Electricity + Control February 2017

CONTROL SYSTEMS + AUTOMATION

ECMWF – European Centre for Medium-Range Weather Forecasts FoD – Forecast on Demand GFS – Global Forecast System ISO – Independent System Operators NAM – North American Mesoscale RPM – Rapid Precision Mesoscale THI – Temperature-Humidity Index WCI – Wind Chill Index

Abbreviations/Acronyms

The two components of modern-day weather forecasting are:

Intelligently using all available computer weather model forecasts to provide the most accurate automated forecast Having an expert and experienced local human forecaster who knows the ‘local flavour’ of the weather and can add further value (and better accuracy) than even the best ‘machine’ forecast For South Africa specifically, the company employs the best weather forecasting models, including the European Centre for Medium-Range Weather Forecasting (ECMWF) model, the Global Forecasting System (GFS) model and its proprietary high-resolution Deep Thunder model. Given its high spatial resolution and advanced physics, the Deep Thunder model is able to handle the localised weather features that are unique to South African weather, from the daily ocean breezes in coastal regions to the unique circulations associated with the mountainous regions. Once the best forecasts are extracted from the stream of the various weather forecasting models, an experienced human forecaster is needed to improve the forecasts further. While weather forecasting models are quite good, there are still flaws that the expert forecaster can exploit, especially in extreme weather.

Cognitive computing helps you outthink the weather To convert weather data into useful load forecasts, data scientists developed a comprehensive set of self-learning neural networks for predicting load in different ISO zones. For each zone, more than 100 neural networks were trained using actual weather conditions. Individual neural networks were trained to predict load for dif- ferent types of days: regular weekdays, Saturdays, Sundays, and holidays. The load profile for each holiday is treated differently based on a proprietary algorithmdeveloped by examining historical load profiles on those days. This specialisation was further refined by training multiple neural networks for bal-day, next-day and medium-range forecasting for each day type. Variable selection was used to optimise the appropriate set of weather parameters needed for each zone, type of day, and forecast period. The bal-day neural networks blend the most recent values of observed load into the raw forecast values using a forward-correction scheme similar to that used in FoD. Make better decisions, with greater confidence For utility companies, we see load forecasting as a critical key to success. It is one that requires and deserves a sophisticated solution. WSI Trader Load Forecast was designed so that energy decision- makers can: • Gain a competitive edge in both near-term and long-range time periods by leveraging accurate, precise, and resolute data that the company has available • Distinguish between types of holidays and how they can impact different sub-regions and zones by leveraging our proprietary holiday-forecasting algorithms • Get accurate bal-day and next-day forecasts based on our pro- prietary forward-correction algorithms • Leverage hyper-local forecasting designed to predict local weather likely to affect load demand in the very near term • Quickly visualise forecasts with the graphical, intuitiveWSI Trader user interface

The Weather Company

Conclusion In order to maintain consistent and reliable energy delivery − across peak periods as well as everyday usage − decision-makers need to leverage technically advanced load forecasting. Accurate weather forecasting, combined with state-of-the-art data science, can poten- tially help improve both short- and long-term forecasting.

• Weather can and does have a huge effect on performance in utilities and industry. • Predicting utility demand and consumption is a complex and uncertain process. • Accurate load forecasting depends on accurate weather forecasting.

take note

Rob Berglund leads the sales team for Energy & Utility (E&U), Agriculture, and Petro-Chemical for the Energy group at The Weather Company. Since the beginning of his career at the Weather Company, starting in 2003, he has developed business in regions around the world, with an industry specific focus of Energy & Water Utilities, Energy Commodities Trading,

Agribusiness, and Oil & Gas. Enquiries: Email energysales@wsi.com

February ‘17 Electricity+Control

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