Power Imbalance Detection in Smart Grid via Grid Frequency Deviations: A Hidden Markov Model based Approach

We detect the deviation of the grid frequency from the nominal value (i.e., 50 Hz), which itself is an indicator of the power imbalance (i.e., mismatch between power generation and load demand). We first pass the noisy estimates of grid frequency through a hypothesis test which decides whether there is no deviation, positive deviation, or negative deviation from the nominal value. The hypothesis testing incurs miss-classification errors---false alarms (i.e., there is no deviation but we declare a positive/negative deviation), and missed detections (i.e., there is a positive/negative deviation but we declare no deviation). Therefore, to improve further upon the performance of the hypothesis test, we represent the grid frequency's fluctuations over time as a discrete-time hidden Markov model (HMM). We note that the outcomes of the hypothesis test are actually the emitted symbols, which are related to the true states via emission probability matrix. We then estimate the hidden Markov sequence (the true values of the grid frequency) via maximum likelihood method by passing the observed/emitted symbols through the Viterbi decoder. Simulations results show that the mean accuracy of Viterbi algorithm is at least $5$\% greater than that of hypothesis test.Comment: 5 pages, 6 figures, accepted by IEEE VTC conference, Fall 2018 editio

Computational modes and grid imprinting on five quasi-uniform spherical C-grids

Currently, most operational forecasting models use latitude-longitude grids, whose convergence of meridians towards the poles limits parallel scaling. Quasi-uniform grids might avoid this limitation. Thuburn et al, JCP, 2009 and Ringler et al, JCP, 2010 have developed a method for arbitrarily-structured, orthogonal C-grids (TRiSK), which has many of the desirable properties of the C-grid on latitude-longitude grids but which works on a variety of quasi-uniform grids. Here, five quasi-uniform, orthogonal grids of the sphere are investigated using TRiSK to solve the shallow-water equations. We demonstrate some of the advantages and disadvantages of the hexagonal and triangular icosahedra, a Voronoi-ised cubed sphere, a Voronoi-ised skipped latitude-longitude grid and a grid of kites in comparison to a full latitude-longitude grid. We will show that the hexagonal-icosahedron gives the most accurate results (for least computational cost). All of the grids suffer from spurious computational modes; this is especially true of the kite grid, despite it having exactly twice as many velocity degrees of freedom as height degrees of freedom. However, the computational modes are easiest to control on the hexagonal icosahedron since they consist of vorticity oscillations on the dual grid which can be controlled using a diffusive advection scheme for potential vorticity

Off-grid Direction of Arrival Estimation Using Sparse Bayesian Inference

Direction of arrival (DOA) estimation is a classical problem in signal processing with many practical applications. Its research has recently been advanced owing to the development of methods based on sparse signal reconstruction. While these methods have shown advantages over conventional ones, there are still difficulties in practical situations where true DOAs are not on the discretized sampling grid. To deal with such an off-grid DOA estimation problem, this paper studies an off-grid model that takes into account effects of the off-grid DOAs and has a smaller modeling error. An iterative algorithm is developed based on the off-grid model from a Bayesian perspective while joint sparsity among different snapshots is exploited by assuming a Laplace prior for signals at all snapshots. The new approach applies to both single snapshot and multi-snapshot cases. Numerical simulations show that the proposed algorithm has improved accuracy in terms of mean squared estimation error. The algorithm can maintain high estimation accuracy even under a very coarse sampling grid.Comment: To appear in the IEEE Trans. Signal Processing. This is a revised, shortened version of version

Variational finite-difference representation of the kinetic energy operator

A potential disadvantage of real-space-grid electronic structure methods is the lack of a variational principle and the concomitant increase of total energy with grid refinement. We show that the origin of this feature is the systematic underestimation of the kinetic energy by the finite difference representation of the Laplacian operator. We present an alternative representation that provides a rigorous upper bound estimate of the true kinetic energy and we illustrate its properties with a harmonic oscillator potential. For a more realistic application, we study the convergence of the total energy of bulk silicon using a real-space-grid density-functional code and employing both the conventional and the alternative representations of the kinetic energy operator.Comment: 3 pages, 3 figures, 1 table. To appear in Phys. Rev. B. Contribution for the 10th anniversary of the eprint serve

Inverse transonic airfoil design methods including boundary layer and viscous interaction effects

A body-fitted grid embedment technique applicable to inviscid transonic airfoil flow field analysis was developed and verified through a series of tests. Test cases used to verify the technique show that the accuracy of the solution was increased by grid embedding. This enhancement of the solution is especially true when small supercritical zones occur which cannot be adequately described using the main grid only. Results obtained with the SKANFP full potential program are considered with regard to the massive separated flow and high lift and the undesirable unrealistic 'bump' in the vicinity of the separation point due to a mismatch between the unseparated and separated pressure distributions. Techniques used to eliminate this feature are discussed