Sharif Digital Repository

This paper proposes a novel formula to calculate sensitivities of electromechanical modes to generators active power changes. Quadratic eigenvalue problem is applied to construct the framework of the proposed formula. Sensitivity factors are calculated using power system model parameters and power flow variables, which can be either obtained via state estimation or measured directly by phasor measurement units. The 39-bus New England power system is used to verify performance of the proposed method  

This paper proposes a comprehensive analytic method for applying various optimal remedial actions to improve critical electromechanical modes damping without jeopardizing damping of non-critical modes and violating security constraints of power system. Generators and reactive power sources redisptach, demand side management and the generators voltage reference tuning are remedial actions that are considered here. Dynamic equations of the flux-decay dynamic model of generators, standard dynamic models of excitation system and power system stabilizer and algebraic equations of active and reactive powers balance are formulated in the quadratic eigenvalue problem framework. With simultaneous use... 

The first spoken dialogue system is developed for the Persian language is introduced. This is a ticket reservation system with Persian ASR and NLU modules. The focus of the paper is on learning the dialogue management module. In this work, real on-line training data are used during the learning process. For on-line learning, the effect of the variations of discount factor (γ) on the learning speed is investigated as the second contribution of the research. The optimal values for γ were found and the variation pattern of the action-value function (Q) in the learning process was obtained. A probabilistic policy for selecting actions is used in this work for the first time instead of greedy... 

This paper proposes a novel error-feedback lattice recursive least-squares (EF-LRLS) filter for online estimation of power system oscillatory modes. The EF-LRLS filter is applied to ambient data provided by phasor measurement units to identify the autoregressive (AR) model parameters. This filter has a modular structure; accordingly, if the length of the filter equals N, it identifies AR(1) to AR(N) models concurrently. In the proposed method, removing very low and high frequencies and re-sampling steps are fulfilled in an online fashion. This adaptive filter has less computational complexity than standard RLS filter, making it an appropriate choice for online system identification. The... 

Online monitoring of inter-area oscillations is a vital need for secure operation of large-scale power systems. This paper aims at online estimation of inter-area modes by a novel stabilized fast transversal recursive least squares (SFTRLS) filter running on ambient power system data received from phasor measurement units. The SFTRLS filter is a fast finite-impulse response adaptive filter that is widely used in communication applications, such as noise and echo cancelation. It has the lowest computational complexity among least-squares filters and directly calculates coefficients of the parametric model selected for identifying a system under study. In the proposed method, the SFTRLS filter... 

This paper proposes a novel error-feedback lattice recursive least-squares (EF-LRLS) filter for online estimation of power system oscillatory modes. The EF-LRLS filter is applied to ambient data provided by phasor measurement units to identify the autoregressive (AR) model parameters. This filter has a modular structure; accordingly, if the length of the filter equals $N$, it identifies AR(1) to ${m{AR(}}N)$ models concurrently. In the proposed method, removing very low and high frequencies and resampling steps are fulfilled in an online fashion. This adaptive filter has less computational complexity than standard RLS filter, making it an appropriate choice for online system identification.... 

This paper presents a model-based method for applying online proactive generators redispatch to improve damping of the critical electromechanical oscillations of power system. The proposed method comprises two stages: 1) monitoring modal characteristics of oscillatory modes in ambient condition, and 2) applying generators redispatch based on sensitivities of the critical mode to the generators active power changes using a new analytic method. An online identification method such as error feedback lattice recursive least square adaptive filter is applied for online estimation of the oscillatory modes. Then, whenever the damping ratio of an identified mode is less than a preset threshold, its... 

Low swirl flame characteristics under external flow excitations are numerically investigated using large eddy simulations with a dynamically thickened flame combustion model. A finite volume scheme on a Cartesian grid with a dynamic one equation eddy viscosity subgrid scale model is used for large eddy simulations. The excitations are imposed on inlet velocity profiles by a sinusoidal forcing function over a wide range of amplitudes and frequencies. Present investigation shows that although, the swirling motion of the low swirl flame is not intense enough to induce a recirculation zone in ensemble averaged results, external flow excitations increase the local swirl number upstream of the... 

This study attempts to examine the natural gas fired power plants in Iran. The required data from natural gas fired power plants were gathered during 2008. The characteristics of thirty two gas turbine power plants and twenty steam power plants have been measured. Their emission factor values were then compared with the standards of Energy Protection Agency, Euro Union and World Bank. Emission factors of gas turbine and steam power plants show that gas turbine power plants have a better performance than steam power plants. For economic analysis, fuel consumption and environmental damages caused by the emitted pollutants are considered as cost functions; and electricity sales revenue are... 

In this paper, we introduce a new dataset for SAD and evaluate certain common methods such as GMM, DNN, and RNN on it. We have collected our dataset in a semi-supervised approach, using subtitled movies, with a labeling accuracy of 95%. This semi-automatic method can help us collect huge amounts of labeled audio data with very high diversity in language, speaker, and channel. We model the problem of SAD as a classification task to two classes of speech and non-speech. When using GMM for this problem, we use two separate mixtures to model speech and non-speech. In the case of neural networks, we use a softmax layer at the end of the network, with two neurons which represent speech and...