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!

Tao

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.

IEEE Working Group on Energy Forecasting in Good Hands

At IEEE Power & Energy Society General Meeting 2010 (GM'10), I proposed a future panel session on Practical Aspects of Electric Load Forecasting. The session was approved by the Power Systems Planning and Implementation (PSPI) Committee.

The following year at GM'11, we hosted the session with 6 speakers and a fully packed room of audience. The discussion was quite engaging. We shared ideas, experience, concerns and visions of the future for this field. At the same conference, Shu Fan and I proposed to establish the IEEE Working Group on Energy Forecasting to tackle a long list of challenges in the field. The proposal was approved at the PSPI committee meeting. I became the Chair, and Shu became the Vice Chair. 

After GM'11, we started working with a few other key players on several initiatives, such as GEFCom2012, and a TSG special session on forecasting. We brought in Pierre Pinson to both initiatives. Both turned out to be unbelievably successful. GEFCom2012 was a game-changing event that produced many valuable assets for the energy forecasting community and started the . Our TSG special section collected many high quality and highly cited papers.

At GM'12, I met Hamidreza Zareipour for the first time. Within seconds, we both sensed each other's strong passion in forecasting. Then Hamid became the Secretary of our working group. 

After GM'12, Shu, Hamid, Pierre, and I started another initiative: a tutorial on energy forecasting. We taught the tutorial for the next four consecutive years, from 2013 to 2016. 

During the last 9 years, we have completed virtually every task we promised to do back in 2011, and much more: the series of three Global Energy Forecasting Competitions, two special sections for IEEE Transactions on Smart Grid and one special issue for Power & Energy Magazine, a 25-page literature review, a full-day tutorial, and more than a dozen panel sessions at PES General Meetings.

Since GEFCom2017, I have been thinking about replicating the success beyond the power sector. Fortunately, the International Institute of Forecasters offered a great platform to reach out to the fields of gas, water, environment, and climate science. Long story short, I founded SWEET, IIF Section on Water, Energy, and EnvironmenT. We just had our first meeting at the International Symposium on Forecasting 2019, with 43 talks in 13 sessions. Our next meeting will be at ISF2020 in Rio, Brazil, July 5-8, 2020.

Running SWEET requires a lot of thoughts and efforts. To focus on this new challenge, I decided to take off my hat as the Chair of the Energy Forecasting Working Group. I believed the group also needed a new leader for its next chapter. I found no better successor than Hamid to take over the Chair position. Hamid is a full professor of electrical and computer engineering at the University of Calgary. He started as the Secretary of the group in 2012. After Shu Fan left academia to pursue his career in trading, he stepped up as the Vice Chair. Hamid has been a crucial contributor to the success of the group since its infancy. I'm sure that he will bring the group up to the next level.

Hamid and I searched for a new secretary and found a rising star Yi Wang, a postdoc researcher at ETH Zurich. Yi received his PhD from Tsinghua University. He has published more than 30 journal papers, of which most are on load forecasting and smart meter data analytics. In the past, he has helped us review many energy forecasting manuscripts for top scholarly journals. This year at GM'19, Yi is chairing a panel session on probabilistic energy forecasting. Yi has already brought up several innovative ideas to grow the group. As the Past Chair, I'll support Hamid and Yi to ensure a smooth transition.

IEEE Working Group on Energy Forecasting is in good hands!

Call for Proposals: IIF-SAS Grant to Promote Research on Forecasting

The International Institute of Forecasters is calling for proposals on how to improve forecasting methods and business forecasting practice. This is the 16th year of the financial support from SAS on this IIF-SAS award. In addition to the $10,000 funding from SAS, the IIF is adding another $10,000 to the award pool this year, so that two $10,000 grants are going to be awarded to the best proposals in methodology and practice/management categories.

The applications are due on September 30, 2019. The application must include: 

• Description of the project (at most 4 pages) 
• C.V./resume (brief, 4 page max) 
• Budget and work-plan for the project (brief, 1 page max) 

Criteria for the award of the grant will include likely impact on forecasting methods and business applications. 

Details about the award can be found from the IIF website. For the frequent readers of this blog and SWEET members, I'm listing the energy related projects that were awarded in the last decade:

• Robust kernel-free nonlinear support vector regression models for load forecasting. Jian Luo, Dongbei University of Finance & Economics, China. (2018-2019 grant, methodology category)
• Hierarchy-based disaggregate forecasting using deep machine learning in power system time series. Cong Feng and Jie Zhang, The University of Texas at Dallas, USA. (2017-2018 grant, business applications category)
• Convolutional neural networks for spatio-temporal wind speed forecasting. Fernando Cyrino and Bruno Q. Bastos, Pontifical Catholic University of Rio de Janeiro, Brazil. (2017-2018 grant, methodology category)
• Short-term load forecasting using rule-based seasonal exponential smoothing incorporating special day effects. Siddharth Arora and James Taylor, University of Oxford, UK. (2010-2011 grant, business applications category)

Best luck!

SWEET Sessions @ ISF2019

Update 6/21/2019: the SWEET presentations can be downloaded via this Dropbox link. The next ISF will be held at Rio, Brazil, July 5-8, 2020. Look forward to seeing you there!

At the board meeting during the 38th International Symposium on Forecasting (ISF2018), I proposed the idea of developing interest groups or communities within the International Institute of Forecasters (IIF) to better offer a collaborative environment and networking opportunities to forecasting researchers and practitioners. Right after ISF2018, I worked with George Athanasopoulos, Stephan Kolassa and Pam Straud to develop a formal proposal to the IIF Board of Directors. The board approved the launch of two communities at the end of last year. One of them is the Section on Water, Energy and Environment (SWEET).

ISF2019 will be held at Thessaloniki, Greece, June 16 - 19. The conference program committee has dedicated a full 3-day track to SWEET. In total, 43 speakers will cover a wide range of topics in 13 sessions, including gas and electricity demand forecasting, wind and solar forecasting, water demand and hydro generation forecasting, water and air quality forecasting, and energy price forecasting. In addition, we will hold the first SWEET member meeting on Monday June 17, right before the IIF member meeting.

If you are interested in ISF2019, please check out the program schedule. Below is the list of SWEET talks:

Electricity Demand 1: Data Resolution

1. Forecasting individual electric utility customer hourly loads from AMI data
2. Development of an end-use load forecasting model for Peninsular Malaysia
3. Daily peak load forecasting with mixed-frequency input data

Electricity Demand 2: Short Term Load Forecasting

1. Evaluation of multi-horizon strategies for electricity load forecasting
2. Zero initialization of modified gated recurrent encoder-decoder network for short term load forecasting
3. Impact of meteorological variables in short-term electric load forecasting

Electricity Demand 3: Load & Price

1. Determining the demand elasticity in a wholesale electricity market
2. Horse and Cart: a scalable electricity load and price forecast model
3. Temporal hierarchies with autocorrelation for load forecasting

Electricity Demand 4: Statistics vs. Machine Learning

1. Forecasting time series with multiple seasonal patterns using a long short-term memory neural network methodology
2. Statistical and machine learning methods combination for improved energy consumption forecasting performance
3. Probabilistic forecasting of electricity demand using Markov chain and statistical distribution

Electricity Price 1: German Market

1. Econometric modelling and forecasting of intraday electricity prices
2. On the importance of cross-border market integration under XBID: evidence from the German intraday market
3. A generative model for multivariate probabilistic scenario forecasting

Electricity Price 2: Probabilistic Forecasting

1. Averaging probabilistic forecasts of day-ahead electricity prices across calibration windows
2. Regularization for quantile regression averaging. A new approach to constructing probabilistic forecasts
3. Revisiting the jackknife method for construction of prediction intervals – application to electricity market

Electricity Price 3

1. Forecasting Italian spot electricity prices using random forests and intra-daily market information
2. Forecasting Northern Italian electricity prices
3. Application of a SVM-based model for day-ahead electricity price prediction for the single electricity market in Ireland

Electricity Price 4

1. Day-ahead vs. intraday - forecasting the price spread to maximize economic benefits
2. Enhancing wind and solar generation forecasts to yield better short-term electricity price predictions
3. Prediction intervals in high-dimensional regression

Energy

1. Forecasting algorithm assignment to distribution grid service points in the context of demand response
2. Modelling uncertainty: probabilistic load forecasting using weather ensemble predictions
3. Understanding the impacts of distributed PV resources on short-term load forecasting – a comparative study on solar data availability
4. Access forecasting for safety-critical crew transfers in offshore environments

Environment

1. A feature-based framework for detecting technical outliers in water-quality data from in situ sensors
2. Probabilistic forecasting models for NO2 concentrations
3. Probabilistic forecasting of an air quality index

Oil & Gas

1. Forecasting oil and natural gas prices with futures and threshold models
2. Ensemble-based approaches and regularization techniques to enhance natural gas consumption forecasts
3. A multi-granularity heterogeneous combination approach to crude oil price
4. Predicting Natural Gas Pipeline Alarms

Water

1. Forecasting power generation for small hydropower plants using inflow data from neighboring basins
2. Probabilistic short-term water demand forecasting
3. When is water consumption extreme?
4. Forecasting water usage demand in Sydney

Wind & Solar

1. A comparison of wind speed probabilistic forecast via quantile regression models
2. Online distributed learning in wind power forecasting
3. Probabilistic solar power forecasting: long short-term memory network vs. simpler approaches
4. A non-parametric approach to wind power forecast

If you can't join the conference but want to stay informed about SWEET activities, you can sign up for the SWEET News Letter.