Tackling climate change with machine learning
Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …
Machine learning for sustainable energy systems
In recent years, machine learning has proven to be a powerful tool for deriving insights from
data. In this review, we describe ways in which machine learning has been leveraged to …
data. In this review, we describe ways in which machine learning has been leveraged to …
A survey of power system state estimation using multiple data sources: PMUs, SCADA, AMI, and beyond
State estimation (SE) is indispensable for the situational awareness of power systems.
Conventional SE is fed by measurements collected from the supervisory control and data …
Conventional SE is fed by measurements collected from the supervisory control and data …
Joint topology identification and state estimation in unobservable distribution grids
HS Karimi, B Natarajan - IEEE Transactions on Smart Grid, 2021 - ieeexplore.ieee.org
Many distribution system operations (eg, state estimation, control, fault
detection/localization) rely on the assumption that the underlying topology is accurately …
detection/localization) rely on the assumption that the underlying topology is accurately …
Gradient-based multi-area distribution system state estimation
The increasing distributed and renewable energy resources and controllable devices in
distribution systems make fast distribution system state estimation (DSSE) crucial in system …
distribution systems make fast distribution system state estimation (DSSE) crucial in system …
[HTML][HTML] A robust transient and sustainable faults location approach for AC microgrid based on voltage and current difference measurements
The most challenging problem to protect the microgrids is the integration of different types of
distributed generations, which leads to the bidirectional load flow and different fault current …
distributed generations, which leads to the bidirectional load flow and different fault current …
Evaluating the planning and operational resilience of electrical distribution systems with distributed energy resources using complex network theory
Abstract Electrical Distribution Systems (EDS) are extensively penetrated with Distributed
Energy Resources (DERs) to cater the energy demands with the general perception that it …
Energy Resources (DERs) to cater the energy demands with the general perception that it …
Sparsity based approaches for distribution grid state estimation-a comparative study
The power distribution grid is typically unobservable due to a lack of measurements. While
deploying more sensors can alleviate this issue, it also presents new challenges related to …
deploying more sensors can alleviate this issue, it also presents new challenges related to …
A measurement-based approach to voltage-constrained hosting capacity analysis with controllable reactive power behind-the-meter
We propose an efficient method for the assessment of localized voltage-constrained
distributed generation hosting capacity given an engineer's choice or estimate of a power …
distributed generation hosting capacity given an engineer's choice or estimate of a power …
Bayesian framework for multi-timescale state estimation in low-observable distribution systems
S Dahale, B Natarajan - IEEE Transactions on Power Systems, 2022 - ieeexplore.ieee.org
To support the smart grid paradigm, there has been a significant increase in sensor
deployments and metering infrastructure in distribution systems. However, the …
deployments and metering infrastructure in distribution systems. However, the …