After the two-week registration period, we officially kicked off the BigDEAL Forecasting Competition 2018 with 81 teams formed by 142 data scientists across 26 countries. This morning, I sent out the data and instructions to the contestants. If you are a registered contestant but have not yet receive the data and instructions, please contact me directly.
Q: I'm new to load forecasting. Where shall I get started?
A: This qualifying problem is very similar to the load forecasting track of GEFCom2012. Reading the papers from those winning teams should help.
Q: We are going to use multiple methods. Can we submit multiple forecasts?
A: No. You should only submit one forecast for grading. If you have multiple forecasts, you may consider combining them. This paper may give you some idea about forecast combination.
Q: The local economy information, which was not given in the data, may have some significant effects to the forecasting period. Would you provide the local economy information? (For details, see Geert Scholma's comment under the original BFCom2018 announcement.)
A: No. We will add an error measure that calculate MAPE on bias-adjusted load forecast. We will adjust the hourly forecast based on the coincidence monthly energy, so that your forecasted energy of each month equal to the actual monthly energy. Beating the last-ranked in-class student on either measure can secure the ticket to the final match.
Q: I did not pass the qualifying match bar, but I'm very interested in learning from the winners about their methodologies. Would you summarize their methods?
A: I will organize a series of webinars for the finalists to talk about their methods, though the webinars are not recorded. I will also invite the finalists to summarize their winning methods to post on the blog.
Q: I'm a PhD student just starting my research in energy forecasting. I've learned a lot from this competition. Will you organize this again?
A: Yes. This is not the first BigDEAL Forecasting Competition. It will not be the last either. You can follow my twitter, subscribe to this blog, and/or connect to me on LinkedIn to get updates about events like this.
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| BFCom2018 attracted 142 data scientists from 26 countries. |
This blog post lists the frequently asked questions for BEFCom2018. I'll be updating this post as the questions come along, so please stay tuned.
Q: Which error measure are you going to use to rank the teams?
A: MAPE, mean absolute percentage error.
Q: Why are there 23 hours in Mar 9, 2008 and 25 hours in Nov 2, 2008?
A: They were observed daylight savings time. Similar observations were in the historical years. See THIS BLOG POST for more information. In the original submission template, the hours in Nov 2, 2008 were from 1 to 25. A new submission template was sent to the contestant on Oct 24, 2018, which had the 2nd hour of Nov 2, 2008 repeated twice, to match the temperature of 2008.
Q: There are 28 weather stations, but only one load series. Which weather stations shall I use?
Q: Why are there 23 hours in Mar 9, 2008 and 25 hours in Nov 2, 2008?
A: They were observed daylight savings time. Similar observations were in the historical years. See THIS BLOG POST for more information. In the original submission template, the hours in Nov 2, 2008 were from 1 to 25. A new submission template was sent to the contestant on Oct 24, 2018, which had the 2nd hour of Nov 2, 2008 repeated twice, to match the temperature of 2008.
Q: There are 28 weather stations, but only one load series. Which weather stations shall I use?
A: That's part of the challenge. Read this weather station selection paper for more information.
Q: I'm new to load forecasting. Where shall I get started?
A: This qualifying problem is very similar to the load forecasting track of GEFCom2012. Reading the papers from those winning teams should help.
Q: We are going to use multiple methods. Can we submit multiple forecasts?
A: No. You should only submit one forecast for grading. If you have multiple forecasts, you may consider combining them. This paper may give you some idea about forecast combination.
Q: The local economy information, which was not given in the data, may have some significant effects to the forecasting period. Would you provide the local economy information? (For details, see Geert Scholma's comment under the original BFCom2018 announcement.)
A: No. We will add an error measure that calculate MAPE on bias-adjusted load forecast. We will adjust the hourly forecast based on the coincidence monthly energy, so that your forecasted energy of each month equal to the actual monthly energy. Beating the last-ranked in-class student on either measure can secure the ticket to the final match.
Q: I did not pass the qualifying match bar, but I'm very interested in learning from the winners about their methodologies. Would you summarize their methods?
A: I will organize a series of webinars for the finalists to talk about their methods, though the webinars are not recorded. I will also invite the finalists to summarize their winning methods to post on the blog.
Q: I'm a PhD student just starting my research in energy forecasting. I've learned a lot from this competition. Will you organize this again?
A: Yes. This is not the first BigDEAL Forecasting Competition. It will not be the last either. You can follow my twitter, subscribe to this blog, and/or connect to me on LinkedIn to get updates about events like this.
(To be continued...)
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