Cybersecurity via Inverter-Grid Automatic Reconfiguration (CIGAR)

This project is performing R&D to enable distribution grids to adapt to resist a cyber-attack by (1) developing adaptive control algorithms for DER, voltage regulation, and protection systems; (2) analyze new attack scenarios and develop associated defensive strategies. It is funded by DOE OE's CEDS program and is co-led by [Sean Peisert](https://crd.lbl.gov/departments/data-science-and-technology/idf/staff/sean-peisert/) and [Daniel Arnold](https://eta.lbl.gov/people/daniel-arnold).

UC-Lab Center for Electricity Distribution Cybersecurity

This project will bring together a multi-disciplinary UC-Lab team of cybersecurity and electricity infrastructure experts to investigate, through both cyber and physical modeling and physics-aware cybersecurity analysis, the impact and significance of cyberattacks on electricity distribution infrastructure. It is funded by the [UC-Lab Fees Research Program](https://www.ucop.edu/research-initiatives/programs/lab-fees/). The overall project is led by [Hamed Mohsenian-Rad](http://intra.ece.ucr.edu/~hamed/); the LBNL portion is led by [Sean Peisert](https://crd.lbl.gov/departments/data-science-and-technology/idf/staff/sean-peisert/).

Integrated Multi Scale Machine Learning for the Power Grid

The goal of this project is to create advanced, distributed data analytics capability to provide visibility and controllability to distribution grid operators. It is funded by the [DOE Grid Modernization Initiative](http://energy.gov/doe-grid-modernization-laboratory-consortium-gmlc-awards). The LBNL portion of this effort is led by [Sean Peisert](https://crd.lbl.gov/departments/data-science-and-technology/idf/staff/sean-peisert/).

Power Grid Threat Detection and Response with Data Analytics

The goal of this project is to develop technologies and methodologies to protect the nation's power grid from advanced cyber and all-hazard threats. This will be done through the collection of disparate data and the use of advanced analytics to detect threats and response to them. It is funded by DOE OE's CEDS program via the [Grid Modernization Initiative](http://energy.gov/doe-grid-modernization-laboratory-consortium-gmlc-awards) and is co-led by [Sean Peisert](https://crd.lbl.gov/departments/data-science-and-technology/idf/staff/sean-peisert/).

An Automated, Disruption Tolerant Key Management System for the Power Grid

This project is designing and developing a key management system to meet the unique requirements of electrical power distribution systems. It is funded by DOE OE's CEDS program and is led by [Sean Peisert](https://crd.lbl.gov/departments/data-science-and-technology/idf/staff/sean-peisert/).

Cyber Security of Power Distribution Systems by Detecting Differences Between Real-time Micro-Synchrophasor Measurements and Cyber-Reported SCADA

This project is using micro-PMU measurements and SCADA commands to develop a system to detect cyberattacks against the power distribution grid. It is funded by DOE OE's CEDS program and is led by [Sean Peisert](https://crd.lbl.gov/departments/data-science-and-technology/idf/staff/sean-peisert/).

Application of Cyber Security Techniques in the Protection of Efficient Cyber-Physical Energy Generation Systems

The goal of this project was to design and implement a measurement network, which can detect and report the resultant impact of cyber security attacks on the distribution system network. It was funded by DOE OE's CEDS program and was co-led by [Chuck McParland](https://crd.lbl.gov/departments/data-science-and-technology/idf/affiliates/charles-mcparland/) and [Sean Peisert](https://crd.lbl.gov/departments/data-science-and-technology/idf/staff/sean-peisert/).