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Raksha Ramakrishna
Arizona State University
Stochastic modellingAttenuationComputer sciencePhotovoltaic systemProbabilistic logic
7Publications
2H-index
7Citations
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Publications 12
Newest
May 1, 2020 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Raksha Ramakrishna (ASU: Arizona State University)H-Index: 2
#2Nurullah Karakoc (ASU: Arizona State University)H-Index: 2
Last. Anna Scaglione (ASU: Arizona State University)H-Index: 48
view all 4 authors...
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#1Raksha Ramakrishna (ASU: Arizona State University)H-Index: 2
#2Anna Scaglione (ASU: Arizona State University)H-Index: 48
In this paper, we derive a Bayesian lower bound on the estimation of a scalar parameter whose prior distribution is assumed to have a bounded support. For such truncated prior distributions it is well known that the Bayesian Cramer-Rao bound (BCRB) does not hold. We also analyze the tightness of this bound for maximum a-posteriori estimators (MAP) in the case of conditionally Gaussian observations and highlight some interesting properties. Numerical results illustrate the tightness of this bound...
Source
#1Mahdi JameiH-Index: 7
#2Raksha Ramakrishna (ASU: Arizona State University)H-Index: 2
Last. Sean Peisert (LBNL: Lawrence Berkeley National Laboratory)H-Index: 15
view all 7 authors...
Author(s): Jamei, Mahdi; Ramakrishna, Raksha; Tesfay, Teklemariam; Gentz, Reinhard; Roberts, Ciaran; Scaglione, Anna; Peisert, Sean
Source
#1Raksha Ramakrishna (ASU: Arizona State University)H-Index: 2
#2Anna Scaglione (ASU: Arizona State University)H-Index: 48
Last. Andrey Bernstein (NREL: National Renewable Energy Laboratory)H-Index: 13
view all 5 authors...
In this paper, a stochastic model is proposed for a joint statistical description of solar photovoltaic (PV) power and outdoor temperature. The underlying correlation emerges from solar irradiance that is responsible in part for both the variability in solar PV power and temperature. The proposed model can be used to capture the uncertainty in solar PV power and its correlation with the electric power consumption of thermostatically controlled loads. First, a model for solar PV power that explic...
Source
#1Raksha Ramakrishna (ASU: Arizona State University)H-Index: 2
#2Anna Scaglione (ASU: Arizona State University)H-Index: 48
In this paper we revisit the problem of False Data Injection (FDI) attacks to electric power systems synchrophasors measurements through the lens of graph signal processing (GSP). First, we introduce a physics based model that supports the empirical evidence that Phasor Measurement Unit (PMU) data are low-pass graph signals. This insight is used to investigate how one can leverage such a structure to construct more effective bad data detection (BDD) algorithms that can detect FDI attack signatur...
1 CitationsSource
#1Raksha Ramakrishna (ASU: Arizona State University)H-Index: 2
#2Anna Scaglione (ASU: Arizona State University)H-Index: 48
While the graph theoretic properties pertaining to the electrical grid are well known, the field of graph signal processing offers new insights and understanding about the measurements from the electrical grid. In this paper we establish that voltage measurements are the result of a low-rank excitation to a low-pass graph filter. Then, we illustrate the identification of community structure in the electrical grid since the excitations are low-rank in nature. Proposed algorithm for community dete...
1 CitationsSource
May 1, 2019 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Raksha Ramakrishna (ASU: Arizona State University)H-Index: 2
#2Anna Scaglione (ASU: Arizona State University)H-Index: 48
Last. Cihan Tepedelenlioglu (ASU: Arizona State University)H-Index: 26
view all 4 authors...
In this paper, we present a distributed array processing algorithm to analyze the power output of solar photo-voltaic (PV) installations, leveraging the low-rank structure inherent in the data to estimate possible faults. Our multi-agent algorithm requires near-neighbor communications only and is also capable of jointly estimating the common low rank cloud profile and local shading of panels. To illustrate the workings of our algorithm, we perform experiments to detect shading faults in solar PV...
7 CitationsSource
Sep 10, 2018 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Raksha Ramakrishna (ASU: Arizona State University)H-Index: 2
#2Andrey Bernstein (NREL: National Renewable Energy Laboratory)H-Index: 13
Last. Anna Scaglione (ASU: Arizona State University)H-Index: 48
view all 4 authors...
In this paper, a mathematical relationship between temperature and solar irradiance is established in order to reduce the sample space and provide joint probabilistic forecasts. These forecasts can then be used for the purpose of stochastic optimization in power systems. A Volterra system type of model is derived to characterize the dependence of temperature on solar irradiance. A dataset from NOAA weather station in California is used to validate the fit of the model. Using the model, probabili...
2 CitationsSource
#1Nikhil Ravi (ASU: Arizona State University)
#2Raksha Ramakrishna (ASU: Arizona State University)H-Index: 2
Last. Anna Scaglione (ASU: Arizona State University)H-Index: 48
view all 4 authors...
In this paper, we explore the application of system identification techniques to the inference of a model that characterizes crowd dynamics, inspired by the social force model proposed by Helbing and Molnar. We focus then on sensor observations of pedestrians' actions considering that wearables, smart mobile phones and other IoT devices embedded in the environment give significant insights on their expected mobility patterns. Previous work using IoT sensors to uncover social interactions is not ...
Source
#1Raksha RamakrishnaH-Index: 2
#2Anna ScaglioneH-Index: 48
Last. Vijay VittalH-Index: 1
view all 3 authors...
In this paper, a stochastic model with regime switching is developed for solar photo-voltaic (PV) power in order to provide short-term probabilistic forecasts. The proposed model for solar PV power is physics inspired and explicitly incorporates the stochasticity due to clouds using different parameters addressing the attenuation in power.Based on the statistical behavior of parameters, a simple regime-switching process between the three classes of sunny, overcast and partly cloudy is proposed. ...
1 Citations
12