Wednesday, June 5, 2019

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
  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
  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
  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

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