{"id":2908,"date":"2026-06-23T10:51:09","date_gmt":"2026-06-23T10:51:09","guid":{"rendered":"https:\/\/artelnics.com\/case_studies\/indra-distribution-forecast-module\/"},"modified":"2026-08-21T20:20:18","modified_gmt":"2026-08-21T20:20:18","slug":"indra-distribution-forecast-module","status":"publish","type":"case_studies","link":"https:\/\/artelnics.com\/case_studies\/indra-distribution-forecast-module\/","title":{"rendered":"Forecasting load and generation in distribution grids"},"content":{"rendered":"
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Machine-learning services forecast transformer load and distributed generation inside a distribution management system.<\/p>\n

\n Energy and utilities<\/span>
\n Load and generation forecasting<\/span>
\n Smart-grid planning<\/span>\n <\/div>\n

Challenge<\/h2>\n

Distribution grid operators need load and generation forecasts across multiple areas and facilities to support operations planning, feeder reconfiguration and renewable integration.<\/p>\n

Data<\/h2>\n

The module uses transformer loads, renewable plant generation, meteorological conditions, calendar variables and area\/facility metadata from the TPC database.<\/p>\n

Solution<\/h2>\n

Artelnics implemented load and generation forecasting services with clustering, model training, forecast execution, validation metrics and database-backed deployment.<\/p>\n

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Forecast types<\/strong><\/p>\n

Short-term, medium-term and long-term load and generation forecasts.<\/p>\n<\/div>\n

Deployment<\/strong><\/p>\n

Services integrated with a distribution forecast module.<\/p>\n<\/div>\n<\/div>\n

Results<\/h2>\n

The system provides forecasts for operations analysis and planning, helping distribution management systems evaluate future load, generation and network conditions.<\/p>\n

Illustrations<\/h2>\n
\"Transformer
Transformer station assignment<\/figcaption><\/figure>\n
\"Forecasting
Demand forecasting diagram<\/figcaption><\/figure>\n<\/article>\n