MetrixIDR™ Retail Real-time Forecasting Solution MANY NEEDS – ONE SOLUTION Typical retail forecasting applications include: To meet the challenging business requirements of today’s energy markets, Itron’s MetrixIDR Retail forecasts hourly or sub-hourly profiles for a list of delivery points or for a portfolio of customers, where the portfolio can be changed on a daily basis. For mass markets, MetrixIDR uses profile models that represent customer segments, and these forecasts are then scaled to represent the customers in that segment. For the largest customers or delivery points, MetrixIDR supports the use of individual models and forecasts for each customer. »» Portfolio forecasting for load-profiled customers For profiled customers, MetrixIDR can be configured to model the profiling method employed in a particular market region. For individual customers or delivery points, the system provides a set of templates that are assigned based on diagnostic statistics and the visual properties of the load. This allows simple models to be used for calendar-driven loads, while more complex models are used for loads driven by weather, price, or other factors. »» Wholesale electric loads »» Individual customer forecasting for interval metered customers »» Short-term forecasting for energy scheduling »» Long-term or life-of-contract forecasting for planning »» Market price forecasting by zone or by node Typical delivery point forecasting applications include: »» Direct serve customer loads »» Substation loads »» Gas deliveries by city gate »» Short-term transmission system loads for system balancing »» Long-term transmission system loads f

THE SOLUTION FOR ALL YOUR NEEDS MetrixIDR Retail forecasts retail loads with profile models, individual customer models, or both. It can also be configured to forecast wholesale loads for individual delivery points or groups of delivery points. The system can be scheduled to update as needed during the day and is designed for the following high-level forecasting tasks. Imports load, generation, weather, calendar and exogenous forecast driver data and stores these data for data analysis, model estimation, forecast generation, and performance evaluation. Enables data analysis, model variable construction,...

These modeling techniques include: Ideal for projecting customer growth trends that support monthly sales and peak forecasting applications. For seasoned time series professionals who want to visualize how historical data patterns extend into the future. The workhorse of the energy forecasting professional. No other tool lets you build multi- variate models faster. Essential for short-term forecasting where modeling the nonlinear response between loads and weather matters the most. Allows the forecast operator to view, modify, and publish, in real-time, the load and generation forecasts generated...

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