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MetrixIDR System Operations
Automated Short-Term Load Forecasting
Product Detail
Product image 1 of 1
MetrixIDR™ is
the most flexible and accurate short-term load forecasting system on
the market and is ideal for forecasting total system loads,
transmission zone loads, daily gas send-out and energy prices.
MetrixIDR System Operations utilizes advanced neural network and
regression model specifications, designed to capture linear and
non-linear interactions between load, weather, and calendar
information. A proprietary Dynamic Learning Algorithm ensures the
forecasts are continuously tuned to the most recent loads.
To learn more about our forecasting technologies, we encourage you to visit the ITRON FORECASTING BLOG
Contact Sales
To learn more about our forecasting technologies, we encourage you to visit the ITRON FORECASTING BLOG
Operating system and user
interface provided in English only.
Resources
Brochure
- Energy Forecasting Services
- Forecast as a Service Brochure
- MetrixIDR Retail
- MetrixIDR System Operations
- MetrixND Brochure
Case Study
White Paper
- A Unified Framework for Near-Term and Short-Term System Load Forecasting
- Closing the Books Forecasting the Unbilled Energy and Sarbanes-Oxley Compliance
- Defining Normal Weather for Energy and Peak Normalization
- Forecasting Solar Generation
- Impact of AMI on Load Research and Forecasting
- Improving Short-Term Load Forecasts by Incorporating Solar PV Generation
- Incorporating DSM into the Load Forecast
- Itron Annual Energy Survey 2020
- Itron Annual Energy Survey 2021
- Itron Annual Energy Survey 2021
- Itron Annual Energy Survey 2022
- Itron Annual Energy Survey 2023
- Itron Annual Energy Survey 2023
- Modeling and Accounting Methods for Estimating Unbilled Energy
- Price Elasticities in Energy Modeling and Forecasting
- Short Term Energy Forecasting with Neural Networks
- Statistical Approaches to Electricity Price Forecasting
- Toward an Optimal Combined Load Forecast for System Operations
- Using Neural Networks for Day-Ahead Forecasting
- Why Not Pi? A Primer on Neural Networks for Forecasting
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