42 research outputs found

    A novel method for power system stabilizer design

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    Power system stability is defined as the condition of a power system that enables it to remain in a state of operating equilibrium under normal operating conditions and to regain an acceptable state of equilibrium after being subjected to a finite disturbance. In the evaluation of stability, the focus is on the behavior of the power system when subjected to both large and small disturbances. Large disturbances are caused by severe changes in the power system, e.g. a short-circuit on a transmission line, loss of a large generator or load, loss of a tie-line between two systems. Small disturbances in the form of load changes take place continuously requiring the system to adjust to the changing conditions. The system should be capable of operating satisfactorily under these conditions and successfully supplying the maximum amount ofload. Power system stability is defined as the condition of a power system that enables it to remain in a state of operating equilibrium under normal operating conditions and to regain an acceptable state of equilibrium after being subjected to a finite disturbance. In the evaluation of stability, the focus is on the behavior of the power system when subjected to both large and small disturbances. Large disturbances are caused by severe changes in the power system, e.g. a short-circuit on a transmission line, loss of a large generator or load, loss of a tie-line between two systems. Small disturbances in the form of load changes take place continuously requiring the system to adjust to the changing conditions. The system should be capable of operating satisfactorily under these conditions and successfully supplying the maximum amount ofload. This dissertation deals with the use of Power System Stabilizers (PSS) to damp electromechanical oscillations arising from small disturbances. In particular, it focuses on three issues associated with the damping of these oscillations. These include ensuring robustness of PSS under changing operating conditions, maintaining or selecting the structure of the PSS and coordinating multiple PSS to ensure global power system robustness. To address the issues outlined above, a new PSS design/tuning method has been developed. The method, called sub-optimal Hoo PSS design/tuning, is based on Hoo control theory. For the implementation of the sub-optimal Hoo PSS design/tuning method, various standard optimization methods, such as Sequential Quadratic Programming (SQP), were investigated. However, power systems typically have multiple "modes" that result in the optimization problem being non-convex in nature. To overcome the issue of non-convexity, the optimization algorithm, embedded in the 111 University of Cape Town sub-optimal Hoo PSS design/tuning method, is based on Population Based Incremental Learning (PBIL). This new sub-optimal Heo design/tuning method has a number of important features. The method allows for the selection of the PSS structure i.e. the designer can select the order and structure of the PSS. The method can be applied to the full model of the power system i.e. there is no need for using a reduced-order model. The method is based on Heo control theory i.e. it uses robustness as a key objective. The method ensures adequate damping of the electromechanical oscillations of the power system. The method is suitable for optimizing existing PSS in a power system. This method improves the overall damping of the system and does not affect the observability of the system poles. To demonstrate the effectiveness of the sUb-optimal Hoo PSS design/tuning method, a number of case studies are presented in the thesis. The sub-optimal Hoo design/tuning method is extended to allow for the coordinated tuning of multiple controllers. The ability to tune multiple controllers in a coordinated manner allows the designer to focus on the overall stability and robustness of the power system, rather than focusing just on, the local stability of the system as viewed from the generator where the controllers are connected

    Performance Comparison of No-preference and Weighted Sum Objective Methods in Multi-Objective Optimization of AVR-PSS Tuning in Multi-machine Power System

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    Simultaneous optimization of controllers in power systems is a challenging research due to the inherent nonlinearity of such a system. Multi-objective optimization is a useful tool for tuning excitation controllers and minimizing oscillations that are described through definition of transient and small-signal stability in power systems. In this paper, a Two-Area-Four-Machine (TAFM) power system model is tested on multiple short circuit and load disturbances. A multi-objective performance analysis is investigated by observing the system\u27s behaviour in different cases involving the no-preference method and a priori method called weighted sum objective. The analysis is done through observation of two different objective functions. First objective function includes the sum of the integral of time-weighted absolute errors of rotor speed differences, generator voltage, and tie-line power transfer. Second objective function observes time domain elements: overshoot, undershoot, and settling time of machines\u27 rotor speeds. Results are compared for two methods combined with four different algorithms to provide better insight into the computational performance of each algorithm and objective search method. Algorithms used for controllers\u27 parametrization include two novel algorithms: multi-objective ant lion optimizer (MOALO) and salp swarm algorithm (MOSSA), and two classic algorithms: multi-objective particle swarm optimization with velocity relaxation (MOVRPSO) and simulated annealing (MOSA)

    Optimal coordination of TCSC and PSS2B controllers in electric power systems using MOPSO multiobjective algorithm

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    Oscillations are an intrinsic phenomenon in interconnected power systems, leading to steady-state stability, safety decline, transmission power limitation, and electric power systems’ ineffective exploitation by developing power systems, particularly by connecting these systems to low-load lines. In addition, they affect the economic performance of the systems. In this study, PSS2B power system stabilizers and TCSC compensators are used to improve the stability margin of power systems. In order to coordinate TCSC compensators, the MOPSO multiobjective algorithm with integral of the time-weighted absolute error (ITAE) and figure of demerit (FD) objective functions was used. The MOPSO algorithm optimization results are compared with nondominated sorting genetic algorithm (NSGAII) and multiobjective differential evolution (MODE) algorithms. The optimization results indicated a better performance of the proposed MOPSO algorithm than NSGAII and MODE. The simulations were iterated in two scenarios by creating different loading conditions in generators. The results indicated that the proposed control system, where the coordination between PSS2B power system stabilizers and TCSC compensators using the MOPSO algorithm, is better than power systems in which PSS2B Stabilizers or TCSC compensators are utilized solely. All criteria, e.g., ITAE, FD, maximum deviation range, and the required time for power oscillation damping in hybrid control systems, have been obtained. This means more stability and accurate and proper performance

    Clustering methods for the efficient voltage regulation in smart grids

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    In this paper, clustering methods are presented to enhance the stability of automatic voltage regulators using the efficient adjustment of their respective gains. The results show that implementations of some of the clustering algorithms provide better reliability and stability for the feedback-based voltage regulators as compared to the other methods, namely, a model predictive controller (MPC), a gaussian mixture model (GMM), a self-organizing mapping (SOM) and hierarchical clustering (HC) methods. Specifically, the K-Means clustering approach (KM) provided superior stability but a slower rise time of the output voltage of the voltage regulators as compared to the other methods. Furthermore, coordination of the clustering methods is tested for a 10 machine, 39 bus power grid system. The results show that the clustering approach could be applied to improve the efficiency of voltage regulation methods in smart grids and related cyber-physical systems

    Smart Control of Automatic Voltage Regulators using K-means Clustering

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    The future cyber physical systems consist of voltage regulators distributed across wide geographical areas. In this paper, a smart control approach of voltage regulators is presented for cyber physical system applications. The approach is implemented using K-means clustering algorithms that use data from voltage and current sensors, compute the correlation of changes across the regulators and generate a proportional feedback. Advanced estimation methods are used in cases where the data from the sensors was not available. The results show that the approach could be used to improve the performance of networked, power dependent systems by 94.5% in terms of overshoot and 9.52% in terms of response time as compared to other methods of controlling voltage regulators

    Epidemiology of Injury in English Women's Super league Football: A Cohort Study

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    INTRODUCTION: The epidemiology of injury in male professional football has been well documented (Ekstrand, Hägglund, & Waldén, 2011) and used as a basis to understand injury trends for a number of years. The prevalence and incidence of injuries occurring in womens super league football is unknown. The aim of this study is to estimate the prevalence and incidence of injury in an English Super League Women’s Football squad. METHODS: Following ethical approval from Leeds Beckett University, players (n = 25) signed to a Women’s Super League Football club provided written informed consent to complete a self-administered injury survey. Measures of exposure, injury and performance over a 12-month period was gathered. Participants were classified as injured if they reported a football injury that required medical attention or withdrawal from participation for one day or more. Injuries were categorised as either traumatic or overuse and whether the injury was a new injury and/or re-injury of the same anatomical site RESULTS: 43 injuries, including re-injury were reported by the 25 participants providing a clinical incidence of 1.72 injuries per player. Total incidence of injury was 10.8/1000 h (95% CI: 7.5 to 14.03). Participants were at higher risk of injury during a match compared with training (32.4 (95% CI: 15.6 to 48.4) vs 8.0 (95% CI: 5.0 to 10.85)/1000 hours, p 28 days) of which there were three non-contact anterior cruciate ligament (ACL) injuries. The epidemiological incidence proportion was 0.80 (95% CI: 0.64 to 0.95) and the average probability that any player on this team will sustain at least one injury was 80.0% (95% CI: 64.3% to 95.6%) CONCLUSION: This is the first report capturing exposure and injury incidence by anatomical site from a cohort of English players and is comparable to that found in Europe (6.3/1000 h (95% CI 5.4 to 7.36) Larruskain et al 2017). The number of ACL injuries highlights a potential injury burden for a squad of this size. Multi-site prospective investigations into the incidence and prevalence of injury in women’s football are require
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