A Partnership of UConn and Eversource

Eversource Energy Center

 

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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.

Presentations

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).

Author: Virtual M.S. Presentation

You are invited to join us for a public presentation in webinar format entitled “Science Communication With Digital Tools: A Story Map for Stormwise Forest Management” where NRE MS candidate Kerste Milik will present the work she has conducted developing an interactive StoryMap for the UConn Stormwise program. She will discuss the StoryMap product itself as well as her experience in developing it and linking the process to her MS program, which has focused strongly on science communication.

The webinar will be next Wednesday 12/9 at 1 pm and should run 30-45 minutes depending on how many questions you ask her.

The WebEx link for joining the session is here:

https://uconn-cmr.webex.com/uconn-cmr/j.php?MTID=mfe6dd9e5cd2e8b634ce4da245de09d3c

Author: Hurricane ETA caused flooding in Mexico

These maps are adopted by International Disaster Charters/United Nations accessible at https://disasterscharter.org/web/guest/activations/-/article/flood-large-in-mexico-activation-683-

Tabasco, Mexico

                      October 30-31, 2020

                         November 5-6, 2020

Coatzacoalcos, Mexico
 

                      November 2-3, 2020

                      November 5-6, 2020

Author: New Power Engineering Faculty Position Announcement

Position Announcement

Title: Assistant/Associate/Full Professor – Nicholas E. Madonna Professorship in Electrical and Computer Engineering

Department: Electrical and Computer Engineering

Search #2020199

Campus/Location: Storrs Campus

Subject Area: Power Systems Engineering

Position Summary

The Electrical and Computer Engineering (ECE) Department and Eversource Energy Center (EEC) at the University of Connecticut (UConn) solicit applications for the Nicholas E. Madonna Endowed Professorship, a tenure-track faculty position at the associate or full professor level.  Strong applicants at the assistant professor level will also be considered. The position has an expected start date of August 23, 2021.  The successful candidate will advance education and research in the Electrical and Computer Engineering Department with a particular emphasis in power systems engineering or related specialties and lead EEC’s research programs in the area of grid modernization.

In addition, candidates whose scholarship and background is well-aligned with entrepreneurship, commercialization, and economic development are particularly encouraged to apply for additional tenure track positions at all ranks. Such candidates, in addition to excellence in their field of expertise, must demonstrate a successful track record as a serial entrepreneur or technology innovator.

Founded in 1881, the UConn is a Land Grant and Sea Grant institution and member of the Space Grant Consortium. It is the state’s flagship institution of higher education and includes a main campus in Storrs, CT, four regional campuses throughout the state, and 13 Schools and Colleges, including a Law School in Hartford, and Medical and Dental Schools at the UConn Health campus in Farmington. The University has approximately 10,000 faculty and staff and 32,000 students, including nearly 24,000 undergraduates and over 8,000 graduate and professional students. UConn is a Carnegie Foundation R1 (highest research activity) institution, among the top 25 public universities in the nation. Through research, teaching, service, and outreach, UConn embraces diversity and cultivates leadership, integrity, and engaged citizenship in its students, faculty, staff, and alumni. UConn promotes the health and well-being of citizens by enhancing the social, economic, cultural, and natural environments of the state and beyond. The University serves as a beacon of academic and research excellence as well as a center for innovation and social service to communities. UConn is a leader in many scholarly, research, and innovation areas. Today, the path forward includes exciting opportunities and notable challenges. Record numbers of undergraduate applications and support for student success have enabled the University to become extraordinarily selective.

The ECE Department (http://www.ee.uconn.edu) is ABET accredited and ranks in the top 50 nationally according to the latest NRC rankings].  The EEC has an endowment that exceeds $10M with state-of-the-art facilities including a high-end grid simulator and is investing in research programs indistributed energy resources in the power grid and grid modernization methods.

The successful candidate will be expected to develop and sustain an internationally-recognized and externally-funded research program in power systems engineering. The position offers the successful candidate, at the associate or full professor level, the Nicholas E. Madonna Endowed Professorship.  The individual appointed to the Professorship will be a nationally or internationally recognized researcher, scholar, and teacher, and will have made significant contributions to power systems engineering.

The successful candidate must also share a deep commitment to effective instruction at the undergraduate and graduate levels, development of innovative courses and mentoring of students in research, outreach, and professional development.

It is the expectation that the candidate will enhance inclusion and broaden participation among members of under-represented groups; as demonstrated through their research, teaching, and/or public engagement, strengthen the richness of diversity in the learning experience; integrate multicultural experiences into instructional methods and research tools; and provide leadership in developing pedagogical techniques designed to meet the needs of diverse learning styles and intellectual interests.

The successful candidate will:

  • Have a research focus on power systems engineering with emphasis on advanced power systems and grid modernization
  • Contribute to the ECE Department academic, research and outreach mission and the mission of EEC.
  • Teach undergraduate and graduate courses that meet the curricular needs of the ECE department.
  • Advise and mentor undergraduate and graduate students.
  • Provide service and leadership to the University of Connecticut, to external academic and scientific communities, and to the general public.

Minimum Qualifications

  1. Completion of all requirements for a Ph.D. in Electrical Engineering or a closely related field by the time of the appointment. Equivalent foreign degrees are acceptable.
  2. Research credentials in Electrical and Computer Engineering specifically power system engineering.
  3. A background that provides preparation for teaching excellence in undergraduate and graduate courses in ECE.
  4. Excellent oral and written communication skills.
  5. Strong interpersonal skills.
  6. Demonstrated success in original research, and publication of that work in archival journals.
  7. Experience with oral presentations at national or international scientific meetings.
  8. Candidates should have established significant research programs with a track record of securing external funding as well as demonstration of a leadership role as the PI of large research grants.

Preferred Qualifications

  1. Research credentials that complements existing faculty expertise.
  2. Experience in collaboration with industry.

This is a 9-month tenure-track position with an expected start date of August 23, 2021. The successful candidate’s primary academic appointment will be at the Storrs campus with the possibility of work at UConn’s regional campuses across the state. Salary and rank will be commensurate with qualifications.

Select “Apply Now” to be redirected to Academic Jobs Online to complete your application. Please submit the following and include your last name as well as search #2020009 in the document title for each document submitted:

  • A cover letter
  • Curriculum Vita
  • A three- to five- page research plan (innovative concepts that will form the basis of academic career, experience in proposal development, mentorship of students, etc.)
  • A two-to-three page teaching plan (including teaching philosophy, teaching experience, commitment to effective learning, concepts for new course development, etc.)
  • Commitment to diversity statement (including broadening participation, integrating multicultural experiences in instruction and research and pedagogical techniques to meet the needs of diverse learning styles, etc.)
  • Additionally, please follow the instructions in Academic Jobs Online to direct four reference writersto submit letters of reference on your behalf.

Employment of the successful candidate will be contingent upon the successful completion of a pre-employment criminal background check.  (Search 2020199)

This position will be filled subject to budgetary approval.

All employees are subject to adherence to the State Code of Ethics, which may be found at http://www.ct.gov/ethics/site/default.asp.

Direct inquiries to Mary P. McCarthy (mary.p.mccarthy@uconn.edu)

The University of Connecticut is committed to building and supporting a multicultural and diverse community of students, faculty, and staff. The diversity of students, faculty, and staff continues to increase, as does the number of honors students, valedictorians and salutatorians who consistently make UConn their top choice. More than 100 research centers and institutes serve the University’s teaching, research, diversity, and outreach missions, leading to UConn’s ranking as one of the nation’s top research universities. UConn’s faculty and staff are the critical link to fostering and expanding our vibrant, multicultural, and diverse community. As an Affirmative Action/Equal Employment Opportunity employer, UConn encourages applications from women, veterans, people with disabilities, and members of traditionally underrepresented populations.

Author: Hurricane Sally Inundation Map

Author: Vulnerable Trees, High Winds, Other Factors Combined for Unusually Severe Storm Damage from Isaias

Aug. 14, 2020

STORRS, Conn. – Gypsy moth infestations and drought conditions in recent years have weakened trees throughout Connecticut to such an extent that forests were particularly vulnerable when the remnants of Hurricane Isaias swept through on Aug. 4, causing extensive power outages related to tree damage.

Those factors, along with the capricious storm’s unusual timing and localized pockets of extreme winds, made it more difficult than expected to predict the extent of possible electrical outages and create accurate restoration plans, according to a new analysis by the UConn-based Eversource Energy Center.

The center, based in UConn’s Innovation Partnership Building, is a research lab that develops storm damage modeling technology and forecasting to help Eversource – New England’s largest energy delivery company – plan for reliable service throughout Connecticut and New England.

Hurricane Isaias had weakened to a tropical storm by the time it reached Connecticut, but was unique in several ways that converged to contribute to the power outages that lasted for several days, according to the EEC’s analysis.

The EEC issued five predictions to Eversource between Aug. 1 and Aug. 4 for the utility company’s territory, and also shared four with United Illuminating, the state’s other large electric supplier. In almost every case, each report predicted significantly increasing storm severity, with the last predictions – released on the morning of Aug. 4, a few hours before the storm – indicating an extreme impact, in the range of 3,000 to 6,000 damage locations for Eversource service territory and 400 to 800 for United Illuminating.

Even given those increasingly ominous indicators, the storm’s damage exceeded the Outage Prediction Model (OPM) as strong winds blew through the state and non-meteorological factors – including the weakened and insect-damaged trees – became an unexpected part of the equation.

An extreme drought affected the region in 2016, and unusually dry conditions persist in much of the state. That had degraded the ability of many trees’ root systems to withstand sustained wind levels of a major weather event, particularly in northern areas of Connecticut. Also, tree canopy defoliations by Gypsy moth infestations in 2016, 2017 and 2018 created vulnerabilities statewide.

The UConn Outage Prediction Model (OPM) is a well-established, state-of-the-art model which uses weather forecasts, land cover, vegetation, and infrastructure characteristics, and historical outage records, to predict the amount of damage in the electric distribution system. Development stages and applications of the model have been published in several top tier peer-reviewed
international journals, demonstrating its accuracy in predicting power outages for a host of weather events, including thunderstorms, hurricanes, nor’easters, and snow and ice storms.

Isaias’ unique characteristics affected the OPM modeling outcome in several ways, most particularly because the storm was disintegrating as it passed over the State of Connecticut, causing higher sustained winds and microbursts in localized circulations across a widespread
area. In these localized pockets, sustained winds reached the level experienced in both Hurricanes Sandy (October 2012) and Irene (late August 2011).

At the same time, data included in the model for similar magnitude storms such as Sandy and Irene reflected significant meteorological differences between those storms and Isaias: Sandy occurred later in the year when leaf area was lower, and Irene involved greater precipitation levels.

In mid-summer, Connecticut’s forests have the highest leaf area for high winds to impact, causing more tree and branch movement than when leaf area is lower. With drought conditions weakening the strength of root systems to an unprecedented extent, the combination of these factors caused an extreme impact.

Moreover, the National Weather Service confirmed that a tornado, characterized by a maximum wind speed of 95 to 105 mph, occurred in Westport, where power outages were extensive. Other small tornadoes and microbursts are suspected to have taken place in some locations, further indicating localized pockets of extreme winds.

“When we issued the first prediction on Aug. 1, the hurricane was still located in the Bahamas and there was a significant uncertainty on the track,” said Emmanouil Anagnostou, EEC’s Director, and a UConn professor in the Department of Civil and Environmental Engineering.

“But at the time of the fifth and final prediction, during the morning of Aug. 4, a few hours before the storm, we were certain that the storm would produce an extreme impact in Connecticut, although not as severe as what was actually predicted due to the novel characteristics of Storm Isaias,” added Diego Cerrai, EEC’s manager and an assistant professor in the Department of Civil and Environmental Engineering.

Going forward, the EEC plans to incorporate more data on vegetation science and drought conditions in its modeling, helping to better predict future warm-season extreme storm impacts.

EEC researchers also say another key observation from tropical storm Isaias and its aftermath is the recognition that vegetation management should be implemented more widely, perhaps including more attention to large trees that have been outside of historical trimming zones. The EEC’s faculty members who specialize in natural resources will be analyzing data from the Center’s Stormwise forest management sites and remote sensing data from NASA to investigate tree damages as it continues reviewing the incident.

This year’s hurricane season is expected to be active, and lessons learned from predictions of tropical storm Isaias will be part of the EEC’s data it uses as it continues monitoring for ways in which future weather events could impact the power grid.

The University of Connecticut Outage Prediction Model (OPM) Post-Storm Report for Tropical Storm Isaias can be viewed here:

https://www.eversource.uconn.edu/wp-content/uploads/2020/08/PSR_Hurricane_Isaias_final.pdf

Author: EEC’s Cory Merow Interviewed by NY Times and Scientific American

Dr. Cory Merow is an assistant research professor in UConn’s Ecology and Evolutionary Biology Department and researcher for Eversource Energy Center. He was interviewed by both the New York Times and Scientific American for insight into climate change and its ecological impact.

The New York Times article can be read here: https://www.nytimes.com/2020/04/15/climate/wildlife-population-collapse-climate-change.html
The Scientific American Article can be read here: https://www.scientificamerican.com/article/rising-temperatures-may-push-ecosystems-past-their-limits/

For more information on Dr. Cory Merow, his website is https://cmerow.github.io/
For more articles on the ecological impact of climate change, please see this site https://www.altmetric.com/details/79339301/news

Author: EEC Welcomes Dr. Ha Nguyen

Eversource Energy Center is pleased to announce the recent hire of Ha Thi Ngyuen, Ph.D., as an Assistant Research Professor to aid in our power engineering research. Dr. Nguyen will lead the Center’s newly acquired RTDS power grid test bed, and will support research projects related to integration of renewables in the power grid, cybersecurity and power grid resilience. Dr. Nguyen will also develop a training program for utility engineers on the use of the RTDS test bed, and you will contribute to the grid modernization certificate program offered by the Center.

Dr. Nguyen received her Ph.D. from the Center for Electric Power and Energy at the Technical University of Denmark (DTU) in 2018. She has worked with the Center Energy Research at University of California, San Diego and for Electric Power and Energy at DTU. Her research interests are power system modelling, operation and control, geographically distributed real-time co-simulation, hardware-in-the-loop simulation, frequency stability and control, and renewable energy integration.

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