Friday, November 3, 2023

Congratulations, Dr. Shukla!

Today (November 3rd, 2023), Shreyashi Shukla defended her doctoral dissertation on short-term peak timing forecasting.

Shreyashi Shukla's PhD defense

Shreyashi joined our MSEM program in Fall 2017. She completed her master thesis under my supervision in October 2018. After that, she continued working with me to pursue her PhD.

Since the first summer into her PhD program, Shreyashi started working half time at Duke Energy. She took a major role in helping millions of Duke Energy customers understand their electricity end uses. Her managers and colleagues all spoke highly of her work.

COVID hit us right in the middle of her PhD journey. She had to juggle several balls at the same time, the Duke Energy job, her dissertation research, and most importantly, her family. While many others were taking a break during the lockdown, she is making progress on her research.

Last year Shreyashi and I organized the BigDEAL Challenge 2022, which attracted 78 teams from 27 countries. She was heavily involved in the competition design. She also took most responsibilities of competition operations.

Her dissertation work is ahead of its time. The committee was very much impressed by the thoroughness and depth of the work. Within the next few years, her name will appear in some of the most influential papers in the load forecasting literature.

Congratulations, Dr. Shukla!

Monday, December 19, 2022

BigDEAL Challenge 2022 Final Leaderboard

BigDEAL Challenge 2022 attracted 78 teams formed by 121 contestants from 27 countries. 14 teams were advanced to the final match, an ex ante daily peak load forecasting competition. 

The final match includes 6 rounds of ex ante daily peak load forecast tasks. The data were released on a rolling basis. The forecasts were evaluated from three different perspectives: magnitude, timing, and shape, which made the three tracks of the final match. The contestants were asked to submit forecasts for all three tracks in each round. 

The following methodology was used to determine the winners:

  • The teams are ranked for each individual round for each track. 
  • The rank of a missing submission is imputed by the team's worst rank of the corresponding track. 
  • A team has to complete at least 5 rounds to be eligible for the final leaderboard. 
  • The grand champion is determined based on rankings of the highest ranked 5 rounds.

13 teams were eligible for the final leaderboard*:

* Gray entries are students from Dr. Hong's Energy Analytics class offered at UNC Charlotte. 

A few highlights:

  • Amperon is the only team that ranks top 2 in all three tracks (No. 1 in magnitude; No. 2 in timing and shape).
  • Team KIT-IAI is the only team that won two tracks (timing and shape). 
  • 4 teams (Amperon, KIT-IAI, Overfitters, and swissknife) outperform Shreyashi's Recency Benchmark in all three rounds.
  • Rajnish Deo is the best performing individual.
  • Belinda Trotta is the highest ranked individual. 

Details of each track are listed below:

We are working with the teams and journals to have their winning methodologies published. For those of you who are interested in what they did in the competition, stay tuned...

Congratulations to all participating teams and UNC Charlotte students!

Tao Hong and Shreyashi Shukla

Monday, November 14, 2022

BigDEAL Challenge 2022 Qualifying Match Results

The qualifying match of BigDEAL Challenge 2022 is ex post one-year ahead load forecasting. 121 contestants from 27 countries formed 78 teams to join the challenge. 

The following data were provided to the contestants:

  • hourly load data of a U.S. utility from 2002 to 2006, and 
  • hourly temperatures of four virtual weather stations from 2002 to 2007. 

The qualifying match includes three tracks: 

  • H (Hourly loads of one year). Contestants were asked to forecast the 8760 hourly loads of 2007. MAPE of the 8760 hourly loads was used to evaluate the forecasts. 
  • M (Magnitude of 365 daily peaks). Contestants were asked to forecast the 365 daily peak loads of 2007. MAPE of the 365 daily peaks was used to evaluate the forecasts. 
  • T (Timing of 365 daily peaks). Contestants were asked to forecast the timings of the 365 daily peak loads of 2007, represented by integers from 1 to 24. MAE of the 365 daily peak timings was used to evaluate the forecasts. 

43, 41, and 40  teams completed the track H, M, and T, respectively. Leaderboards of the three tracks are shown below. 

Teams beating Shreyashi's Recency Benchmark in any track are qualified for the final match. Congratulations to the following 14 teams (in alphabetical order)!

  • Amperon
  • BelindaTrotta
  • EnergyHACker
  • freshlobster
  • Overfitters
  • peaky-finders
  • RandomForecast
  • SheenJavan
  • swissknife
  • Team SGEM KIT
  • VinayakSharma
  • X-Mines
  • Yike Li
Stay tuned...

Tao Hong and Shreyashi Shukla

Thursday, October 6, 2022

Congratulations, Dr. Li!

Today (Oct 6, 2022) Yike Li defended his doctoral dissertation on short-term ex ante load forecasting. 

Yike joined our MSEM program in Fall 2018. He completed his master thesis under my supervision in Spring 2020. After that, he continued working with me to pursue his PhD.

The COVID-19 pandemic did not slow him down at all. Instead, the lockdown days may have speeded up his research. Towards the end of his PhD journey, I was frequently surprised by the amount of work he has done within a short timeframe between our meetings. 

From January 2021 to May 2022, Yike worked at Duke Energy as a Data Scientist intern, where he built predictive models to understand consumer electricity usage. After that, he spent a summer with Cruise. While Yike received many offers during the past few months, he decided to bring his talent back to Cruise after graduation. 

While the load forecasting literature is dominated by ex post forecasting studies, many practical issues with ex ante forecasting have never been thoroughly studied. Yike's dissertation tackled some of the most difficult problems in ex ante load forecasting. I'm glad to see that he is applying these skills in the transportation sector. 

Thanks to Yike, I can tell my department chair: "My student makes more than your Dean!"

Congratulations, Dr. Yike Li!

Tuesday, October 4, 2022

BigDEAL Challenge 2022

Dear colleagues,

This is the registration form for BigDEAL Challenge 2022. Please feel free to forward the link ( to anyone you think might be interested.

The theme of BigDEAL Challenge 2022 is peak load forecasting. The competition includes a qualifying match and a final match. 

Each team will include up to four team members. All team members should fill in the form.

The qualifying match is ex post one-year ahead forecasting. The match includes three tracks: 1) H (hourly loads of one year); 2) M (magnitude of 365 daily peaks); and 3) T (timing of 365 daily peaks). Winners of the qualifying match will be invited to the final match. Additional details and instructions will be released together with the qualifying match data on Oct 31, 2022. 

The final match is ex ante day ahead peak load forecasting. The data will be released on rolling basis. Forecasts from the finalists will be judged based on magnitude and timing of daily peaks. Additional details and instructions will be released together with the final match data on Nov 15, 2022. 

Every team qualifying the final match will be invited to submit a paper to IET Smart Grid describing the methodology used in the competition. Selected winning team(s) will receive waiver of Article Processing Charges.

Important Dates

  • Registration Open: Oct 4, 2022
  • Registration Close: Oct 29, 2022
  • Qualifying Match Data Release: Oct 31, 2022
  • Qualifying Match Submission Due: Nov 10, 2022
  • Qualifying Match Results Announcement: Nov 14, 2022
  • Final Match 1st Data Release: Nov 15, 2022
  • Final Match Submission Due: Dec 7, 2022
  • Final Match Results Announcement: Dec 12, 2022

Tao Hong, PhD

Duke Energy Distinguished Professor and NCEMC Faculty Fellow of Energy Analytics

Director of Big Data Energy Analytics Laboratory (BigDEAL)

Department of Systems Engineering and Engineering Management

University of North Carolina at Charlotte

hong "AT" 

Thursday, April 22, 2021

Jordan McCorey - MVP

Last Thursday (April 15th, 2021), Jordan McCorey defended his master thesis Forecasting Most Valuable Players of the National Basketball Association.

Jordan McCorey received his B.S. in Mechanical Engineering from NC A&T University in 2017. Right after graduation, he started his full time job at Boeing in North Charleston as a process engineer. He joined our Master of Science in Engineering Management as a part-time student in Fall 2018. 

Jordan McCorey's master thesis defense
From left to right: Dr. Tao Hong, Dr. Linquan Bai, Jordan McCorey, and Dr. Pu Wang

MVP, a.k.a. Most Valuable Player, is the highest individual award for the most performing player in the entire league. If I were asked to name the MVP among all the graduate students in our program during this pandemic year, Jordan McCorey would be the one.

I have always been interested in sports, basketball in particular. After ISF2019, I sent an email to our graduate students list with a few project topics. One topic was sports analytics - NBA forecasting. Jordan responded to my email with a passionate cover letter expressing his strong interest.

We quickly set up a phone call to discuss a plan to move forward. During the phone call, I was very pleasant to know that Jordan was a varsity basketball player in high school. His understanding of the game was definitely a big plus for this topic. On the other hand, I also got to know that he has limited experience in programming, statistics, and forecasting.

I explained the challenge to him. Apparently he didn't back off. Then I asked him to take my forecasting course, which is known as one of the most demanding courses on campus. The COVID-19 pandemic hit us right in the middle of Spring 2020 semester. Many students took the easy route by taking a passing grade. Jordan, however, worked extra hard to earn a solid A while working on his full-time job at Boeing. 

Due to the quarantine, I was never able to meet Jordan in person. Instead, we had many phone calls to discuss his plan of study, research progress, and of course, our shared passion about the game of basketball. 

A few weeks before his defense date, I got a call from Jordan telling me that he just had Achilles injury. That's the same injury that led to Kobe's retirement, and the same injury that took down Kevin Durant during Game 5 of 2019 final. I asked him if he wanted to postpone the defense. He said no.

Then it came the defense date. 

A fabulous presentation Jordan delivered. 

I was super impressed, so were the other two committee members. 

Jordan McCorey, MVP of the 2020-2021 academic year. 

Tuesday, December 22, 2020

Announcing Global Energy Forecasting Competition 2021: Solar and Net Load Forecasting

Dear colleagues and readers of this blog,

Last year at ISF2019 in Thessaloniki, Greece, I mentioned the possibilities of running the next Global Energy Forecasting Competition in the SWEET membership meeting. Then the COVID-19 pandemic put everything on hold. 

Today, I'm pleased to announce GEFCom2021: Solar and Net Load Forecasting. 

GEFCom2021 will feature two tracks, solar irradiance forecasting and net load forecasting. Dr. Dazhi Yang will chair the solar irradiance forecasting track, while I'm taking care of the net load forecasting track.

This competition will inherit the bi-level setup of GEFCom2017. We will use a qualifying match math to bring together contestants from various domains, and to help people get familiar with solar and load forecasting problems. Then a final match will determine the winners. 

Additional details of GEFCom2021 will be released in Spring 2021. Please join the email list via this REGISTRATION FORM to get timely updates about GEFCom2021.

Hope you all stay safe and enjoy the holiday season!


Tuesday, June 23, 2020

Consulting, Research and Teaching in Energy Forecasting

In one week, Jun 30, 2020 11:00 AM Eastern Time, to be exact, I am going to give a talk at the IIF Early Career Researchers Network (ECR) virtual meeting. The registration link is HERE. You will need to have ZOOM on your PC or mobile device to join the meeting. 

Consulting, research and teaching in energy forecasting

Dr. Tao Hong will discuss the transition from a graduate student, to an industry professional, and then to a university professor. He will discuss how he balances the activities to strengthen his research program while helping students, industry organizations, and local communities.

About Dr. Tao Hong

Dr. Tao Hong is an Associate Professor of Systems Engineering and Engineering Management Department, Director of BigDEAL (Big Data Energy Analytics Laboratory), and NCEMC Faculty Fellow of Energy Analytics at University of North Carolina at Charlotte. In 2011, Dr. Hong started IEEE Working Group on Energy Forecasting as the Founding Chair and chaired the group until 2019. He is a Director at Large of International Institute of Forecasters, Founding Chair of IIF Section on Water, Energy and EnvironmenT (SWEET), General Chair of Global Energy Forecasting Competition, and author of this blog Energy Forecasting. Dr. Hong has been serving as department editor, editor and associate editor of several top journals, such as IEEE Transactions on Engineering Management, IEEE Transactions on Smart Grid, International Journal of Forecasting, and Solar Energy. Dr. Hong has provided training and consulting services to over 200 organizations worldwide in the area of energy forecasting and analytics.

Beyond his 24 x 7 working hours, Dr Hong is a volunteer coach of the Math Olympiad team of my neighborhood school. He started the Charlotte Math Meetup during the COVID-19 quarantine to help local kids and their friends with math. He enjoys basketball and jump rope. He was a silver medalist at the 2019 USA Jump Rope National Competition.

Wednesday, April 22, 2020

Energy Forecasting Jobs During COVID-19

This blog has been viewed hundreds of thousands of times by tens of thousands of energy forecasters worldwide have been visiting this blog. Several years ago, I used to post jobs on weekly basis. Then I stopped doing that to avoid primary contents being buried by job posts. 

I changed my mind because of COVID-19.

Many companies have hiring freeze, while many are still searching for people to fill in the vacancies. 

Many students and job seekers are desperate and panic in the job market. 

As a forecaster, I have zero interest forecasting when this chaos would end. As an energy forecaster, maybe I can help other energy forecasters and energy companies during COVID-19.

This is what I'm going to do for the next few months...

To hiring companies/managers:
  • Send me an email with the link to your job description, as well as job location, restrictions about visa status / green card / citizenship, and other important details you think applicants should know. 
  • Leave your contact information if you want. 
  • If you haven't followed me on LinkedIn, do that now. 
I'll post the links on the JOBS page of this blog. Sometimes, I will also select some jobs to broadcast through my LinkedIn profiles, which are followed by thousands of energy forecasters. 

To job seekers:
  • Check this blog frequently. 
  • Apply to the jobs you are qualified for and interested in. 
  • Leave your name under my LinkedIn post.
  • If you haven't followed me on LinkedIn, do that now. 
If you think you are a superstar in the job market, you can send me more details about your experience. I may broadcast your profile through my LinkedIn profile as well. 

Hope we all work together to fight through this unprecedented period!

Tuesday, April 7, 2020

Deeksha Dharmapal - Well-rounded

Today (4/7/2020), Deeksha Dharmapal defended her master thesis on Gross Domestic Product for short-term load forecasting.

Deeksha received her B.S. in Civil Engineering from Bangalore Institute of Technology, India, in 2012. Prior to joining UNC Charlotte in Fall 2018, she had several years of industry experience in India, with Amazon and EMC2 (now DellEMC). During her graduate study at our program, she also completed a summer internship at Bosch Rexroth, Charlotte.

During the past few years, I gave a departmental seminar to new graduate students every year. Deeksha is definitely the one that left the best impression on me. Most students at the seminar stayed quiet, while Deeksha was one of the few asking questions. Her questions sounded genuine and intelligent. Nevertheless, I didn't think she would eventually join my group, because she appeared to have a bright future on the managerial track.

Among the students in our program, the self-motivated ones start looking for their faculty mentor rather early. Deeksha took an unique approach. She showed up at one of my MS student, Shreyashi Shukla's thesis defense. Later she signed up and completed my forecasting course, which was a surprise to me.

When she told me that she wanted to join my group, I gave her the same task, passing two SAS programmer certification exams. She completed the base one, but failed the advanced one in her first attempt. The outcome didn't surprise me, because I knew her programming background was weak at that time. Most students at this point would just give up and look for other professors. She didn't. Finally she got the SAS Advanced Programmer Certification. Since she didn't pass it within the time limit I assigned, I gave her an extra task, which she completed in time. I brought her to BigDEAL as my MS thesis student in the summer of 2019.

The thesis topic I gave her was non-trivial. Economic indicators are typically used for long term load forecasting but not short term load forecasting. I asked her to investigate what are the situations that we should consider economy, GDP to be specific, in short term load forecasting. This research involves a lot of programming skills as well as knowledge in statistics.  She picked up those things along the way, and had the thesis beautifully done.

As a forecaster, I love to investigate the things that I failed to predict. I was wondering how a little girl Deeksha surprised me multiple times by pushing herself out of her comfort zone and fighting such a tough uphill battle. Through some casual conversations, I learned that she was a student athlete. She ran track for the most part of her student life - short distance sprints and relay. She was on the basketball and volleyball teams. Post marriage, she has been playing competitive badminton.  I guess the sports experience must have built her a strong heart!

Congratulations, Deeksha!