efficiency is proposed to quantify the relation between attack cost and attack gain, wherein the attack gain is the damage on systems caused by the cyber attack. [ABSTRACT FROM AUTHOR]

This study reports the methodology and results of a renewables (REs) integration grid study for the 2030 Japanese power system. In light of the Japanese energy policy outlook for 2030, two scenarios were compared: the government's target scenario with 22–24% RE penetration (64 GW solar and 10 GW wind), and a scenario with higher RE penetration (100 GW solar and 36 GW wind). The impact of these two RE integration scenarios on the grid in terms of frequency stability and power flows were simulated and compared. The evaluation outcomes showed that a RE penetration more ambitious than the government's plan can be achieved without compromising the evaluated elements of grid security and without additional technical measures in situations with at least up to 62% variable REs, i.e. wind and solar, instantaneous penetration in western Japan and at least up to 36% in eastern Japan. Furthermore, technical solutions like soliciting fast frequency response from solar and wind power plants, and setting a system non‐synchronous penetration limit for grid management can be applied to improve grid security for higher RE penetrations. [ABSTRACT FROM AUTHOR]

In many China's enterprise‐owned power grids (EPGs), the frequently changing operation state and the poor reliability of some outdated facilities may lead to inaccuracy or even malfunctions of the traditional pre‐decision‐making emergency control systems, which have already caused several blackouts in EPGs. To solve this problem, a real‐time decision‐making emergency control system based on the detailed time‐domain transient stability simulation is designed. Based on the trajectory characteristics of the stability restoration process of EPGs, the stability restoration criteria are proposed to significantly shorten the simulation time needed to judge the elimination of a certain stability problem. Fast decision‐making algorithms for frequency instability, rotor angle instability and branch overload with relatively low computational cost are introduced. Control strategies can be determined within a specific time after faults are detected. The corresponding countermeasures are directly executed when the strategy is obtained. The system configuration is designed to be capable of dealing with complicated and unanticipated faults, such as cascading outages and unexpected grid splitting. The test results of a 31‐node practical EPG show that the proposed algorithms and the system configuration are practical and efficient. This work is a meaningful exploration of the real‐time decision‐making emergency control system. [ABSTRACT FROM AUTHOR]

For ac electricity grids, the aim has always been at low-cost and disruption-proof solutions. The power grid is inherently vulnerable to environmental disturbances. However, the introduction of power electronics (PEs) and changes in load and generator characteristics have introduced a game changer at an unprecedented pace over the last decade. During this change, load specifications, load characteristics, and control and monitoring requirements for power system security have also dramatically evolved. Efficiency and reliability of system components have progressed in parallel with this evolution. However, high penetration of renewable energy sources has reduced the percentage contribution of conventional electricity based on synchronous generation, which affects grid stability and hence reliability. Furthermore, numerous camouflaged dc generators and dc loads are being embedded in ac and dc microgrids at ever increasing rates. While embedded generation rapidly increases its share in the hybrid power grid (where ac and dc coexist), the current developments in PE switches—based on wide bandgap (WBG) technology—indicate that within the next two decades Max Planck’s well-known sentiment that science advances one funeral at a time will repeat itself on the ac grid. This article aims to summarize the technical developments and problems facing the utilization of ac during widescale electrification of the world using numerous distributed energy resources (DERs). Then, it will map out evolutionary changes toward a future dc grid. [ABSTRACT FROM AUTHOR]

Head‐sensitive forbidden and restricted zones of large hydropower units are challenging the automatic generation control (AGC) as admissible operating zones are discontinuous and variational. This study focuses on the AGC of such a large hydropower plant to ensure the stability, security and timeliness of power grids. A methodology is developed to solve the unit commitment (UC) and load distribution in AGC. This methodology identifies in advance all feasible unit combinations under different water heads and determines admissible operating zones using combinatorial mathematics techniques. A fast strategy that includes the accurate estimation of varying water heads helps to eliminate infeasible unit combinations. Minimising the number of units working in restricted zones and times of unit output passing through forbidden zones is used to optimise the UC, where priority orders of units are introduced to evaluate UC schemes with the same objective value. Finally, a dynamic programming based model is formulated to solve an economic load distribution among operating units. The methodology is applied to the AGC of the Nuozhadu with nine 650 MW units of two different types. Three cases indicate that the number of units working in restricted zones and times of unit output passing through forbidden zones is significantly reduced. [ABSTRACT FROM AUTHOR]

In cyber‐physical power systems, tiny failure occurring in the communication network could propagate to affect the operation of the physical power grid through inter‐links and even cause catastrophic blackouts. The authors propose a partial random coupling systems model to study the vulnerability of nodes and connectivity of systems in a cascading failure. In terms of traffic loads generated in systems, they employ load spill index to analyse dynamic states of nodes in cascading failure. In cascading failure, considering the effect from a communication network, vulnerability matrices are established to study the vulnerability of nodes in the physical power grid. Furthermore, an efficiency index is defined to analyse connectivity of systems. In the numerical simulation, they verify the accuracy of the proposed evaluation approach and test its scalability and universality in different power systems. [ABSTRACT FROM AUTHOR]

Power‐grid partitioning is an important prerequisite for power systems security analysis and control. In this study, a novel recursive grid bipartitioning strategy is proposed. First, two analytical expressions are derived from Kirchhoff's equations to represent coupling relationships between nodes. Then, generator nodes under study are divided into two groups by recursively applying the coupling relationships between generator nodes. Finally, the coupling relationships between generator and load nodes are used to merge relevant load nodes to the corresponding groups of generators. The stopping criterion of the grid bipartitioning process is also discussed. The proposed bipartitioning strategy is implemented on the IEEE 118‐bus system and a practical provincial power grid in China to demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

The continued rise of renewable power generation requires the invention of smart grid technologies, among which communication and remote control are key. Multilevel control strategies improve grid stability and provide the necessary flexibility to address changing demand, contingency, and renewable generation variability. To test these strategies while avoiding damage to existing infrastructure or lab equipment, simulation is employed to facilitate large‐scale control and protection applications. In this work, a hierarchical control strategy is tested in a real‐time simulation environment implementing a moderately large microgrid with 100% renewable generation penetration, using both physical and software‐based controllers, in both local‐ and remote‐control configurations. Additionally, an adaptation is made to the existing hierarchical control strategy to accommodate energy storage balancing amongst distributed resources. The scalability of the testbed and adaptability of the control strategy are tested, and stable operation is observed. [ABSTRACT FROM AUTHOR]

The conventional distribution network is becoming an active grid due to widespread integration of distributed energy resources (DERs). This integration raises great concerns about security of the power system considering the growing interactions between the transmission and active distribution systems. One way to ensure stability of the integrated power system is prediction of critical contingencies which can jeopardize the power system security. Therefore, this paper aims to investigate transient stability contingency ranking in power grids considering the uncertainties raised by DERs of active distribution networks. To this end, probabilistic transient stability prediction framework is provided, in which the probability density function of transient stability condition is calculated based on the normalized stability indicators. The normalized stability indicators are based on the rotor angle and rotor speed. The normalized stability indicators are only utilized in the case of using fault data for prediction. Based on the proposed scheme, the instability of generators is anticipated through the proposed probabilistic transient stability prediction framework. Also, the effects of the probable topology changes on the line overload and also the voltage profile are investigated. Finally, the performance of the proposed method is validated and compared with the time domain simulation under various operating conditions. [ABSTRACT FROM AUTHOR]

The transient stability margin is affected by different fault locations, fault clearing time and fault types that could be provided by protection information. This study presents an analytical on‐line method of determining transient stability margin quantitatively using protection information for multi‐generator system. First, the multi‐machine system is equivalent to a one‐machine infinity‐bus system with the help of complementary cluster centre of inertia‐relative motion. Second, the asymmetric fault models are built using positive rule, and the transient stability margin is then deduced by modelling the piecewise models of generator angles. Third, the practical transient stability margin assessment algorithm is then obtained. The sensitivity and affection mechanism of stability margin affected by fault factors are further derived, and the analytical stability margin is put forward to online access the transient stability margin after fault with the acquisition of the protection information. Finally, four‐generator system, New England system and a real large power grid are used as test systems to verify the effectiveness and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Phasor measurement units (PMUs) are currently the most useful devices to obtain fast, precise, and synchronised measurement data. Owing to the high cost of installation, the minimum number of PMUs required for the full observability of a network must be determined. However, power companies do not consider such optimal PMU installation (OPI), because their main concerns are preventing cascaded tripping and secure grid separation, for which critical buses (CBs) should be prioritised for direct observability. In practice, utility grids (UGs) may lose their full observability status during islanding, which the OPI problem should account for. On the other hand, actual bus‐to‐bus variations in the PMU installation cost are not properly addressed in the PMU installation problem. Considering these practical aspects, an operational‐based multiphase PMU installation approach is proposed here using the grey wolf optimisation algorithm for CB prioritisation. A PMU cost minimisation‐based OPI problem that considers the full observability of each UG during islanding is formulated. To determine quality outputs, logical and unique mathematical equations are developed. A novel multiple bus selection approach is proposed for a phase‐wise bus assortment. The results of the proposed algorithm are compared with those of other existing methods. [ABSTRACT FROM AUTHOR]

As power systems mature into smart grid entities, they face new challenges toward online monitoring and control of the system's behaviour. Burgeoning classes of cyber-attacks are observed which may cause instability of the power grid and system blackouts if not identified. In this study, the authors propose an ensemble Kalman filter based anomaly detector using a relaxation-based solution. Performance of the proposed method is tested with Chi-Square detector and Largest Normalised Residual test. Results of simulations based on real-world data, up to 5000 bus system, demonstrate the effectiveness of the proposed framework over traditional bad data detection in presence of false data injection attack.

High penetrations of wind generation have intermittency and volatility issues in deregulated power system. With increasing penetration of wind power, independent system operator (ISO) faces an enormous challenge in secure operation with intermittency and uncertainty of renewable energy resources. To handle these issues, battery energy storage system (BESS) is a probable solution for enhancing the wind penetration in the electric grid. In this regard, this article proposes a stochastic security constrained unit commitment (SCUC) with BESS considering wind uncertainty. The proposed approach is formulated and solved by Benders decomposition (BD) method which reduces computational time. The goal is to detect the optimal amount of SCUC, locational marginal price (LMP), wind curtailment, and line contingency by performing DC optimal power flow (DCOPF). Numerical case studies are investigated in detail using IEEE Reliability test system (RTS) 24-bus network and simulation results are found to be inspiring.

As electrical power operations tend to be smart grid with strong penetration of renewable energy resources, the evolution of operational technology brings on board another dimension of vulnerabilities with the participation of cyber-physical systems (CPSs). Thus, it becomes essential to perform technical risk assessment and CPS prognosis to envisage the integrity of the system's operational resilience. The communication network elements such as cyber signal transmission, wireless sensor networks (WSNs) and the internet of things (IoTs) converges as a superhighway hub. This seeks to improve on network operations for efficient power delivery of distributed energy resources (DERs) integration grid. It then demands system configuration to be firewalled to avoid operational intrusions and malfunctions. The paper examines the technical threats involved in the paradigm of schemes and mitigation strategies. The areas of study are the vulnerabilities of the DERs integration with CPS, WSNs and IoTs layers. The risk aversion strategies of DERs integration with CPS are also discussed. The study aims to ascertain the intrusion level and responses of the integrated DERs grid in terms of power management. The paper's objective is to present an overview of current developments in the integrated cyber-power systems evolution and the implementation strategies with DERs.

Photovoltaic (PV) systems are weather-dependent. A solar eclipse causes significant changes in these parameters, thereby impacting PV generation profile, performance, and power quality of larger grid, where they connect to. This study presents a case study to evaluate the impacts of the solar eclipse of 21 August 2017, on two real-world grid-tied PV systems (1.4 MW and 355 kW) in Miami and Daytona, Florida, the feeders they are connected to, and the management areas they belong to. Four types of analyses are conducted to obtain a comprehensive picture of the impacts using 1 min PV generation data, hourly weather data, real feeder parameters, and daily reliability data. These analyses include: individual PV system performance measurement using power performance index; power quality analysis at the point of interconnection; a study on the operation of voltage regulating devices on the feeders during eclipse peak using an IEEE 8500 test case distribution feeder; and reliability study involving a multilayer perceptron framework for forecasting system reliability of the management areas. Results from this study provide a unique insight into how solar eclipses impact the behaviour of PV systems and the grid, which would be of concern to electric utilities in future high penetration scenarios.

With the maturity and wide application of the voltage-source converter-based high-voltage direct current (VSC-HVDC) technology in the power grid, the fast-response characteristic of VSC helps to improve the speed of corrective control for the AC/DC hybrid system. This paper presents a corrective control model for AC/DC hybrid grids based on VSC-HVDC. The model is expressed as a typical optimisation model with both the features of the equipment and security constraints of a power network. The corrective control model is dived into an active power sub-model and a reactive power sub-model in order to improve the calculation speed. Case studies of a modified IEEE testing system have been carried out. The results demonstrate the effectiveness of the approach.

DC grounding fault is a typical fault for HVDC system. In order to obtain smoother, faster, and more secure transient process, the DC protection block strategy is used to remove and isolate the converter to prevent the accident enlargement and reduce the impact on devices and power grid when the grounding fault is detected. Two main strategies are commonly taken in this situation: the X block for not >±500 kV and the S block for ±800 kV. There is no specific principle on the strategy choosing for ±1100 kV UHVDC system with hierarchical connection mode. Changji–Guquan ±1100 kV UHVDC transmission project adopting hierarchical connection mode at receiving end. In this study, the effects of different DC block strategies when grounding faults occurred in both converter stations are compared based on PSCAD simulation. The simulation results indicate that the overvoltage at rectifier side has two stages while the overvoltage at inverter side has only one. Taking S block strategy can cause lower overvoltage but longer oscillation duration on grounding current. The proper block strategy for ±1100 kV UHVDC grounding faults is adopting S block at rectifier side and X block at inverter side.

In recent years, large-capacity high-voltage direct currents (HVDCs) have been employed to transfer electricity from the west to the east of China. However, the frequent frequency drops due to HVDC blockings seriously threaten the short-term frequency stability of receiving-end power systems. The existing emergency frequency control strategy is not adaptive to the varying operation conditions and may cause excessive or deficient actions, which could result in inefficient control or high risk of frequency instability. Therefore, a real-time coordinated control strategy is proposed in this study based on the online-updated frequency response model. The model is designed to incorporate multiple types of generators and to reflect the dynamic frequency response of loads. The new control strategy combines multiple control resources, including the emergency demand response and HVDC power modulation, to improve the short-term frequency stability after HVDC failures. By online data preparation and cubic fitting, the nadir of the frequency is expressed as an analytic function of the control variables. A real-time optimisation of emergency controls is achieved to improve the short-term frequency dynamics. Case studies show that the proposed scheme is robust to the varying operation conditions and has lower control cost than the existing control strategy.

This study presents a multi-objective operation optimisation model for urban power grids with flexible switching (FS) stations to comprehensively improve system security and reliability. In the proposed model, uncertainties associated with load variation and component failures are considered. Moreover, constraints after a feeder or transformer N − 1 contingency are preliminarily formulated. The operation problem optimises the apparent power of feeder section loading. The combination of normal boundary intersection and sequential quadratic programming is employed to solve the non-linear optimisation model. A case study carried out on a test 75-feeder distribution grid with FS stations demonstrates the effectiveness of the proposed model and solving method. Compared with conventional distribution loadability, the optimal load distribution solution obtained in this study provides a trade-off between system security and reliability. The coordinated operation optimisation method is suitable for urban smart distribution grids featured by distribution automation and large-scale interconnections.

Dynamic security assessment (DSA) is widely used in dispatching operation systems, and the small signal stability is one of the DSA's most time-consuming calculation methods. In this article, a fast method is proposed aiming to predict the small signal stability metrics of designated oscillation mode, for example frequency or damping ratio. The method is much faster than the simulation and suitable for the online application. First, the t-distributed stochastic neighbour embedding (t-SNE) algorithm is performed which can create a mapping from the power system components to 2D coordinate depending on the electrical distance of each other; then, it will be transformed into a grid structure by meshing operation, on which the convolutional neural network (CNN) model can be run properly. Finally, with a large amount of simulation samples, the CNN model can be well trained using static quantities as its input and small signal stability metrics as its prediction target. While a new operation mode needs to be evaluated, the result will be obtained by CNN directly. The validity of proposed method is verified using online data of State Grid Corp of China. It is proved that the method meets the requirements for speed and accuracy of online analysis system.

Dynamic security assessment is widely used in dispatching operation systems, and calculation speed is one of its most important performance indices. In this study, an improved k-nearest neighbour (k-NN) method is proposed aiming to predict the stability indicators of power system, for example, critical clearing time. The method is much faster than the simulation and suitable for online analysis. Firstly, a simulation sample database is constructed based on historical online data and a logistic regression model with least absolute shrinkage and selection operator is trained to pick the stability features, which are chosen from static quantities like running state and active power of electric elements. While a new operation mode needs to be evaluated, a weighted k-NN is implemented to obtain the most familiar samples in the database using the chosen features; the final result will be determined comprehensively by the familiar samples. The validity of the proposed method is verified by simulation using online data of State Grid Corp of China and different key faults. It is proved that the method meets the requirements for speed and accuracy of online analysis system.

Extensive deployment of interoperable distributed energy resources (DER) is increasing the power system cyber security attack surface. National and jurisdictional interconnection standards require DER to include a range of autonomous and commanded grid-support functions, which can drastically influence power quality, voltage, and bulk system frequency. Here, the authors investigate the impact to the cyber-physical power system in scenarios where communications and operations of DER are controlled by an adversary. The findings show that each grid-support function exposes the power system to distinct types and magnitudes of risk. The physical impact from cyber actions was analysed in cases of DER providing distribution system voltage regulation and transmission system support. Finally, recommendations are presented for minimising the risk using engineered parameter limits and segmenting the control network to minimise common-mode vulnerabilities.

Recently, China Power Grid has built a number of multi-infeed AC−DC systems, as the safety issues caused by voltage fluctuations have drawn much attention. The security device of a DC system is applied to correct voltage. First, it brings a new voltage control mode, classifies the DC system control device and disturbance mode, and puts forward an online evaluation skeleton drawing in AC−DC voltage security regions. Second, the optimisation model of voltage safety regions in different scales has been built based on this skeleton drawing. Finally, the feasibility and effectiveness of this method was proved through simulation of the Institute of Electrical and Electronics Engineers system.

Aiming at the problem of large number of power grids and the difficulty of on-line monitoring, a method of on-line search of typical transmission section considering geographical attributes is proposed. Firstly, the initial partition is divided by the geographical attributes of the station nodes, and the boundary nodes in each partition are further optimised and rationally evaluated to obtain the simplified structure of the grid. Then, the cut-set search algorithm based on matrix operations of graph theory is used to quickly identify the transmission section in the power grid, and the power transmission section with heavy load and low margin is obtained by using the safety margin index of the power grid, which is regarded as a typical transmission section and used as the key monitoring object of power grid. Finally, an actual power grid and local grid are taken as an example to search for the typical transmission section of the system, which can not only find the section given by the operation mode expert but also find the new section, which verifies the practicability and effectiveness of the method.

In order to release the capability restriction of the North–South transmission channels in the 500 kV power grid of Fujian Province, this article studies the application of unified power flow controller (UPFC) to improve the transmission capability under steady-state security restriction with N−1 principle. On the basis of analysis of principle and structure of UPFC, a simplified equivalent model of UPFC is constructed and used in BPA simulation software. The optimal installation scheme and the minimal capacity required of UPFC are determined by comparing the results of power flow calculation in various schemes. The research result shows that the application of UPFC can effectively reduce the N−1 overload problem of the North–South transmission channels, and has a great economic advantage over the traditional solution. Finally, based on the technical and economic analysis, this study puts forward suggestions on the construction of UPFC in the Fujian 500 kV power grid.