Vijay Kumar Sood

Dr. Vijay Kumar Sood

Ontario Tech University
orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 March 2021 in IET Energy Systems Integration
Verified
Journal Article
Open access
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PBPedro Betancourt‐Paulino
Pedro Betancourt‐Paulino
RCRodrigo Chamorro
Rodrigo Chamorro
MSMilad Soleimani
Milad Soleimani
FGFrancisco Gonzalez‐Longatt
Francisco Gonzalez‐Longatt
Vijay Kumar SoodVijay Kumar Sood
Vijay Kumar Sood
WMWilmar Martinez
Wilmar Martinez
The conventional structure of operating transmission and distribution systems is currently experiencing new challenges in maintaining the system operability with the significant changes such renewable energy sources inclusion, technology development, infrastructure revolution, and services provision. A futuristic operation management paradigm at the high level of interaction between Transmission System Operators (TSOs) and Distribution System Operators (DSOs) is presented that supports the usage of flexibility services to simplify the congestion management, and ancillary services procurement by involving the DSO actively in the DSO‐TSO boundaries and the downstream network. The architecture considers new actors such as Distributed Services Aggregator, Prosumers, and Services Market Operators. A comparison between the typical grid structure (including the short‐term smart grid requirements) and the proposed one is presented considering different actors and interactions involved in the operation management of the grid. The opportunities and challenges of the proposed architecture are discussed.

12 January 2021 in Electronics
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Journal Article
Open access
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RCRodrigo Chamorro
Rodrigo Chamorro
Alvaro David Orjuela-CañónAlvaro David Orjuela-Cañón
Alvaro David Orjuela-Cañón
DGDavid Ganger
David Ganger
MPMattias Persson
Mattias Persson
Francisco Gonzalez-LongattFrancisco Gonzalez-Longatt
Francisco Gonzalez-Longatt
WMWilmar Martinez
Wilmar Martinez
Frequency in power systems is a real-time information that shows the balance between generation and demand. Good system frequency observation is vital for system security and protection. This paper analyses the system frequency response following disturbances and proposes a data-driven approach for predicting it by using machine learning techniques like Nonlinear Auto-regressive (NAR) Neural Networks (NN) and Long Short Term Memory (LSTM) networks from simulated and measured Phasor Measurement Unit (PMU) data. The proposed method uses a horizon-window that reconstructs the frequency input time-series data in order to predict the frequency features such as Nadir. Simulated scenarios are based on the gradual inertia reduction by including non-synchronous generation into the Nordic 32 test system, whereas the PMU collected data is taken from different locations in the Nordic Power System (NPS). Several horizon-windows are experimented in order to observe an adequate margin of prediction. Scenarios considering noisy signals are also evaluated in order to provide a robustness index of predictability. Results show the proper performance of the method and the adequate level of prediction based on the Root Mean Squared Error (RMSE) index.

31 August 2021 in IEEE Journal of Emerging and Selected Topics in Power Electronics
Verified
Journal Article
Closed access
AHAmir Heidary
Amir Heidary
Kumars RouzbehiKumars Rouzbehi
Kumars Rouzbehi
Ali Mehrizi-SaniAli Mehrizi-Sani
Ali Mehrizi-Sani
Vijay Kumar SoodVijay Kumar Sood
Vijay Kumar Sood
Rapid protection of modern electric networks using Fault Current Limiters (FCLs) is often delayed and limited by the inherent controller, sensor and power electronic unit delays. This paper proposes a novel self-activated fault current limiter (SAFCL), comprised of a DC saturation winding and series AC limiter windings and AC parallel reactor, which limits the fault current in less than 0.4 ms. Furthermore, the advantage of this SAFCL, when compared to a traditional Saturated Core Fault Current Limiter (SCFCL), is that it does not rely on any external controller, sensor, controllable solid-state switch, and battery. In the normal state, the SAFCL behaves as a saturated reactor with a very low impedance and in the fault state cores are entered to the unsaturation region without relying on an external controller which imposes a high impedance to limit the fault, rapidly. The performance of the SAFCL is evaluated through off-line MATLAB, and Maxwell ANSYS FEM simulations, and is also validated by experimental studies conducted on a scaled-down prototype.

5 April 2021 in IETE Journal of Research
Verified
Journal Article
Closed access
SASanjeev K. Aggarwal
Sanjeev K. Aggarwal
LSLalit M. Saini
Lalit M. Saini
Vijay Kumar SoodVijay Kumar Sood
Vijay Kumar Sood
Wind farm layout optimization (WFLOP) is a complex constrained optimization problem. In this paper, an application of biogeography based optimization (BBO) algorithm for large WFLOP is presented and its performance is compared against three other major meta-heuristic algorithms namely genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). The performance is evaluated on the basis of a modified cost of energy fitness function across 25 different wind farm scenarios. Further statistical inference has been drawn on the basis of 99% Confidence Intervals and Student’s t-test which shows that the fitness function values obtained using BBO are better when compared to the other algorithms for the same number of iterations. The execution time in case of PSO is largest, while GA takes the lowest amount of time.

6 May 2022 in Electric Power Systems Research
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Journal Article
Closed access
MBMonalisa Biswal
Monalisa Biswal
MMManohar Mishra
Manohar Mishra
Vijay Kumar SoodVijay Kumar Sood
Vijay Kumar Sood
RBR.C. Bansal
R.C. Bansal
AAAlmoataz Abdelaziz
Almoataz Abdelaziz

25 January 2020
Verified
Book Chapter
Closed access
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Vijay Kumar SoodVijay Kumar Sood
Vijay Kumar Sood
MAMohammad Y. Ali
Mohammad Y. Ali
FKFaizan Khan
Faizan Khan