It's a couple of weeks since the IEEE Power & Energy Society's General Meeting, and I thought it was worth highlighting some of the society's forecasting activities. IEEE PES co-sponsors a number of IEEE journals that frequently publish energy forecasting research, such as Trans. Power Systems, Smart Grid and Sustainable Energy, they also sponsor the the Global Energy Forecasting Competition along with the International Institute of Forecasters.
At this year's general meeting there was a large range of forecasting activities lead by experts in various aspects of energy forecasting beginning with a whole-day tutorial on the Sunday before the main conference. Introductory lectures were given by Dr Tao Hong, Dr Shu Fan and Prof Hamidreza Zareipour on load, price, wind and solar power forecasting to a diverse audience of both forecasters and forecast users for both industry and academia. During the conference proper almost every session seemed to include a few posters on one aspect of energy forecasting or another! While the quality of papers varied the number of contributions from, or sponsored by, industry is evidence of the important role forecasting plays in modern power systems. All papers should be available on IEEE Xplore shortly.
The highlight of the week for me was the day of presentations by winners of the 2014 Global Energy Forecasting Competition. Many of the top performing entrants in all four competition tracks were present to discuss their work and receive their prizes. The winning entries will be published in a forthcoming special issue of the International Journal of Forecasting. Something that I had under-appreciated before the meeting was the strength of the machine learning community in the energy forecasting space: many of the top performing entrants were not energy experts or pure statisticians but computer scientists.
At this year's general meeting there was a large range of forecasting activities lead by experts in various aspects of energy forecasting beginning with a whole-day tutorial on the Sunday before the main conference. Introductory lectures were given by Dr Tao Hong, Dr Shu Fan and Prof Hamidreza Zareipour on load, price, wind and solar power forecasting to a diverse audience of both forecasters and forecast users for both industry and academia. During the conference proper almost every session seemed to include a few posters on one aspect of energy forecasting or another! While the quality of papers varied the number of contributions from, or sponsored by, industry is evidence of the important role forecasting plays in modern power systems. All papers should be available on IEEE Xplore shortly.
The highlight of the week for me was the day of presentations by winners of the 2014 Global Energy Forecasting Competition. Many of the top performing entrants in all four competition tracks were present to discuss their work and receive their prizes. The winning entries will be published in a forthcoming special issue of the International Journal of Forecasting. Something that I had under-appreciated before the meeting was the strength of the machine learning community in the energy forecasting space: many of the top performing entrants were not energy experts or pure statisticians but computer scientists.
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