You can find here more on our work on 1: Frequency Estimation in Smart Grid, 2: 2D and 3D Wind Modelling.

Legend: MATLAB code, PDF files, Supplements.

You can download from here some Wind Data used in some of the simulations in the work below. These are 2D (complex) data, for three different wind regimes of 'low', 'medium', and 'high' dynamics.

Frequency Estimation in Smart Grid

  1. Y. Xia, M. Xiang, Z. Li, and D. P. Mandic, "Echo state networks for multidimensional data: Exploiting noncircularity and widely linear models", in D. Comminiello and J. Principe (editors), Adaptive Learning Methods for Nonlinear System Modelling, pp. 267-288, Elsevier, 2018. [pdf]
  2. A. Stott, S. Kanna, and D. P. Mandic, "Widely linear complex partial least squares for latent subspace regression", Signal Processing, vol. 152, pp. 350-362, 2018. [pdf]
  3. Y. Xia, L. Qiao, Q. Yang, W. Pei, and D. P. Mandic, "Widely linear adaptive frequency estimation for unbalanced three-phase power systems with multiple noisy measurements", Proceedings of the 22nd International Conference on Digital Signal Processing (DSP'17), pp. 1-5, 2017. [pdf]
  4. S. Kanna and D. P. Mandic, "Self-stabilising adaptive three-phase transforms via widely linear modelling", Electronics Letters, vol. 53, no. 13, pp. 875-877, 2017. [pdf]
  5. Y. Xia, Y. He, K. Wang, W. Pei, Z. Blazic, and D. P. Mandic, "A complex least squares enhanced smart DFT technique for power system frequency estimation", IEEE Transactions on Power Delivery, vol. 32, no. 3, pp. 1270-1278, 2017. [pdf]
  6. S. P. Talebi, S. Kanna, and D. P. Mandic, "A distributed quaternion Kalman filter with applications to smart grid and target tracking", IEEE Transactions on Signal and Information Processing over Networks, vol. 2, no. 4, pp. 477-488, 2016. [pdf]
  7. S. Kanna, D. Dini, Y. Xia, R. Hui, and D. P. Mandic, "Distributed widely linear Kalman filtering for frequency estimation in power networks", IEEE Transactions on Signal and Information Processing over Networks, vol. 1, no. 1, pp. 45-57, 2015. [pdf]
  8. Y. Xia, Z. Blazic, and D. P. Mandic, "Complex-valued least squares frequency estimation for unbalanced power systems", IEEE Transactions on Instrumentation and Measurement, vol. 64, no. 3, pp. 638-648, 2015. [pdf]
  9. V. Jaksic, C. Wright, J. Murphy, A. Chanayil, S. F. Ali, D. P. Mandic, and V. Pakrashi, "Dynamic response mitigation of floating wind turbine platforms using tuned liquid column dampers", Philosophical Transactions of the Royal Society A, vol. 373, no. 2035, pp. 1-9, 2015. [pdf]
  10. P. Talebi and D. P. Mandic, "A quaternion frequency estimator for three-phase power systems", Proceedings of ICASSP'15, pp. 3956-3960, 2015. [pdf]
  11. V. Jaksic, R. O'Shea, P. Cahill, J. Murphy, D. P. Mandic, and V. Pakrashi, "Dynamic response signatures of a scaled model platform for floating wind turbines in an ocean wave basin", Philosophical Transactions of the Royal Society A, vol. 373, no. 2035, pp. 1-18, 2015. [pdf]
  12. Y. Xia and D. P. Mandic, "A widely linear least mean phase algorithm for adaptive frequency estimation of unbalanced power system", International Journal of Electrical Power and Energy Systems, vol. 54, pp. 367-375, 2014. [pdf]
  13. Y. Xia, K. Wang, W. Pei, and D. P. Mandic, "A balancing voltage transformation for robust frequency estimation in unbalanced power systems", Proceedings of the IEEE APSIPA'14, pp. 1-6, 2014. [pdf]
  14. Y. Xia and D. P. Mandic, "Augmented MVDR spectrum based frequency estimation for unbalanced power systems", IEEE Transactions on Instrumentation and Measurement, vol. 62, no. 7, pp, 1917-1926, 2013. [pdf]
  15. D. Dini and D. P. Mandic, "Widely linear modeling for frequency estimation in unbalanced three-phase power systems", IEEE Transactions on Instrumentation and Measurement, vol. 62, no. 2, pp. 353–363, 2013. [pdf]
  16. Y. Xia, S. C. Douglas, and D. P. Mandic, "Adaptive Frequency Estimation in Smart Grid Applications: Exploiting Noncircularity and Widely Linear Adaptive Estimators," IEEE Signal Processing Magazine, vol. 29, no 5, pp. 44-54, 2012. [pdf]
  17. Y. Xia and D. P. Mandic,"Widely Linear Adaptive Frequency Estimation in Unbalanced Three-Phase Power Systems," IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 1, pp. 74-83, 2012. [pdf]

Complex valued and quaterion valued 2D and 3D wind prediction

Most of the papers on complex valued and quaternion valued adaptive filtering have wind prediction as a case study. See below for our recent contributions in this field.

  1. C. Cheong-Took, G. Strbac, K. Aihara, and D. P. Mandic"Quaternion-valued short term forecasting of three-dimensional wind and atmpospheric parameters," Renewable Energy, vol. 36, pp. 1754-1760,2011. [pdf]
  2. C. Cheong-Took, D. P. Mandic, and K. Aihara, "Quaternion-valued short term forecasting of wind profile," in Proceedings of IJCNN, pp. 3412-3417,2010. [pdf]
  3. D. P. Mandic, S. Javidi, S. L. Goh, A. Kuh and K. Aihara, "Complex Valued Prediction of Wind Profile Using Augmented Complex Statistics," Renewable Energy, vol. 34, no. 1, pp. 196-201, 2009. [pdf]
  4. S. L. Goh, M. Chen, D. H. Popovic, K. Aihara, D. Obradovic and D. P. Mandic, "Complex-Valued Forecasting of Wind Profile," Renewable Energy, vol. 31, pp. 1733-1750, 2006. [pdf]
  5. Y. Hirata, D. P. Mandic, H. Suzuki, and K. Aihara, "Wind Direction Modelling Using Multiple Observation Points, ," Philosophical Transactions of the Royal Society A, vol. 366, pp. 591-607, 2008. [pdf]
  6. C. Cheong-Took and D. P. Mandic, "The Quaternion LMS Algorithm for Adaptive Filtering of Hypercomplex Processes," IEEE Transactions on Signal Processing, vol. 57, no. 4, pp. 1316-1327, 2009. [pdf]
  7. C. Cheong-Took and D. P. Mandic, "A Quaternion Widely Linear Adaptive Filter ," IEEE Transactions on Signal Processing, vol. 58, no. 8, pp. 4427-4431, 2010. [pdf]
  8. A. Kuh and D. P. Mandic, "Applications of Complex Augmented Kernels to Wind Profile Prediction," Proceedings of ICASSP 2009, pp. 3581-3584, 2009. [pdf]
  9. C. Ujang-Bukhari, C. Cheong-Took, and D. P. Mandic, "Split-Quaternion Nonlinear Adaptive Filtering," Neural Networks, vol. 23, no. 3, pp. 426-434, 2010. [pdf]
  10. S. L. Goh and D. P. Mandic, "A Complex-Valued RTRL Algorithm for Recurrent Neural Networks," Neural Computation, vol. 16, no. 12, pp. 2699-2713, 2004 [pdf]
  11. S. L. Goh and D. P. Mandic, "Nonlinear Adaptive Prediction of Complex-Valued Signals by Complex-Valued PRNN," IEEE Transactions on Signal Processing, vol. 53, no. 5, pp. 1827-1836, 2005. [pdf]
  12. S. L. Goh and D. P. Mandic, "An Augmented Extended Kalman Filter Algorithm for Complex-Valued Recurrent Neural Networks," Neural Computation, vol. 19, no. 4, pp. 1039-1055, 2007. [pdf]
  13. D. P. Mandic, S. L. Goh, and K. Aihara, "Sequential Data Fusion via Vector Spaces: Fusion of Heterogeneous Data in the Complex Domain," International Journal of VLSI Signal Processing Systems, vol. 48, no. 1, pp. 99-108, 2007. [pdf]