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The social economy is growing rapidly, and the power grid load demand is increasing. To maintain the stability of the power grid, it is crucial to achieve accurate and rapid power system stability assessment. In the actual operation of the power network, data loss is an unavoidable situation. However, most of the data‐driven models currently used assume that the input data is complete, which has obvious limitations in real‐world applications. This paper suggests an IVS‐GAN model to assess power system stability using incomplete phasor measurement unit measurement data with random loss. The proposed method combines the super‐resolution perception technology based on generative adversarial network (GAN) with a time‐series signal classification model. The generator adopts a 1D U‐Net network and uses convolutional layers to complete and recover missing data. The discriminator adopts a new gated recurrent unit–attention architecture proposed here to better extract voltage temporal variation features on key buses. The result of this paper is that the stability evaluation method outperforms other algorithms in high voltage data loss rates on the New England 10‐machine 39‐bus system. [ABSTRACT FROM AUTHOR]

Maintaining stability in modern power systems is challenging due to complex structures, rising power demand, and load disturbances. The integration of renewable energy sources further threatens stability by causing imbalances between generation and demand. Conventional load frequency stabilization methods fall short in such scenarios. This paper proposes an optimal fractional‐order proportional‐integral‐derivative‐acceleration (FOPIDA) controller, enhanced by a robust adaptive neuro‐fuzzy inference system (ANFIS), to improve load frequency control and reliability in power systems with wind and solar generators. First, the dynamical model of a multi‐area interconnected power system, including a thermal power plant, wind turbine, and solar photovoltaic generators, is developed. A decentralized ANFIS‐FOPIDA controller is then designed for load frequency control objectives. The gains of this controller are optimized using the whale optimization algorithm (WOA), focusing on frequency deviation and tie‐line power exchange. Simulations on a New England IEEE 10‐generator 39‐bus power system demonstrate the approach's effectiveness under various disturbances, including random load‐generation disturbances and nonlinear generation behaviors. Comparisons with other strategies, such as fractional order (FO) beetle swarm optimization algorithm (FOBSOA)‐FOPIDA, WOA‐PIDA, and WOA‐ANFIS‐PIDA, and recent control approaches highlight the superior performance of the WOA‐ANFIS‐FOPIDA method in enhancing power system stability. [ABSTRACT FROM AUTHOR]

This paper offers non‐linear control for enhancing the transient stability in power systems containing a photovoltaic (PV) and doubly fed induction generator (DFIG) by transient energy function (TEF) method and finite‐time observers. At first, the TEF method is utilized to enhance the transient stability in a power system containing a PV, DFIG, and synchronous generator (SG) by constructing a hybrid Lyapunov function. Then, the derivative terms in control are estimated with finite‐time observers. The main contribution of the research is the application of the TEF technique in the transient stability evaluation of a power system consisting of PV, SG, and DFIG. Another innovation of the research is the simultaneous control of DFIG and PV, whose uncertain parameters are estimated with the use of finite‐time observer. The proposed non‐linear control scheme is robust against changes in the configuration of the power system. In order to show the capability of this control scheme, time domain simulations are performed on the IEEE 9‐bus, and the NEW ENGLAND Standard 39‐Bus power system. Using the obtained result, some comparisons are made with the back‐stepping control scheme to clarify the superiority of the proposed method. The comparisons show that the proposed non‐linear control scheme can properly provide extra damping to reduce the first‐swing fluctuations in less time. The manuscript contains the new original results of the authors' research. In this article, to maintain and improve the transient stability, a new controller with simultaneous management of photovoltaic (PV) and doubly fed induction generator (DFIG) has been developed. The contributions of the paper are as follows. (1) The transient energy function (TEF) is obtained for the power system containing synchronous generator (SG) and DFIG. (2) The control laws are acquired with four PV and DFIG control variables. (3) The derivative parameters of the PV and DFIG controls by a finite‐time observer are estimated. [ABSTRACT FROM AUTHOR]

The goal of contingency ranking is to provide a list of possible critical situations and rank them according to the severity of their impact on a power network. The methods of contingency ranking may be divided into two major categories: static and dynamic techniques. Static approaches are fast and can be implemented in real‐time, but they present different results depending on the parameter which has been selected for contingency ranking. Dynamic methodologies are more accurate than static ones, but they are time‐consuming. This paper presents a novel combined static and dynamic method for contingency ranking which takes advantage of both techniques and shows the performance evaluation for the hybrid method using accuracy and efficiency as criteria. The proposed method uses three well‐known static indices and the Lyapunov spectrum based dynamic approach to select the worst critical lines. IEEE 39‐bus (New England grid) and IEEE 118‐bus networks are utilized to verify the proposed method. The method provides speed and accuracy. One of the prominent features of the proposed approach is its ability to rank contingencies that lead to network load flow divergence. [ABSTRACT FROM AUTHOR]

The increasing interactivity between energy carrier networks such as electrical, natural gas (NG), and heating can be appropriately used for improving the operation optimality along with overcoming some challenges of those systems. With such a view, this paper studies the practical issue of power transmission lines congestion management in integrated multicarrier energy systems (MCESs) and makes a comparison with the only electrical operation mode. The MCES consisting of electrical and NG network infrastructures with exchanged energy between them is modelled by considering the several local energy hubs and their electrical and heat loads. Rescheduling of energy sources (power plants and gas wells) and demand side management in both electrical and NG networks have been utilized as the two important tools in the developed congestion alleviation framework. The proposed method confirms that the provided flexibility in the integrated operation of the MCESs can lead to a remarkable reduction in the congestion management cost index. Implementing the proposed congestion management framework on an assumed test MCES with a combined 39‐bus New England power system and 20‐node Belgium NG system demonstrates its effectiveness and applicability for the system operators. The issue of power transmission lines congestion management in integrated multi‐carrier energy systems (MCESs) has been studied. The proposed method confirms that the provided flexibility in the integrated operation of the MCESs can lead to reduction in the congestion management cost. [ABSTRACT FROM AUTHOR]

Conventional power systems function under the assumption that loads are uncontrollable, and that the generation control is the primary means of preserving system voltage, frequency, and stability. Thanks to recent advancements of power electronics technology and communication schemes, demand‐side resources are now capable of providing fast frequency regulation. Controllable loads can provide upward/downward reserve during frequency excursions. In this paper, the authors consider collective contribution of large clusters of controllable loads which modulate their aggregate demand power to regulate the primary frequency. Koopman model predictive control is designed to handle local frequency variations caused by various disturbances at each load bus, considering uncertain load models. The efficacy of the proposed method has been validated using the New‐England power system considering two scenarios, namely, load variation, and generation outage. [ABSTRACT FROM AUTHOR]

Mid-long term voltage stability refers to voltage stability concerning the dynamics of the slow dynamic elements and protection devices in power systems. To improve the mid-long term voltage stability, this paper proposes a scheme of model predictive control (MPC) based on Galerkin method. The basic principle of MPC is to solve the optimization problem regarding voltage stability control based on the prediction model periodically. By applying the optimal control scheme to power systems, the mid-long term voltage stability can be enhanced. The Galerkin method-based polynomial approximation approximates the relationship between mid-long term trajectories and control parameters by a polynomial function. The polynomial function acts as a prediction model to predict future system trajectories under different values of control parameters in MPC. The advantage of the proposed method is that its prediction accuracy is relatively high and thus the control efficiency of MPC is improved, as the polynomial function can embody the non-linear characteristics of the power system. In the case study, the 3-machine 10-bus system and the New England 39-bus system are taken as examples to compare the MPC based on the proposed method and the trajectory sensitivity method in terms of prediction accuracy, computation time and control results. [ABSTRACT FROM AUTHOR]

This paper aims to improve transient stability using the Ant Colony Optimization for Continuous Domains (ACOR). This improvement is obtained by solving the Transient Stability Constrained Optimal Power Flow (TSCOPF) problem and extracting the sensitivity coefficients. The presented costs minimization approach requires less execution time to manage energy resources efficiently and compared to other conventional methods, it also outperforms based on statistical indicators such as mean and standard deviation. Furthermore, the sensitivity analysis of the suggested method considers the active power generation of the generating units along with their terminal voltage, which notably decreases the operation cost and reduces risk to the power system. On the other hand, the application of ACOR algorithm can reduce the fuel cost of power system operation to 60,928.36 $/h with a decrease of 15.33 $/h compared to the conventional method with a standard deviation equal to 2.51 $/h and an execution time of 7.66 s. This strategy could be used in power system dispatching. This method is implemented on the New England 39 bus system, and the results demonstrate the method's efficiency compared to other conventional methods. [ABSTRACT FROM AUTHOR]

Transient stability is one of the major features of power systems operation which can be also considered an objective function in the flexible AC transmission systems (FACTS) allocation problem. This paper introduces a general multi‐level multi‐objective optimisation framework and its application on optimising the size and location of the improved hybrid flow controller (IHFC). IHFC is a new member of the FACTS family whose ability to control power flow and improve power system stability has been investigated. The optimisation problem considers economic and stability‐based objective functions simultaneously, and the allocation problem is formulated as a non‐linear programming (NLP) problem. The New England 39‐bus system has been used as a case study to demonstrate that the proposed framework can provide efficient and economically viable solutions to the allocation problem. [ABSTRACT FROM AUTHOR]

Due to the expansion of the decarbonization in modern power systems, particularly the high integration of renewable energy resources, more and more uncertainties and variabilities are brought to electricity systems. These uncertainties change the system operating conditions and face the power system with unknown issues. The secure operation of modern power systems requires developing security assessment techniques that effectively mitigate the variation of the operating conditions. This paper proposes a novel continuous learning scheme for online static security assessment (SSA) that enables the periodic renovation of the assessment model. The scheme consists of a Mondrian forest (MF)‐based training model and database generation approach conducting characteristics of operating conditions. The employed security index is a new weather‐depended performance index whose ambient temperature can affect line ratings. After the new training set is generated in the update procedure, the MF algorithm is updated using this data. Eventually, the SSA model is enriched with current circumstances in the power system. The proposed scheme is examined using real‐world data mapped to the New England 39‐bus and 118‐bus standard test systems. The effectiveness and superior performance of the proposed method are demonstrated using various criteria and measures. [ABSTRACT FROM AUTHOR]

Increased wind power penetration and induction loads have deteriorated the voltage stability performance of the power system. This study proposes a multi-stage multi-objective dynamic VAR source placement method for wind energy power system, where three sub-objectives are optimised simultaneously: (i) investment cost and operational control cost; (ii) steady-state voltage stability index; (iii) short-term voltage stability index. This method coordinates the dynamic VAR allocation decisions with preventive and corrective stability controls, including wind power curtailment, modification of the line drop compensation, and load shedding, to improve both steady-state and short-term voltage stability of the system. A robust parameter design technique called Taguchi's Orthogonal Array Testing is used to model the wind power uncertainty. Pareto optimal solutions are obtained for flexible decision-making. The computation burden is mitigated by candidate buses selection and critical contingency identification. The proposed model is demonstrated on the New England 39-bus test system using PSS®E. Compared with conventional approaches, it can achieve higher voltage stability level with less overall cost and moderate wind power curtailment, and at the same time avoid the conservativeness of planning decisions. [ABSTRACT FROM AUTHOR]

A well-designed scheme is essential for assessment and protection of the stability of power system after an unanticipated event. This paper proposes a strategy for regulating three-phase faults and other events that endanger frequency or voltage stability of the system. The aim is to promptly identify such events utilizing supervised learning-based classification modules, and initiate suitable emergency control. The imbalances of active and reactive power after an event have been utilized to predict the stability of system. A new optimization-based formulation has been presented for estimation of reactive power imbalance. An event predicted as unstable is counteracted by prompt load shedding. Conventionally, load shedding is based on frequency or voltage information independently which reduces the effect of load shedding. This work proposes a new load shedding procedure considering both active and reactive power. The proposed scheme is tested on New England (NE) 39-bus system and Northern Regional Power Grid (NRPG) 246-bus system, and results of load shedding have been compared with two existing load shedding schemes. The results indicate the accuracy of classification modules in identifying faults and unstable events, and the proposed load shedding restores stability of the system with less amount of load shed and better voltage profile. [ABSTRACT FROM AUTHOR]

This paper aims to improve transient stability using the Ant Colony Optimization for Continuous Domains (ACOR). This improvement is obtained by solving the Transient Stability Constrained Optimal Power Flow (TSCOPF) problem and extracting the sensitivity coefficients. The presented costs minimization approach requires less execution time to manage energy resources efficiently and compared to other conventional methods, it also outperforms based on statistical indicators such as mean and standard deviation. Furthermore, the sensitivity analysis of the suggested method considers the active power generation of the generating units along with their terminal voltage, which notably decreases the operation cost and reduces risk to the power system. On the other hand, the application of ACOR algorithm can reduce the fuel cost of power system operation to 60,928.36 $/h with a decrease of 15.33 $/h compared to the conventional method with a standard deviation equal to 2.51 $/h and an execution time of 7.66 s. This strategy could be used in power system dispatching. This method is implemented on the New England 39 bus system, and the results demonstrate the method's efficiency compared to other conventional methods. [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 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]

Voltage source converter-based multi-terminal HVDC (VSC-MTDC) system has been considered for interconnecting asynchronous power grids for improved system operation efficiency and reliability. In this study, a frequency response control strategy is proposed for the VSC-MTDC systems that can enable operating reserves sharing among the interconnected asynchronous grids. The proposed control strategy consists of three frequency control components: MTDC primary frequency control, corrective frequency control, and MTDC secondary frequency control. The MTDC primary frequency control could keep the frequency of a disturbed power grid stable and avoid the frequency dropping into an unacceptable level when a sudden power imbalance event occurs. The corrective frequency control strives to guarantee the settled frequency can be within the predefined secure frequency range. The MTDC secondary frequency control provides a novel optimal allocation strategy for considering the participation of MTDC system for restoring system frequency back to the nominal frequency with the lowest cost. The simulation results, based on a modified IEEE New England 39-bus system modelled in PSCAD/EMTDC, show the effectiveness of the proposed frequency response control strategies. [ABSTRACT FROM AUTHOR]

Since the initial objective of power system stabiliser (PSS) units and flexible AC transmission system (FACTS) devices is the damping of inter-area and local oscillations, it is very substantial that the network electromechanical oscillatory modes are identified for tuning the controller of large-scale interconnected power systems. In this research, a method based on the combination of continuous wavelet transform and Prony algorithm is presented to study low-frequency electromechanical oscillations of the power system. The coordinated design of PSS and FACTS parameters become a multi-objective optimisation problem that will be solved using the SPEA II. The residue method is used to improve damping and satisfy the controller constraints of the suggested power systems. Finally, the proposed method of mode estimation and controller design is simulated on the two well-known test case systems, namely IEEE 2-area 4-generator and New England-New York 68-bus 16-generator systems using MATLAB software. The results represent accurate performance and validity of the proposed method to improve oscillation damping, dynamic stability of the power systems. [ABSTRACT FROM AUTHOR]

Unit restarting after a blackout is the basis of the overall restoration process for a power system. A reasonable restarting sequence of units may speed up the restoration process and reduce economic loss. In view of the situation that there are usually several black-start sources in a large-scale power system, a global optimisation method for unit restarting considering black-start zone partitioning is proposed in this study. On the basis of the multiple time-step modelling framework, the optimisation problem is formulated as a mixed integer linear programming model, with the objective functions to maximise the total-weighted MWh output and minimise the links between the subsystems under various operational constraints. The hierarchical method based on generalised Benders decomposition is applied to decompose the optimisation problem into one master problem and two sub-problems: (i) determination of the unit restarting sequence considering only the grouping of units and (ii) rationality check of unit grouping and check of operational constraints based on power flow calculation. The master problem and sub-problems are alternately and iteratively solved until the optimal solution is obtained. The results of New England 10-unit 39-bus system and a practical power system in southwest China verify the validity of the proposed method. [ABSTRACT FROM AUTHOR]

From the power systems security point of view, determining the voltage stability margin is essential for the operation of systems. An inaccurate determination of the maximum loading factor or voltage collapse point in a power system may cause voltage instability and blackout of the system. So, applying a proper method with high accuracy and high speed is vital in analysing voltage stability in power systems. This article presents a novel method based on Thevenin equivalent of power systems to accurately determine load‐ability margin using phasor measurement units (PMUs) data. The proposed method is based on the fact that at the voltage collapse point, the characteristic curves of 'the reactive power at the receiving end' and 'the reactive power of the load' in the weakest bus are tangential to each other. Furthermore, online application of the proposed method requires accurate estimation of the 'ZIP load model' and 'Thevenin equivalent' of the system. The proposed method is designed to determine the load‐ability margin, ZIP load model and Thevenin equivalent of the power system, simultaneously. This characteristic of the method makes it possible to be applied for online voltage stability assessments. To demonstrate the effectiveness of the proposed method, the simulation results for IEEE 14‐bus, 39‐bus New England and IEEE 300‐bus are presented and analysed. [ABSTRACT FROM AUTHOR]

Generally, the mathematical formulation of the dynamics governing multi-area power systems with Unified Power Flow Controller (UPFC) is a challenging task owing to the presence of both differential and algebraic sub-systems. The proposed research work attempts to integrate the two subsystems by replacing the algebraic subsystem with a differential approximant that leads to a non-linear system of differential equations. Solution of the proposed model with a properly chosen Lyapunov function produce a nonlinear control signal which damps inter-area oscillations effectively. The non-linear control signal is realised using the backstepping method. Moreover, the new formulation enables utilisation of the law for uncertain parameters using the standard parametric feedback form, such that the advantage of such a controller is unaffected by these parameters. In addition to this major contribution, full utilisation of UPFC, by using a lone multi-variable PI controller which eliminates negative interaction between the controllers, is also achieved. Empirical verification of the proposed approach is done by simulating various scenarios with varying degrees of complexity -- from dual area power networks to 39 buses New England system. The results of the experiments indicate the efficacy of the method. [ABSTRACT FROM AUTHOR]

This work proposes a novel relative electrical distance measure that provides information of coupling between voltage and apparent power between two buses in power systems. Relative electrical distance measure is derived from the bus admittance matrix which can be obtained in real time using Phasor Measurement Units. Based on the relative electrical distance measure, in this work, an isoperimetric clustering based algorithm for partitioning power systems into voltage-apparent power coupled areas is proposed. The advantage of the partitioning algorithm proposed in this work is that large networks can be represented as a weighted graph with number of vertices equal to number of generators in the system which is much lesser than the size of system, thereby reducing the computational effort for partitioning. Isoperimetric clustering technique along with k-means is then applied to the graph to obtain voltage-apparent power coupled areas. Simulations carried out on New England 39-bus system and IEEE 118-bus system demonstrate the effectiveness of the proposed methodology for partitioning the system into voltage-apparent power coupled areas, subject to changes in the operating condition of the system. The quality of clustering is analysed and compared with Cheeger inequality bounds, which ensures that power system is well partitioned. [ABSTRACT FROM AUTHOR]

This study presents a H∞ mixed-sensitivity robust control design to improve the overall damping performance of lowfrequency oscillations for power systems with doubly fed induction generator-based (DFIG) wind power generation. The supplementary damping controller is designed in the linear matrix inequality framework which allows the placement of the closed-loop poles inside a pre-defined region for improved stability. The damping signal is implemented at the reactive power modulation of the rotor-side converter of the DFIG wind turbine (DFIG-WT). The damping contribution of the power oscillator damper is compared with that provided by the power system stabiliser (PSS) of the synchronous generator (SG). State-space system analysis and time-domain simulations show the capability of DFIG-WT to enhance the overall damping of the oscillatory modes even if PSSs are not installed at SG s. Also, the designed controller shows a robust performance to wind speed variations. The performance evaluation is based on the revised two-area four machines system and the revised New England 39-bus system. [ABSTRACT FROM AUTHOR]