Probabilistic evaluation of transient stability of active distribution networks
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The main objective of the research described in this thesis is to develop appropriate models and techniques for the probabilistic transient stability assessment of active distribution networks and extend the conventional well-being framework to the area of power system transient stability assessment. Transient stability assessment is one of the important aspects in power system planning and operating. The transient stability performance of power systems can be evaluated using either a deterministic method or a probabilistic approach. Deterministic methods are unable to fully recognize and reflect the actual risk associated with a given system and therefore the industry is leaning towards using probabilistic methods. This is particularly true with the introduction of non-dispatchable renewable generation in the energy supply. A probabilistic approach based on Monte Carlo simulation is, therefore, proposed in this thesis to accurately model and evaluate the risk of various uncertainties associated with active distribution networks transient stability performance. The approach utilizes the calculation accuracy of Electromagnetic Transient (EMT) simulator such as PSCAD/EMTDC and computationally-efficient algorithms such as parallel computing to facilitate the probabilistic transient stability evaluation of active distribution networks. A framework for advancing the industry knowledge in the area of power system transient stability well-being analysis is also proposed. Well-being analysis uses an acceptable deterministic criterion incorporated into probabilistic assessment to assign a comfort level to the power system in terms of healthy, marginal, and risk states probabilities. The concepts, models and methodologies are illustrated using the results obtained from studies on a practical active distribution network.