Robin Preece

Damping of inter-area oscillations in mixed AC/DC networks using WAMS based supplementary controller

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.

Comparison of Detailed Modeling Techniques for MMC Employed on VSC-HVDC Schemes

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.

Probabilistic Evaluation of Damping Controller in Networks With Multiple VSC-HVDC Lines

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.

International Industry Practice on Power-Quality Monitoring

Monitoring of voltages and currents at system buses gives the network operators information about the performance of their network, both for the system as a whole and for individual locations and customers. There is also demand from the customers and the regulatory agencies to provide information on the actual power-quality (PQ) level. Developments in enabling technology have made it possible to monitor at a large scale and to record virtually any PQ parameter of interest. While many network operators are installing monitoring equipment and while more and more monitors are available, there is a lack of knowledge and agreement on a number of aspects of the monitoring process and on processing the recorded data. As a response to this lack of uniformity in approach, data acquisition, and processing, in February 2011, CIGRE and CIRED established the Joint Working Group C4.112: “Guidelines for Power quality monitoring-measurement locations, processing and presentation of data.” In order to identify the current international industry practice on PQ monitoring, the group carried out a survey in 43 countries across the world. This paper summarizes the key findings from 114 responses to the questionnaire and identifies prevalent industrial practice in PQ monitoring around the world.

Tuning of a Damping Controller for Multiterminal VSC-HVDC Grids Using the Probabilistic Collocation Method

This paper presents a robust probabilistic controller tuning method to improve the damping of critical system modes through the modulation of active power injected by a voltage-source converter-based multiterminal high-voltage direct current (VSC-MTDC) grid. This methodology first establishes the probabilistic locations of the critical modes based on the known variation in power system operating conditions. Following this, the modal linear quadratic Gaussian (MLQG) controller structure is tuned for a set of probabilistic values of critical eigenvalues. The controllers performance following small disturbances in the network for wide-ranging operating conditions is compared with the conventionally tuned MLQG controller designed for the nominal system operating point. The probabilistic collocation method is shown to facilitate robust probabilistic tuning without the need for large numbers of full system linearizations. The test system used incorporates a large wind farm with variable power output connected to the meshed ac network through the VSC-MTDC grid.

The Probabilistic Collocation Method for Power-System Damping and Voltage Collapse Studies in the Presence of Uncertainties

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.

Probabilistic Small-Disturbance Stability Assessment of Uncertain Power Systems Using Efficient Estimation Methods

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.

Risk-Based Small-Disturbance Security Assessment of Power Systems

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.

Damping of electromechanical oscillations by VSC-HVDC active power modulation with supplementary wams based modal LQG controller

This paper presents a Multi Input Single Output (MISO) Modal Linear Quadratic Gaussian (MLQG) Power Oscillation Damping (POD) controller for Voltage Source Converter based HVDC systems. Applying this technique to a small (four machine) test network incorporating parallel HVDC/AC transmission has lead to improved damping of electromechanical modes compared with a traditional Power System Stabilizer (PSS) based controller structure. Furthermore, the MLQG controller has demonstrated greater robustness to varying operating conditions. The performance of the proposed control structure is assessed through small and large disturbance analysis.

Efficient Estimation of the Probability of Small-Disturbance Instability of Large Uncertain Power Systems

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.