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Power outages due to cascading failures which are triggered by extreme weather pose an increasing risk to modern societies and draw attention to an emerging need for power network resilience. Machine learning (ML) is used for a real‐time selection process on preventive actions, such as topology reconfiguration and islanding, aiming to reduce the risk of cascading failures. Training data is obtained from Monte Carlo simulations of cascading failures triggered by extreme events. The trained ML‐based decision‐making process uses only predictors that are readily available prior to an extreme event, such as event location and intensity, network topology and load, and requires no further time‐consuming simulations.The proposed decision‐making process is compared to time‐consuming but ideal decision‐making and fast but trivial decision‐making. Demonstrations on the German transmission network show that the proposed ML‐based selection process efficiently prevents the uncontrolled propagation of cascading failures and performs similarly to an ideal decision‐making process whilst being computationally three orders of magnitude faster. [ABSTRACT FROM AUTHOR]

Replacing conventional generation by power electronics based generation changes the dynamic characteristics of the power system. This results among others in the increased susceptibility to sub synchronous oscillations (SSO). This paper proposes a systematic procedure for mitigating the interactions between a DFIG and a series compensated transmission line using the phase imbalance compensation (PIC) concept. The impact of the series and parallel PIC on the resonance behaviour of the grid is first thoroughly investigated. Then, the influence of the system strength on the capabilities of the PIC to mitigate DFIG-SSR is assessed. Based on the findings a design framework which enables the systematic assessment of the series and parallel PIC for mitigating DFIG-SSR is developed and successfully implemented in the modified IEEE 39 bus system. Comparison between both concepts reveals that the parallel PIC is better suited to mitigate DFIG-SSR. The impedance based stability analysis and detailed time domain electromagnetic transient (EMT) simulations are used to respectively screen and validate the results. [ABSTRACT FROM AUTHOR]

Retaining frequency stability is becoming increasingly challenging as the power system incorporates more non-synchronous generation. Assessing the frequency stability in a system has been predominantly completed by focusing on the quantity of connected synchronous kinetic energy in the system, or inertia. This traditionally was considered a function of generator construction – network factors typically were not considered. The research in this paper investigates how network topology, power flow, droop gain distribution, and inertia distribution all impact frequency stability. A generic four-area model has been created that allows discrete system setups. This research has shown that certain topologies lead to a more severe rate of change of frequency. A key finding is that the frequency drop is further increased when there is greater power flow into the area that experiences the disturbance. The extent to which the rate of change of frequency and frequency drop are influenced differently is emphasized, highlighting the need to procure different services depending on which metric is of primary significance at a specific location. [ABSTRACT FROM AUTHOR]

In recent years, voltage source converter (VSC) HVdc has emerged as an excellent solution for transmitting offshore renewable energy sources and strengthening transmission corridors. It is also reported in the literature that VSC-HVdc is able to enhance specific types of stability. With growing capacity of VSC-HVdc and increasing uncertainty in the current power system, it is essential to perform a rigorous analysis of its impact on the interdependence of power system dynamics. This paper presents a methodology for the thorough assessment of the impact of VSC-HVdc on interdependence among four types of stability: small-disturbance rotor angle, large-disturbance rotor angle, frequency, and voltage. This analysis is performed assuming uncertain conditions for various VSC-HVdc topologies and system loading and generation conditions. The impact of the VSC-HVdc on the interdependence of dynamic performance is assessed using the Spearman correlation coefficient as a quantification tool. The results obtained show that a significant alteration over the interdependence between power system dynamics occurs with the addition of VSC-HVdc. [ABSTRACT FROM AUTHOR]

Synchronous generation is being displaced by renewable energy sources and high-voltage direct current (HVDC) interconnectors. These factors will lead to a diminishing provision of ancillary services. Conventional services tendered to provide network support rely on the availability of synchronous generation and because of this, future power system operators will have to develop new ways to obtain the ancillary services required. A technology rapidly gaining in popularity is voltage source converter (VSC)-based HVDC and further advances in the technology have led to the modular multilevel converter (MMC). Due to the design of an MMC there is intrinsic electrostatic energy that could potentially be utilised to provide ancillary services. This study determines the electrostatic energy available from a typical grid-scale MMC VSC for network support during disturbances and for power oscillation damping. Supporting simulations are provided to ascertain the impact that this electrostatic energy could have on network performance if utilised. This study displays that although an MMC possesses intrinsic energy, utilising it for frequency response would provide negligible system benefits. However, for POD, the available intrinsic MMC energy did improve system stability which leads to the potential of using multiple MMCs to increase the energy and further improve system stability. [ABSTRACT FROM AUTHOR]

In many future power systems, the power generation may be predominantly supplied from converter interfaced sources (i.e. wind, solar, HVDC interconnection). In the context of the UK, the government is aiming for a share of wind capacity in the total generation mix as high as 29 GW by 2020. For a small power system like Great Britain (GB) with no synchronous connection to continental Europe, frequency stability is identified as a major challenge. Therefore, additional primary response and inertia (or fast frequency containment response) are anticipated as being required to sustain the frequency stability of the GB system. Here, techno-economic assessment is carried out to explore the overall benefits of various frequency control strategies. Frequency regulation by VSC-HVDC system is realised as the best strategy regarding overall system benefits. [ABSTRACT FROM AUTHOR]

Due to the anticipated proliferation of HVDC links up to and beyond 2020 into transmission systems, it is expected that in some locations, two or more HVDC links will be installed with a short electrical distance between them and will form a multiinfeed (MI)-HVDC scenario for the system. The control and operation of MI-HVDC systems are of particular concern for weak grids such as that likely to be found in the North of Scotland network. It is shown that the ac voltage regulation in the VSC-HVDC link may adversely affect the dynamic performance of the host weak ac system under the MI-HVDC scenario. To overcome this identified limitation associated with the ac voltage controller in the VSC-HVDC link, a new controller modification conforming to the grid code is proposed in this paper. Furthermore, this paper presents a robust control design method for ac voltage control using the fractional order (FO) control design theory. The influences of the proposed FO-based ac voltage controller are assessed alongside various voltage controllers for the representative North Scotland system. It is shown that the FO-based ac voltage controller has favorable effects on the dynamic behavior of weak ac systems with MI-HVDC. [ABSTRACT FROM AUTHOR]

A high level of stochastic dependence (or correlation) exists between different uncertainties (i.e., loads and renewable generation), which is nonlinear and non-Gaussian and it affects power system stability. Accurate modeling of stochastic dependence becomes more important and influential as the penetration of correlated uncertainties (such as renewable generation) increases in the network. The stochastic dependence between uncertainties can be modeled using 1) copula theory and 2) joint probability distributions. These methods have been implemented in this paper and their performances have been compared in assessing the small-disturbance stability of a power system. The value of modeling stochastic dependence with increased renewables has been assessed. Subsequently, the critical uncertainties that most affect the damping of the most critical oscillatory mode have been identified and ranked in terms of their influence using advanced global sensitivity analysis techniques. This has enabled the quantification and identification of the impact of modeling stochastic dependence on the raking of critical uncertainties. The results suggest that multivariate Gaussian copula is the most suitable approach for modeling correlation as it shows consistently low error even at higher levels of renewable energy penetration into the power system. [ABSTRACT FROM PUBLISHER]

This paper establishes a generic severity function that can be used to produce power system security risk profiles. It is illustrated by analyzing the impacts of system load attributes on the small-disturbance rotor angle stability of a power system. The load attributes contributing to the oscillatory modes can be considered as inherent uncertain variables within power systems and include load power variations, load composition, and load model parameters. Uncertainty in the renewable power generation is also incorporated in the probabilistic modelling and risk assessment to demonstrate the flexibility of the approach. A novel approach is proposed to select the severity functions to logically represent small-disturbance security margin. The risk profile of a power system has been presented considering the probability density functions of power system critical modal damping and a selected set of severity functions. The analysis techniques developed are illustrated with a modified version of the 68-bus NETS-NYPS power system with a high amount of renewable power penetration. The relative importance of the load attributes and the impact of these attributes on stability boundaries have been identified at varying risk levels with respect to their contribution to small-disturbance stability. [ABSTRACT FROM PUBLISHER]

This paper critically evaluates a number of sensitivity analysis (SA) techniques to identify the most influential parameters affecting power system small-disturbance stability. SA of uncertain parameters has attracted increased attention with the adoption of deregulated market structure, intermittent energy resources, and new types of loads. Identification of the most influential parameters affecting system stability using SA techniques will facilitate better operation and control with reduced monitoring (only of the parameters of interest) by system operators and stakeholders. In total, nine SA techniques have been described, implemented, and compared in this paper. These can be categorized into three different types: local, screening, and global SA. This comparative analysis highlights their computational complexity and simulation time. The methods have been illustrated using a two-area power system and 68 bus NETS-NYPS test system. The priority ranking of all uncertain parameters has been evaluated, identifying the most critical parameters with respect to the small-signal stability of the test systems. It is shown that for many applications, the Morris screening approach is most suitable, providing a good balance between accuracy and efficiency. [ABSTRACT FROM AUTHOR]

To exploit the full and flexible capability of offshore voltage‐sourced converter high‐voltage DC (VSC‐HVDC) lines, interaction studies in the offshore AC grid are required but are not well understood or reported. This study examines the interaction dynamics of an offshore AC grid for interconnecting large wind power plants (WPPs). The conventional eigenvalue analysis method has limitations which make the interaction analysis of such systems difficult. Hence, in this study, an impedance‐based analytical approach is employed to investigate the interaction phenomena. The impedance model of a VSC‐HVDC converter for both direct and vector control with outer and droop controls are derived along with the impedance model of the full‐converter wind generator. The interaction dynamics of the offshore grid is predicted through the well‐established Nyquist criteria and is validated using time‐domain simulations. The analysis shows that the system stability is decidedly influenced by the control configurations and tuning of the VSC‐HVDC lines. [ABSTRACT FROM AUTHOR]

In order to strengthen the onshore transmission network in many parts of the world, voltage-source current–high-voltage direct current (VSC–HVDC) will increasingly be utilized. The effect of the operating point of a VSC-HVDC link and the control strategies employed can substantially affect the electromechanical oscillatory behavior of the ac network as well as the dc-side dynamics. In order for the full, flexible capability of VSC-HVDC to be exploited, further study of the effects of these controllers and their interactions with ac system responses is necessary. This paper addresses this gap. Both modal analysis and transient stability analysis are used to highlight tradeoffs between candidate VSC-HVDC power controllers and to study the electromechanical performance of the integrated ac/dc model. Tests are carried out on both a generic two-area model and a large-scale realistic network with detailed ac generator and HVDC models. [ABSTRACT FROM PUBLISHER]

This paper critically evaluates a number of uncertainty importance measures for use in power system stability studies. Sensitivity analysis of uncertain system parameters is vital as new technologies proliferate and the total level of system uncertainty grows. Accurate assessment of the importance of different uncertainties can guide power system operators towards parameters which will require the greatest levels of mitigation or increased monitoring in order to reduce the uncertainty and its subsequent impact. Local and global sensitivity analysis techniques are described and evaluated within this paper, including nonparametric methods, variance-based approaches, and distribution-based techniques. The techniques are illustrated using a large 295-bus realistic network model of a generic distribution system. Numerical experiments on dynamic models are used in order to assess the impact of uncertainties on the mitigation of system frequency excursions using single-site and distributed energy storage devices. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology to efficiently estimate the probability of small-disturbance rotor angle instability of uncertain power systems. Traditional Monte Carlo (MC) approaches are computationally intensive and inefficient, particularly when used to study low probability conditions which result in small disturbance instabilities and develop into serious outage events high impact. The proposed methodology uses importance sampling to focus on conditions which contain the high information content required to make relevant decisions about low probability events. Latin hypercube sampling (LHS) is used to efficiently bound the search space and identify operating conditions leading to a marginally stable or unstable system response. The proposed approach is demonstrated on a model of a multi-area transmission network with a significant capacity of intermittent generation connected through a multi-terminal voltage source converter-based high voltage direct current (VSC-HVDC) grid. It is demonstrated that the methodology yields accurate results with just a small fraction of the sample points required using a conventional numerical MC approach. [ABSTRACT FROM PUBLISHER]

This paper proposes a new method for the probabilistic risk assessment of rotor angle instability in power systems using fuzzy inference systems (FISs). The novel two-step approach first models the stochastic uncertainties present within the power system to produced probability density functions (pdfs) for stability indicators. These stability indicators are established for both small and large disturbance rotor angle stability analysis. The pdfs produced are subsequently decomposed into regions based on user-specified threshold values. The outputs from this decomposition are analyzed using fuzzy techniques to complete the risk assessment of instability. The methodology is applied to a multi-area test network into which a VSC-MTDC grid has been embedded to support power transfer from a number of large wind farms. This new combination of probabilistic and fuzzy techniques is shown to provide an effective methodology for quantifying the influence of system uncertainties on the risks of rotor angle stability. [ABSTRACT FROM PUBLISHER]

This paper presents a risk-based probabilistic small-disturbance security analysis (PSSA) methodology for use with power systems with uncertainties. This novel addition to existing dynamic security assessment (DSA) techniques can be used to quantify the small-disturbance stability risks associated with forecasted operating conditions. This approach first establishes the probability density functions (PDFs) for the damping of the critical oscillatory electromechanical modes by modeling the stochastic variation of system uncertainties, such as loading levels, intermittent generation sources, and power flows through voltage-source converter–high-voltage direct current (VSC–HVDC) lines. The produced PDFs are then combined with severity measures (either simple risk matrices or continuous functions) in order to quantify the risk of stability issues for the system associated with the forecasted operating scenario. In addition, the PSSA is used to establish risk-based operational limits and the concept of a probabilistic security margin is introduced to more accurately represent the probabilistic operation of uncertain power systems. The proposed techniques are demonstrated using a multiarea meshed power system incorporating two VSC-HVDC systems, one of which is connected to a large wind farm. [ABSTRACT FROM AUTHOR]

Modular multilevel converters (MMC) are presently the converter topology of choice for voltage-source converter high-voltage direct-current (VSC-HVDC) transmission schemes due to their very high efficiency. These converters are complex, yet fast and detailed electromagnetic transients simulation models are necessary for the research and development of these transmission schemes. Excellent work has been done in this area, though little objective comparison of the models proposed has yet been undertaken. This paper compares for the first time, the three leading techniques for producing detailed MMC VSC-HVDC models in terms of their accuracy and simulation speed for several typical simulation cases. In addition, an improved model is proposed which further improves the computational efficiency of one method. This paper concludes by presenting evidence-based recommendations for which detailed models are most suitable for which particular studies. [ABSTRACT FROM AUTHOR]

This paper presents comparative analysis of the performance of three efficient estimation methods when applied to the probabilistic assessment of small-disturbance stability of uncertain power systems. The presence of uncertainty in system operating conditions and parameters results in variations in the damping of critical modes and makes probabilistic assessment of system stability necessary. The conventional Monte Carlo (MC) approach, typically applied in such cases, becomes very computationally demanding for very large power systems with numerous uncertain parameters. Three different efficient estimation techniques are therefore compared in this paper—point estimation methods, an analytical cumulant-based approach, and the probabilistic collocation method—to assess their feasibility for use with probabilistic small disturbance stability analysis of large uncertain power systems. All techniques are compared with each other and with a traditional numerical MC approach, and their performance illustrated on a multi-area meshed power system. [ABSTRACT FROM PUBLISHER]

This paper explores the feasibility of using the Probabilistic Collocation Method (PCM) in power-system studies in the presence of uncertainties. The application of the PCM is illustrated on small disturbance stability studies and voltage stability studies. First, the PCM is used to determine the effects of a supplementary power oscillation damping (POD) controller installed on a VSC-HVDC line in the presences of parameter and operational uncertainties. Second, it is used to calculate the probabilistic distance to voltage collapse in a distribution system based on measurement errors. The PCM is shown to produce accurate statistical results whilst drastically reducing the computational time of the studies in both cases. Additionally, a ranking process based on eigenvalue sensitivity is presented alongside the small disturbance analysis as an appropriate method for reduction of system complexity for extension to large power systems. This technique is validated through the application of the PCM on a large power-system model, yielding accurate probabilistic results. [ABSTRACT FROM PUBLISHER]

The paper presents a supplementary VSC-HVDC Power Oscillation Damping (POD) controller based on wide area measurement signals (WAMS). The controller is designed as Multi Input Single Output (MISO) using a Modal Linear Quadratic Gaussian (MLQG) methodology in order to target critical inter-area electromechanical modes. The approach has been tested on a large (16 machine, 68 bus) test network incorporating parallel HVDC/AC transmission and has shown improved damping compared to a traditional Power System Stabilizer (PSS) based controller structure utilizing local signals. The design process has incorporated the effects of wide area signal transmission delays. Variation in these signal delays and the complete loss of signals has been also investigated to establish the robustness of the WAMS based controller and its sensitivity to loss of signals. Extension of the controller to incorporate reactive power modulation has been investigated, as has variation in available active power modulation capacity. The proposed controller performance has been assessed through small and large disturbance analysis. [ABSTRACT FROM PUBLISHER]

The paper presents a robust probabilistic methodology for assessing the performance of power system controllers. In this study, the proposed probabilistic technique is applied to a novel power oscillation damping (POD) controller structure implemented through active power modulation of multiple voltage source converter based high voltage direct current (VSC-HVDC) links within a large heavily meshed network exhibiting multiple inter-area modes. The modal linear quadratic Gaussian (MLQG) controller, as an example of advanced POD, is implemented in both a centralized and a decentralized form for comparison. Following the development and demonstration of the effectiveness of the controller designs, the robust probabilistic performance evaluation is carried out incorporating outage contingencies for generators, lines, and VSC-HVDC lines. The results obtained demonstrate that both controller structures are largely robust to wide ranging operating conditions. For those conditions where controller performance is unsatisfactory, various mitigation techniques are discussed, including the use of classification tools to guide operational limits. A contingency specific controller design is shown to significantly improve performance when robustness cannot be achieved. [ABSTRACT FROM PUBLISHER]