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AI Load & Demand Forecasting Solutions & Services

  • Consumers, wholesale, retail and utility load.
  • Intraday, 7 DA & long-term 5-60 mins forecast resolution.
  • Forecast frequency every 5 -10 mins, 24/7.
  • Upper and lower uncertainty forecast bands.
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QR AI Forecaster offers robust and flexible intraday, 7 days ahead, and long-term load forecasting services tailored to meet the requirements of utilities, munis, electric co-ops, energy retail providers and marketers, and grid operators
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Challenges

Clients’ profile. Load serving entities such as utilities, electric co-ops and munis, energy retail providers and marketers, grid and transmission line operators and generators, operating in real-time intraday and day-ahead 5-60 mins resolution markets.

Target.
1. Accurate and flexible load forecasts, aggregating or drilling load by any desired criteria, i.e., geographic regions, cities, distribution nodes, or by consumer type (residential, commercial, industrial).
2. Net load forecast, i.e., demand net of behind the meter solar generation, needed to optimize the integration of microgrid fleets with utilities’ macro grid.
3. These AI demand forecast models can be short-term intraday, up to 7 days ahead, and medium to long term. In the latter case the model should include what-if-scenarios on exogenous factors, e.g., a shift in temperature up or down by 10 degrees, or some global economic or localized indicators such as consumer load growth by 9%, etc.

Implement real-time 24/7 automated, stand-alone and accurate load forecast solutions, as a web cloud solution that can be easily integrated with in-house trading systems, ISOs, weather data services, and internal data sources, e.g., meters, SCADA, etc.

QR Load Forecasting Solutions

DataLack Hub

Meter Data Hub

Consumer load data management

Retail Energy Provider Load

Retail electricity consumer load

Utility Net Load

Utility & LSE Load

Utilities & LSE total & net load

Sourcing Optimization

Electricity System Demand

World ISO, RTO and power market system demand

Sample Load Forecasting Dashboard Displaying Actual & Forecast Load
Sample Load Forecasting Dashboard Displaying Different Profiles: Actual & Forecast Load
Drag & Drop Load Forecasting AI Feature Modelling Dashboard
Drag & Drop Load Forecasting AI Feature Modelling Dashboard
Load Forecast Dashboard Displaying Actual and Forecast: With Accuracy Measures such as MAPE
Load Forecast Dashboard Displaying Actual And Forecast: With Accuracy Measures Such As MAPE
Probabilistic Forecast at Multiple Percentiles: Net Load of Behind-the-meter Solar Generation
Probabilistic Forecast at Multiple Percentiles: Load Net of Behind-the-meter Solar Generation

QR AI Load & Demand Forecaster General Features

  • QR AI Load Forecaster is fully automated and fetches your load, meter, SCADA, ISO demand data, as well as weather data. Forecast results are published via API or in web dashboards with data visualization and manual download options.
  • You can always start with a POC Trial.
  • QR AI Load Forecaster offers a range of intraday, 15 days-ahead and long tern load forecast solutions using advanced custom-configured Deep Learning and Machine Learning AI models.
  • Long term forecasts include what-if-scenarios on exogenous factors, e.g., a shift in temperature up or down by 10 degrees, some global economic indicators, or localized indicators such as consumer load growth by 9%, etc.
  • Forecast temporal resolution is 5–60 minutes, depending on your data and requirements. QR AI Load Forecaster can scale data while forecasting from lower to higher resolution, e.g., from actual 5-min load data, it can forecast 5-min, 15-min, 30-min or 60-min resolution forecasts.
  • Forecasts computation frequency is configurable, e.g., 5–10 minutes, 24/7 for real-time intraday forecasts, and 9-12 am for day-ahead forecast.
  • These load forecast solutions can be licensed as a cloud service. No hardware or software installations are needed, just a browser.

Meter Data Hub

A key challenge for energy retail providers operating through multiple utility jurisdictions is to integrate and use their data through various third-party data feeds, each using possibly different data formats. On the other hand, utilities and load serving entities have large amounts of meter data in multiple and often legacy systems and Excel files.

  • QR Meter Data Hub is a robust cloud data management platform that offers great flexibility to connect to various utility and third-party data feeds and collect, format and organize consumer consumption load into a standard uniform data format within an optimized data platform, suitable for reporting, warehousing, data export, analytics and AI load forecasting.
  • Connectivity can be established via Restful API, sql, direct file (csv, Excel, XML, Json) fetching.
  • We are compatible with Electronic Data Interchange (EDI) billing data feeds, individual utilities and third-party automated Utility Data Platform or Metering Services.
  • We can connect to utilities’ systems or data feeds to collect granular load data and SCADA stream if available.
Meter-Data-Hub-Forecasting-Service
Retail-Energy-Provider-Load-Forecasting-Service

Retail Energy Provider Load

QR AI Load Forecast service for Energy Retail Providers is designed to overcome the specific challenges of this industry.

  • Energy Retail Providers operate through multiple utility jurisdictions. A first challenge is to integrate their data through different data feeds and file formats. QR Meter Data Hub is used to integrate and manage various Electronic Data Interchange (EDI) billing data feeds, individual utility and third-party automated Utility Data Platform or Metering Services.
  • Another challenge is that cumulative electricity meter consumption is read once a month or less frequently. QR AI Load Forecast models can use approved load profiles to estimate 5-60 min load consumption for forecasting. On the other hand, our AI models can also use advanced or smart grid meter data at 5-60 minute granularity.
  • Forecasts can be probabilistic with an average, high, and low forecasts at any desired percentile, e.g., 5 and 95, 10 and 90, 15 and 85, etc.
    Forecast temporal granularity is 1 to 60 min. Forecast frequency is every 10 min for intraday forecasts and 10 am local time for 7 DA forecasts.
  • Easy and flexible creation of load forecast models for specific aggregation rule, e.g., geolocation (regions, cities), consumer types such as single or multifamily w/air cons or space heater, offices, malls, businesses, small or medium size, commercial, or industrial.

Utility & LSE Load

QR AI Load Forecast service for load service entities (LSE), utilities, electric cooperatives and munis, offers a range of forecast services:

  • Load forecast for individual load nodes, substations, or consumers’ meter.
  • Load forecast per arbitrary aggregations rules such as geolocation (regions, cities), or per consumer types such as single or multifamily w/air cons or space heater, offices, malls, businesses, small or medium, commercial or industrial.
  • Net load forecasting, that is, load net of behind-the-meter solar generation, scattered across fleets of individual PV stations.
  • Forecasts can be probabilistic with an average, high, and low forecasts at any desired percentile, e.g., 5 and 95, 10 and 90, 15 and 85, etc.
  • Forecast temporal granularity is 1 to 60 min. Forecast frequency is every 10 min for intraday forecasts and 10 am local time for 7 DA forecasts.

QR Meter Data Hub is used to connect to your utility and third-party data feeds and collect the fullest range of data used in load forecasting:

  • Granular load data and SCADA stream if available.
  • Aggregate or granular net load.
  • Multiple weather and irradiance data, DNI, DHI and GHI.
Utility-&-LSE-Load-Forecasting-Service

Electricity Market System Demand

  • Demand forecasting service for world electricity system operators and markets, also known as Independent System Operators (ISOs), Regional Transmission Organizations (RTOs), Transmission System Operators (TSO).
    We compute demand forecasts per regional organization of demand or transmission zones, or Trading Hubs.
    Forecast temporal granularity is 1 to 60 min. Forecast frequency is every 10 min for intraday forecasts and 10 am local time for 7 DA forecasts.
  • This service does not require any data from clients. QR Meter Data Hub automatically fetches and manages demand data from the market operator data services, as well as weather data vendors.
  • This is part of our Electricity Market Price & System Demand Forecast Service.

Forecast as A Service

  • Intraday and 7 DA forecasts as a web service.
  • We provide weather and ISO & electricity market operator data.
  • No implementation required. Receive forecasts instantly via API or web dashboards & downloads.
  • Forecast resolutions can be 5 to 60 min. Forecast frequency: every 15 min, 24/7, for intraday, and at 10 am for DA forecasts.
  • Option to start with a trial.

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Free Trial

Free trial for 14 days.

View Forecast Samples

View delayed sample demand and nodal LMP price forecasts for the main US electricity markets. Explore our forecast data visualization dashboard.
Forecast View Samples

Contact us today to start your Load Forecast project

Our data science team stands ready to work with you.

QR Load Forecaster Benefits & Features

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How to Proceed

Whether we install QR Load Forecaster on your private cloud or on-site, or you use it as a service, the road map to follow is the same. You can always start with a POC Trial. Our team is here to assist and work with you every step of the way.
Presales 1-5 Days
  • Demos and Q&A.
  • SOW: Identification of number of load data, and type of forecasts of interests for the POC Trial, and later for full service.
  • Execution of POC Trial Agreement.

POC Trial Setup & Onboarding 5 Days
  • Account set-up, access control management.
  • Connectivity to client’s sample load data and data fetching for POC.
  • Load forecast model set-up and testing.
  • Walkthrough and demo for client’s users to use the forecast web-portal for POC Trial.
POC Trial 2-3 Week
  • Client can access the demo portal 24/7 to see and download the selected price forecasts.
  • Support and ongoing Q&A during Trial.
Post POC Trial & Licensing 5 Days
  • Client has the option to execute the Subscription Agreement and start using the solution commercially.
  • Mapping out the full rollout plan for client’s load forecast project.

We offer flexible delivery options:
a) AI Forecast Service where our expert team and platform do everything, and you receive, via API and electronic means, intraday and 5-DA load forecasts, every 5–10 minutes, 24/7.
b) Software as a Service (SaaS) where we implement QR AI Forecaster on a private cloud of your choosing, or on-site, and you control the data and the AI models.

You pay one single annual subscription fee comprising license, maintenance and upgrade releases.

Our expert (MSc and PhD) data science team configures, fine-tunes and deploys your AI forecast models in record time and helps you maintain and calibrate them in time.

QR AI Forecaster is a no-coding AI platform that allows users to drag, drop and combine various AI and Machine Learning methods in a user-friendly dashboard to create their own custom forecast models. The AI platform offers a range of Deep Learning and Machine Learning models especially designed for load forecasting.

To ensure the highest degree of accuracy and stability, AI model optimization is automated with specialized built-in toolboxes that considerably lessen the need and workload of data scientists and analysts.

To perform load forecasting, QR AI Forecaster allows you to aggregate or disaggregate load data on the fly, by any criteria across your operations. E.g., go from individual meters, to cities, regions or by consumer types.

Each forecast can have upper and lower uncertainty bands computed via quantiles or standard deviation.

To reduce project risk, you can start with a Proof of Concept (POC) or trial period. Contact us for more details.

To increase load forecast accuracy, QR AI Forecaster allows users to control a host of key parameters: date range for model training and forecast horizons, calendars to replace intra-term holidays’ data with the nearest Sunday’s data, model splitting to create multiple models across off/peak periods and week/weekend days, model grouping create multiple regression/forecast models, and have a classifier merge them into the best forecast, internal and external predictors, e.g., SCADA, weather indicators, demand and supply side data, generation by fuel type including renewables, outages, ISO published hour and day ahead forecasts, data quantization, scaling, gap filling methods, outlier data remediation.

AI Load & Demand Forecast Case Studies & Video Demos