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Eversource Energy Center



Author: Hurricane Henri Outage Forecast

OPM prediction:

August 22nd, 2021

Hurricane Henri

Outage Prediction Modeling group
Eversource Energy Center
University of Connecticut

Fourth prediction, released on: 08-21-2021 10:30 a.m. EDT

The Eversource Energy Center Outage Prediction Model at UConn is forecasting a very high impact from Hurricane Henri in Connecticut. The highest relative impact is expected in Eastern Connecticut, and the overall impact in Connecticut is expected to be between 10,000 and 20,000 damage locations.


Hurricane Henri is expected to make landfall in Connecticut (after a first landfall in Long Island). It is still not clear yet whether the hurricane will primarily hit Eastern, Central, or Western Connecticut. In any case, the impact in Connecticut appears to be very severe. The expected impact on the CT electric grid further increased with respect to yesterday’s update.

We are currently excluding a landfall in Eastern Massachusetts. However, this territory will be on the right (strong) side of the hurricane, despite not close to the center, and therefore will experience a moderate impact. A moderate to low impact is also expected in New Hampshire. The expected impact in NH and EMA decreased with respect to yesterday’s update.

For Western Massachusetts there is some uncertainty on the speed and on the weakening rate of the hurricane. If the hurricane slows down and weakens quickly in Connecticut, Western Massachusetts will have a moderate-high impact, while if the hurricane keeps moving North quickly, with a moderate weakening, the impact will be high also on this territory. An intermediate projection for WMA is provided.

Weather Predictions

With a landfall in Central Connecticut, wind gusts are expected to exceed 50 mph for several hours in CT and 45 mph in WMA and EMA.

Long lasting gusts exceeding 40 mph are also expected in New Hampshire.

Up to 5 inches of precipitation are expected in Connecticut and Western Massachusetts, while 2-4 inches are expected elsewhere.

Summary Table

Probability of TS Ranges

Author: NRT Inundation Maps of the European Flood

The UConn team at the Eversource Energy Cener has mapped European flood extent from Jul 15 to 17 spanning West Germany, France, Netherlands, and Luxembourg using a near-real-time tool, the Radar Produced Inundation Diary (RAPID, patent published), based on Sentinel-1 Synthetic Aperture Radar (SAR) satellite. The maps are also provided to the Dartmouth Flood Observatory (DFO). Original maps (created by Qing Yang) in GeoTiff format can be found via Amazon Web Service (AWS). Publications describing the algorithm and the CONUS system can be found online.

Author: Tropical Storm Elsa Outage Forecast


The Eversource Energy Center Outage Prediction Model at UConn is forecasting moderate impact from tropical storm Elsa for Connecticut. As shown at the storm outages maps, the highest impact is expected in Eastern Connecticut, and the overall impact in Connecticut is expected to be between 300 and 600 damage locations.

Author: Wind Whirls to Electricity: Predictive Modeling of Offshore Wind Power

By Georgios Matheou

Offshore wind is an abundant energy resource with significant environmental and economic benefits, but as a natural resource, it is variable. At the Eversource Energy Center the Marine Boundary Layer Modeling project aims to improve the design and operation of wind farms by better characterizing meteorological conditions at the wind-farm scale.

We are currently developing a high-fidelity, high-resolution computational model that is capable of simulating the atmospheric motions around individual wind turbines. To model the flow in the wind farm, we are extending UConn’s Large-Eddy Simulation (LES) model to include wind turbines. LES models are high resolution atmospheric models capable at simulating the wind, thermals, and clouds at spatial scales of a few meters. The newly developed model is able to capture the interaction of individual turbines with the turbulent atmosphere. The new model will allow us to investigate the dependence of overall power output on the environmental conditions and the characteristics of the wind farm, such as the type of wind turbines and their relative positioning.

A comprehensive modeling system is developed to capture the energy flow through the atmosphere. Energy initially enters the system by differential solar heating of the Earth’s surface. Regions near the equator receive more radiant solar heating compared to the regions near the poles. The energy enters the atmosphere through direct heating of the air at the surface and through evaporation in the form of latent heating of the atmosphere. This spatially variable energy flux drives the large-scale atmospheric circulation, weather patterns, and eventually the wind field at the location of the wind farm. Design and operation of the wind farm depends on the details of the wind field at small scales (less than 100 m) and near the surface. Modeling of the entire atmosphere at fine scale is not feasible. Thus, a hierarchy of modeling methods is used to track the energy flow through the system

Numerical weather predilection (NWP) modeling of the entire atmosphere provides information about the global weather patterns. NWP modeling is typically performed by government agencies and the model output is available to researchers. The output of the global model is used as input to a regional weather model which captures wind patterns at smaller scales (about 250 m). Subsequently, the output of the regional model is passed to the LES model that includes the interaction of the wind field with the wind farm. Through this modeling sequence, we are able to produce realistic predictions of energy output and the gather critical information related to equipment maintenance operations.

The wind turbines are converting the kinetic energy of the wind field to electrical power. Similar to the experience of a “bumpy” flight, the turbine blades move through a constantly fluctuating wind field. The fluctuating character of the wind field, or the characteristics of atmospheric turbulence, are important for the efficiency of energy extraction and the structural fatigue of the turbines. Accordingly, the accurate representation of atmospheric turbulence is important in the LES model. The model uses a sophisticated technique to generate a turbulent atmosphere upstream of the wind farm by using a pair of concurrent synchronized LES simulations. An auxiliary LES is carried out to generate a realistic turbulent atmosphere. Data from the auxiliary LES are used as an inflow condition to the main LES which includes the wind farm. 

The following figures show results from the main LES domain. The locations of the wind turbine disks are indicated with black lines. Movies correspond to a horizontal plane at the hub height and a vertical plane along the turbine axis. The color contours correspond to wind speed. The wind speed downstream of the wind turbines decreases as a result of the reduction of the kinetic energy as the atmosphere moves through the wind turbine. Essentially, the plots visualize the extraction of kinetic energy from the atmosphere. Also shown is the importance of atmospheric turbulence as small fluctuations interact with the turbines but also the interactions of the wakes between the turbines. For closely placed turbines as in the figure, the placement to reduce interference of the wakes with the downstream turbines is important because the wakes are regions of low wind speed, thus, less energy can be generated.



Author: New Power Engineering Faculty Joining ECE and the Center

The Electrical and Computer Engineering (ECE) Department and Eversource Energy Center (EEC) are happy to announce the recruitment of two new faculty as part of our cluster hire in the field of power systems engineering:



Dr. Zongjie Wang is currently research associate in Systems Engineering at Cornell University. She earned her Bachelors,Masters, and Ph.D. degrees in Electrical and Computer Engineering at Harbin Institute of Technology (HIT), China. Dr. Wang’s research interests focus on problems in modern power systems and renewable energy through leveraging dataanalytics, optimization and simulation techniques. Her projects include development of new algorithms  for  optimal  power  flow  in  power  systems  with  high  penetration  of renewable energy sources; bi-level optimization between transmissionand distribution systems; comprehensive modeling of distributed generators in active distribution systems; networkequivalent modeling of New York state power system topology; feasible power flow solutions in weakly-meshed activedistribution systems, sensitivity analysis of new extended bus types in power systems. Dr. Wang has a patent “online multi-period power dispatch problems” filed by U.S. in 2020. As an invited speaker, she gave one of her talks at the headquarter ofUS Federal Energy Regulatory Commission (FERC)’s Technical Meeting in DC. She is also a member of PSERC committee and hascollaborations with power system operators in the industries and other institutions, for example, New England ISO, New York ISO, MIT, OhioState University, Technical University of Denmark.


Dr. Junbo Zhao has been an Assistant Professor at Mississippi State University, Starkville, MS, USA since 2019. He received his Ph.D. degree from the Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, VA, USA, in 2018. He was a Research Assistant Professor at Virginia Tech from May 2018 to August 2019. He also did a summer internship at Pacific Northwest National Laboratory from May to August 2017. He is currently the chair of the IEEE Task Force on Power System Dynamic State and Parameter Estimation and the IEEE Task Force on Cyber-Physical Interdependency for Power System Operation and Control, co-chair of the IEEE Working Group on Power System Static and Dynamic State Estimation, the Secretary of the IEEE PES Bulk Power System Operation Subcommittee. He has published three book chapters and more than 100 peer-reviewed journal and conference papers, where more than 50 appear in IEEE Transactions. His research interests are cyber-physical power system modeling, estimation, security, dynamics and stability, uncertainty quantification, renewable energy integration and control, robust statistical signal processing and machine learning. He serves as the editor of IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid and IEEE Power and Engineering Letters, the Associate Editor of International Journal of Electrical Power & Energy Systems, and the subject editor ofIET Generation, Transmission & Distribution. He is the receipt of best paper awards of 2020 IEEE PES General Meeting and 2019 IEEE PES ISGT Asia. He received the Top 3 Associate Editor Award from IEEE Transactions on Smart Grid and IEEE PES Outstanding Engineering Award in 2020.




Author: EEC Welcomes Its First Underrepresented Minority Undergraduate Fellows!

Congratulations to Justin, Frantz, Yleise, Lawrence, Wilmais, Brandon and Enrique on being the first to be named Eversource Energy Center Undergraduate Fellows!

Over the next twelve months each one of them will be mentored by an experienced team of UConn faculty and Center researchers who will engage them in energy research project(s). Over the summer we will also participate in e-meetings with Eversource Energy managers and engineers to facilitate future collaborations with the electric utility industry.


Enrique Casas Cofradia

Plan: Business Admin/Physics

Mentor: Marcello Graziano/Fred Carstensen/Peter Gunther

Topic: EVs/Cost of Renewables

Enrique will assist Peter Gunther and Dr. Marcello Graziano in preparing the overall dataset used for analyzing the drivers of diffusion of EVs, on performing some basic initial statistical analysis, and searching literature for modeling the appropriate inputs for the regional  analysis.  He will thus be introduced to several methodologies, while familiarizing himself with popular public datasets from the US Census, being introduced to exploratory statistical techniques.



Frantz Gabriel

Plan: Civil Engineering

Mentor: Malaquias Peña

Topic: Underwater Acoustics

“Our objective is to perform simulations of underwater sound emissions due to the installation of wind turbine foundations in offshore regions. The intention is to use these simulations to predict high-decibel areas to help in the design of noise suppression systems.”



Justin Bazemore-Travers

Plan: Electrical Engineering

Mentor: Ha Thi Nguyen /Jason Philhower

Topic: Renewable Integration

My name is Justin Bazemore-Travers. I am a twenty-one year old electrical engineering student working on my sixth semester. I am from Manchester, Connecticut and I enjoy spending time with friends and investing in equities in my free time. My research interests are in renewable energy and the electrical grid structures that they power.”



Lawrence Ravel

Plan: Business Accounting

Mentor: Diego Cerrai

Topic: Renewables

“Since I have been here at the University of Connecticut, I always wanted to get involved in the institution’s research opportunities. After taking different classes, I have learned the impact that research has on society, and how we use this information to better our way of living. Coming across the Pioneering Diversity Internship, I thought that this was an amazing opportunity because of the intentionality of the different goals of the research topics like weather prediction, predicting power outages, and even modeling the occurrence of wildfires. With that being said, I believed that this internship opportunity was the best fit for me to not only expand my skills and knowledge but prepare me for the possible postgraduate research opportunities by exposure.”



Yleise Saez

Plan: Electrical Engineering

Mentor: Dave Wanik

Topic: Outage Modeling & Restoration

“I am an Electrical Engineering student at UConn looking forward to researching under Eversource Energy Center. There are many projects about improving systems resilience to extreme weather conditions that give me the opportunity to learn about advanced technology used within EEC. This will also be a great experience to research, as well as work and learn together as a team.”


Wilmalis Rodriguez

Plan: Environmental Engineering

Mentor: Giuliano Sofia & Manos Anagnostou

Topic: Understanding Flood Hazard

Wilma will collaborate in a research team at the Eversource Energy Center, partnering with researchers from Florida Tech and George Mason, on a project that seeks to  Mapping changes in hydroclimatic risk in High Mountain Asia. Specifically, she will be involved in understanding flood hazard using (1) downscaled precipitation data, (2) geomorphological analysis with high-resolution terrain data, (3) statistic data on flood damages.


Brandon Hermoza-Ricci

Plan: Civil Engineering with a Minor in Urban and Community Studies

Mentor: Manos Anagnostou

Topic: Conversion of Infrastructure Systems to Renewable Energy

Brandon is an undergraduate student who is passionate about using infrastructure within urban spaces to address the increasing problems of climate change. Brandon hopes to address the failed planning concepts in American cities during the last century to create new urban environments that are equitable, inclusively diverse, and sustainable. For Brandon, a green economy is one that everyone can participate in, but this fundamentally begins with redesigning the spaces we inhabit to represent that.


Author: Meet the Researcher: Sita Nyame

Nyame has developed an enduring interest for studying natural hazards and developing technology to help people who experience them through her work with the Eversource Energy Center.

UConn today story on Eversource Energy Center undergraduate student researcher Sita.


Rain and snow are normal weather events in many areas. But when weather turns severe in the form of storms, floods, or fires, it can cause massive damage for communities.

Sita Nyame ’18 (CLAS), today an environmental engineering major at UConn, is working with the Eversource Energy Center at UConn Tech Park to develop a prediction model for wildfires, the start of a promising research career.

Nyame spent her childhood in Ghana, an area that is particularly vulnerable to the effects of global climate change.

“When I was young, I saw a lot of environmental issues and didn’t understand why governments wouldn’t deal with it,” Nyame says.

This concern has followed Nyame throughout her life. When Nyame first came to UConn in 2015, she intended to major in environmental engineering, but when she took an introductory anthropology course, she fell in love with the subject.

“At the moment, that was the perfect fit for me,” Nyame says.

Nyame graduated with a degree in anthropology in 2018. After taking a year off, Nyame returned to UConn and is now completing a bachelor’s degree in environmental engineering.

A Big-Picture Outlook

Nyame’s interest in anthropology still has applications for her work as an engineer.

“It definitely gave me a bigger-picture outlook,” Nyame says.

Oftentimes, engineers design a solution without considering how it needs to be integrated into the community using it.

“You can think that, as an engineer, you found the perfect solution, but you bring it into a different culture and they don’t see it as useful,” Nyame says.

As an engineer, Nyame was particularly drawn to studying natural hazards.

“Seeing how these events are very normal in our environment, but in extreme circumstances they do cause a lot of damage and have a severe impact on people’s everyday lives made me interested in studying them,” Nyame says.

Nyame worked on an NSF Partnership for International Research and Education (PIRE) project studying flood predictions in Ethiopia and the impact on food security. When an area swings from drought conditions to flooding, it can be difficult for farmers to plan where and when to plant and harvest crops.

In the work with PIRE, cross-cultural communication was critical. The communities the researchers work with in Ethiopia have a very different culture than the one from which the US-based researchers were coming.

“Talking to community representatives and getting their input and combining it with our input, bringing those two together, and coming up with a solution together was really beautiful,” Nyame says.

A New Project

Looking to expand her research work, Nyame approached Efthymios Nikolopoulos, a PIRE researcher, who introduced her to the principal investigator Emmanouil Anagnostou, professor of civil and environmental engineering and director of the Eversource Energy Center at UConn Tech Park.

Nyame began working with the Center in Spring 2020, developing a wildfire prediction mode under the supervision of Diego Cerrai, assistant professor of civil and environmental engineering and manager of the Eversource Energy Center. This was a great fit for Nyame, who had been following the stories of wildfires breaking out around the world last year.

“It was the icing on the cake to dive into it and see how engineers are going about tacking this issue,” Nyame says.

The model uses factors such as tree dryness, a forest’s proximity to roads, wind patterns, and human factors to predict where and when wildfires will break out.

“Every week and everything we do I’m surprised by and intrigued by— Sita Nyame

Before a wildfire, energy companies cut off service because electrical wires can become dangerous during a blaze. This model will help companies better prepare for instances in which they need to cut off power.

“The hope of the model is to help companies predict wildfires before they happen, so they can get resources to people who will be impacted and limit outages,” Nyame says.

The model is currently focused on California, which regularly experiences devastating wildfires, but can be applied to other areas. This model could be useful for local government agencies who need to plan how to distribute resources to combat natural disasters.

Nyame’s role on the project is to complete data analysis, something she had little previous experience with from her engineering classes.

“Every week, and everything we do, I’m surprised by and intrigued by,” Nyame says.

Nyame was thrust into the center of a problem without a clear solution, but with a supportive team of other researchers.

“You just get thrown into a project and figure it out with everyone else,” Nyame says. “If it goes wrong, people are always around to help, so I never feel alone.”

Nyame hopes to continue working on this project while completing her Ph.D.

“Because of this research, I’ve gained the motivation to complete my engineering degree,” Nyame says.

After completing her Ph.D., Nyame wants to become a professor or work in the industry doing research and design, maintaining a focus on natural hazards.

“It definitely gave me insight into the engineering major. It helps you see the different things you can do with your major,” Nyame says. “This research has shown me the possibility of combining multiple aspects to find something I’d like to do.”

Research Driven by Industry Need

Nyame is one of many undergraduate students who gain a unique research experience working at the Center. Whereas traditional research labs focus narrowly on a specific research challenge, the Center incorporates students into an interdisciplinary team tackling challenges relevant to industry partners.

“They do gain a lot, and we gain a lot because they are very motivated, and that’s a great help to the project and the progress we’re making,” Anagnostou says.

The Center includes students from a variety of majors including engineering, physics, math, statistics, and computer science, as well as social sciences like economics.

By nature of the problems the Center is addressing, they need an interdisciplinary team to consider engineering, business, and community concerns.

“You do see a whole range of expertise coming together under the same roof,” Anagnostou says. “No matter where they go, they’ll have to be able to understand a problem holistically.”

The work students complete at the Center helps prepare them technically and mentally for work they will do as graduate researchers.

“The path we are trying to give students is to guide them through the research and to further studies they can do at the graduate level,” Cerrai says.

As the work at the Center is driven by industry needs, students can see a direct impact of their research on society.

The Center is  deeply committed to recruiting students from minority populations. The Center recently established a diversity scholarship which provides minority undergraduate students with $2600 for the spring, summer, or fall semester to work on the Center’s research project.

“We’re looking for students who are excited about research and we are keen in enhancing diversity and inclusion in the research environment,” Anagnostou says.

Anyone interested in joining the research team at the Eversource Energy Center should contact Emmanouil (Manos) Anagnostou at emmanouil.anagnostou@uconn.edu.

Author: Eversource Energy Center (EEC) New Research Projects

The EEC recently hosted a workshop where principal investigators had the opportunity to present new research projects kicked off in the areas of (i) Preparedness and emergency response, (ii) Vegetation management & risk analysis, (iii) Cyber and physical security and (iv) Renewable energy. These projects will run through Spring 2023 and project milestones and deliverables will be visible through the Center website.

Below is links to each project presentation grouped by thematic area.


Preparedness and Emergency Response


The UConn OPM – Enhancing Prediction Accuracy & Supporting the Emergency Response Team with Real-Time Outage Forecasts

PI Anagnostou, Co-I Cerrai

Improving Extreme Weather Forecasting Capabilities in Support of Power Outage Prediction Activities

PI Astitha

Resilience System Modeling and Dynamic Economic Impacts

PI Bagtzoglou, Co-I Zhang


Projecting Dynamic Economic Impacts of System Resilience

PI Carstensen, Co-I Graziano, Gunther


Vegetation Management and Risk Analysis

Vegetation Management and Modeling to Promote Resilient Trees, Power, and Communities

PI Fahey, Co-I Worthley

Landowner Planning for Roadside Forest Management Given Multiple Stressors

PI Morzillo


Assessing Forest Risk to Infrastructure Using Remotely Sensed Imagery

PI Zhu

Fine-Scale Assessment of Vegetation Risk to Infrastructure Using Remotely Sensing Imagery and LiDAR Data

PI Witharana

Cyber and Physical Security


Protecting Critical Infrastructure from UAV Threats- Developing an Integrated Multi-Sensor System for UAV Detections

PI Witharana


Evaluation of Eversource-CT Substations Vulnerability of Flooding in Current and Climate Change

PI Shen, Co-I Sofia and Anagnostou


Securing Power Distribution Grid Against Power Botnet Attacks

PI Fei Miao

Renewable Energy

Fine Resolution Nowcasting of PV and Loads in Key Sections of the Eversource Energy Grid

PI Pena, co-I David Wanik

High-Resolution Mapping of Renewable Energy Sources

PI Anagnostou, Co-I Nikolopoulos and Francois

Monitoring, Analysis and Prediction of Offshore Wind

PI Pena

High-resolution Wind Prediction Capabilities

PI Astitha

Marine Boundary Layer Modeling

PI Matheou

Author: EEC Celebrates Undergraduate Research

The Microgrid Project

In the rural regions of Ethiopia, long periods of drought can have severe food security and economic consequences. A collaboration of UConn undergraduate students from various engineering disciplines and social sciences guided by faculty and graduate students at the Eversource Energy Center, sought to address this problem by designing a microgrid for rural Ethiopia, employing renewable energy sources (solar and hydropower) and taking into consideration the social needs of local farming communities that reside in the country’s smallest administrative units, or kebele. Overall, the study examined the sustainability of the microgrid as an energy source that supports farming activities by providing power for irrigation groundwater pumping, with the excess generated energy made available for community needs, such as heating, lighting, and cooking. In addition to enhancing food and health security, the system has the potential to improve the general quality of life in rural Ethiopia. Upon installation of such a microgrid, future studies may focus on the social dynamics and resulting new habits of local people, in order to optimize its performance and tailor its service to specific community needs. A paper on the project is currently under review for publication by the peer-reviewed journal, Sustainability.

Himaja Najireddy and Natalie Roach, from UConn’s Department of Sociology, initially collected important information and social data related to the study area in Ethiopia, such as individual and communal needs, as well as habits and activities of the local society, which were later employed in the design and optimization phases of the sustainable microgrid. Then, they conducted a thorough analysis on the potential social impact of the proposed system, while they provided recommendations on the necessity of educational activities that would ensure the sustainability of the endeavor. Sophie Macdonald, from the Department of Mechanical Engineering, was part of the engineering group that designed and optimized the microgrid. She utilized multi-paradigm computer programming and advanced software to assist in all research phases, from the preparation and analysis of hydroclimatic data, to the scenario-based design process and evaluation of results.

Finally, all students aided in the preparation of a research article that is currently under review in the peer-reviewed journal Sustainability, by reviewing the current bibliography and writing sections related to their contribution.

Natalie Roach Himaja Najireddy Sophie Macdonald

Other examples of the excellent research our students have completed include those listed below:



Xinyu Lin

Xinyu’s work centers on applying the integrated groundwater footprint index (iGF) to Ethiopia. The groundwater footprint concept, originally introduced in 2012, is a measurement tool used to quantify and qualify how sustainably water resources are being used in a location. The iGF accounts for the annual abstraction rate, recharge rate, the groundwater contribution to environmental stream flow, and potential contaminants. This work will contribute to the currently limited knowledge on groundwater resources in Ethiopia and further the sustainable use of groundwater in irrigation practices.


Berk Alpay

“Thunderstorms are complex phenomena that cause substantial power outages in a short period. Predicting these outages is difficult using eventwise models, which summarize the weather dynamics over the entire course of the storm. Instead, we developed a framework designed for models to learn the dynamics of thunderstorm-caused outages directly from hourly weather forecasts. Our work was published in 2020 in the journal Forecasting.”


Sita Nyame

“I am combining large data (environmental, climate, anthropogenic) with state-of-the- art
machine-learning models to develop a Fire Ignition Model to predict the likelihood of wildfire
ignition in proximity to overhead electric distribution and transmission networks. I have been performing computational analysis using MATLAB to study the contributing factors to wildfire ignitions. I have also generated parameter files using R to use as training data for the Fire
Ignition Model. I am working on utilizing the Fire Ignition Model to generate preliminary results
using cross validation methods.”


William Hughes

“As an undergraduate, I was fortunate to have the opportunity to work with EverSource Energy Center in their cutting-edge research project on power grid resilience. Under the exceptional guidance of Professors Zhang and Bagtzoglou, in addition to a multitude of other professors and industry workers, I was able to gain practical research experience firsthand. The work is rewarding knowing the problems being tackled will lead to real-world impacts improving infrastructure reliability under extreme storms to
reduce power outages and improve daily well being. My experience as an undergraduate culminated in my honors thesis and later first publication while inspiring me to continue to graduate school, where I had a head start thanks to the skills I had gained.”

Aaron Spaulding

Aaron is currently studying mathematics and electrical engineering at the University of Connecticut and has been working at the UConn Eversource Energy Center to build and tune machine learning modules used to predict outages. His recent focus has been on predicting tree failure following extreme weather events in northern Italy and helping build and validate an extreme event model for the Eversource service territories.

Author: January 2021 Mozambique Flooding captured by RAPID system

The RAPID flood maps are also integrated into Dartmouth Flood Observatory (DFO)’s flood mapping web service (https://floodobservatory.colorado.edu/Events/5015/2021Mozambique5015.html).

Eversource Energy Center | Innovation Partnership Building: 159 Discovery Drive, Unit 5276, Storrs, CT 06269-5276 | E-Mail: eversourceenergycenter@uconn.edu