Time-series forecasting models
Across classical, ML, and deep learning approaches applied to relevant horizons.
Forecasts engineered to be acted on.
Forecasting is where energy operations meet uncertainty. Demand shifts, weather changes, renewable generation fluctuates, and the cost of getting the forecast wrong shows up immediately - in dispatch decisions, balancing costs, customer reliability, and trading positions.
Entiovi engineers forecasting systems that deliver accuracy operations can act on: calibrated to the time horizon that matters, integrated with the planning and operational systems that use them, and instrumented so accuracy can be measured continuously.
Entiovi designs and builds demand and generation forecasting systems for utilities, grid operators, renewable energy companies, energy traders, and industrial consumers. The work spans data engineering across consumption, generation, weather, and market signal, model development at the time horizon the operation requires - intra-hour, day-ahead, week-ahead, seasonal - and integration with planning, dispatch, and trading workflows.
Forecasts are evaluated on the metrics the business cares about, not academic benchmarks. Accuracy is measured continuously, against the operational decisions the forecasts feed - and improvement is engineered into the platform rather than promised on a slide.
Across classical, ML, and deep learning approaches applied to relevant horizons.
Coupling forecasts with weather, market, and operational signal.
For solar irradiance, wind power, and hybrid generation forecasting.
At segment, customer-class, and feeder level.
With probabilistic forecasts that operations can plan against.
With forecasts delivered where decisions are actually made.
For grid operators and balancing functions.
For energy traders and aggregators.
For wind and solar operators.
For distribution operators and aggregators integrating distributed assets.
For procurement and production planning.
For utility infrastructure planning.
Better-informed dispatch and trading decisions, reduced balancing and imbalance costs, improved renewable integration, sharper capacity and procurement planning, and a forecasting function whose accuracy is continuously measured and continuously improving.
Engagement begins with use case scoping and a forecasting-accuracy baseline against current operations. From there, Entiovi designs the data and feature architecture, develops models calibrated to the relevant horizons, integrates forecasts with EMS, dispatch, or trading systems, and operates the forecasting function with continuous performance monitoring against the business metrics that matter.
A forecast is only as valuable as the decision it improves. Entiovi engineers for the decision first - and lets the model serve it.
Talk to Entiovi about putting this discipline into production - from design and engineering through ongoing operation, with delivery from India and regional presence in your market.