Search

This paper presents a clustering technique to rank the dominant modes of low frequency oscillations in power systems under model order uncertainty of the signal. The rotational invariance property of the signal subspace is utilized to obtain the modes of oscillations. Rotational invariance of the signal under multiple shifts is considered to obtain the preliminary estimates of the modes. Subsequently, the modes are clustered to obtain the dominant modes that belong to the signal subspace. A signal subspace participation index (SSPI) is used to rank the modes according to their dominance in signal subspace. Thereafter, the convex combination of the preliminary modes, estimated from the multiple shifts of the signal subspace, is used to obtain the final mode estimates. The simulation results are presented for signal generated using the modes obtained from a two-area system. Additionally, the methodology is also tested on field data obtained from the PMU installed at a generating station in India. [ABSTRACT FROM AUTHOR]

Remote sensing-derived spectral data have been used in the past to partition net radiation, soil heat, and sensible heat fluxes for estimating latent heat flux as a residual of surface energy balance, and thus regional evapotranspiration. Attempts to provide a simplified procedure for estimating sensible heat flux at a regional scale have not been successful because of the relatively strong dependence of the heat transfer coefficient on the land–atmosphere boundary condition. This paper presents a remote sensing-based procedure to estimate the sensible heat flux incorporating the local meteorological conditions, and in turn to determine the regional evapotranspiration. The model utilizes satellite-derived surface albedo, surface temperature, and leaf area index along with a very few agrometeorological data as inputs. The proposed procedure has been tested on a part of the Western Yamuna Canal system, India, and is found to be computationally simple as well as stable. For a well-watered wheat crop, the average evapotranspiration by the proposed model is estimated to be 2.05 mm·d-1 on January 30, 1996, whereas it is estimated to be 1.89 mm·d-1 using the Penman-Monteith equation, indicating a difference of less than 10%. The model is subjected to sensitivity analysis for uncertainties in the observed wind velocity and the computed leaf area index (by ±20%) to estimate sensible heat flux. Results reveal that the percentage change in mean sensible heat flux for the image is less than 5% in all cases, thus indicating the acceptability of the model against the uncertainties. Further, the model has been applied to three sets of Landsat-TM data covering the Sone Low Level Canal system, India, to demonstrate its usefulness in evaluating water delivery performance. [ABSTRACT FROM AUTHOR]