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GCRIEnergy NexusEstablished
Method page · Forecasting and time-series analysis

Forecasting for power systems

Forecasting gives energy operators lead time: minutes to days for demand and renewable output, weeks to seasons for hydropower inflows and adequacy outlooks. The value lies in calibrated probabilities with stated skill, which let operators hold the right reserves at the right time.

Method recordforecasting
  1. MethodForecasting and time-series analysis
  2. Applied inEnergy Nexus
  3. Canonical pageSTEM Commons

GCRI · Established · service level R0

01In brief

The short answer.

Load and renewable power forecasting is the prediction of electricity demand and wind and solar output from minutes to days ahead, and of inflows and adequacy weeks to seasons ahead. Calibrated probabilities with stated skill let operators hold the right reserves at the right time.

02Application

What forecasting and time-series analysis does here.

Forecasting and time-series analysis predict future values of variables from past observations and explanatory information. They support early warning and planning across hazards, markets and health. In energy, critical infrastructure and climate and hazards, forecasts trigger early action and anticipatory finance before shocks materialise. Probabilistic forecasts allow decisions to account for uncertainty across connected systems. The canonical description is on the STEM Commons.

Load forecasting with weather

Demand is forecast from temperature, calendar and economic drivers, with probabilistic ranges that widen with lead time and during temperature extremes.

Wind and solar power forecasts

Ensemble weather forecasts are converted into power output for each region, so operators see the probability of ramps and low-output spells, not a single line.

Seasonal adequacy outlooks

Seasonal climate forecasts, reservoir levels and planned outages are combined into outlooks of supply margin for the coming winter or summer.

03Key terms

Terms used on this page.

Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.

TermDefinition
Probabilistic forecastA forecast given as a range of outcomes with probabilities rather than a single value.
Forecast horizonHow far ahead a forecast predicts, from intraday to seasonal.
Reserve requirementThe spare capacity an operator holds to cover forecast errors and outages.
04Geography

Energy demand and corridors in the Nordic and Baltic region.

Where demand concentrates in cities and the rail, road and port corridors that move fuel and equipment, shown for the Nordic and Baltic region as an example geography for this subject.

Where demand concentrates in cities and the rail, road and port corridors that move fuel and equipment.Indicator derived from Natural Earth at map scale; a screening view, not an assessment.
GCRI · Energy Nexus · fieldDESIGN FIGURE
05Canvas

The method as a run graph.

Data from the source register feeds the methods; calibration and an independent test gate the estimate and its limits; the decision stays with the competent authority.

Method canvas · Forecasting and time-series analysis as applied hereDesign, not a record
Forecasting and time-series analysis in Energy Nexus: flood forecasting and warning chainRainfall forecasts drive a hydrological then a hydraulic model; inundation maps are compared with thresholds; the mandated authority issues the warning, it reaches people through every channel, and action follows. Design of the process, not a record of a run.

Fig. 01Nodes carry their type, metrics and state; connectors show what feeds what; the gates are the validation steps; the timeline is one application. Design of the method's use, not a record of a run.

06Data

What the method consumes.

Datasets and records used by forecasting and time-series analysis on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.

DataRoleLabel
Ensemble numerical weather predictionForecast forcingFORECAST
Historical load and generation recordsModel training and verificationOFFICIAL
Copernicus seasonal climate forecastsOutlook forcingFORECAST
Real-time metering and SCADANowcasting and correctionOBSERVED
07Validation

How results are checked.

Forecasts are evaluated out of sample with proper scoring rules and reliability diagrams. Rolling-origin evaluation tests performance over time.

CheckHow it is done
Out-of-sample verificationForecasts are scored with proper scoring rules on periods not used in training
Reliability diagramsStated probabilities of ramps and peaks are checked against observed frequencies
Extreme-event performanceSkill is reported separately for heat waves, cold spells and storms, not only on average days

Structural breaks and regime changes undermine models trained on the past. Forecast skill typically declines rapidly with lead time.

09Stewardship

Who maintains the method.

Climate and Hazards stewards forecasting and time-series analysis for the Consortium and reviews how it is applied across platforms.

11Questions

Questions and answers.

What are the limits of forecasting and time-series analysis in this field?
Structural breaks and regime changes undermine models trained on the past. Forecast skill typically declines rapidly with lead time.
How are results checked?
Forecasts are evaluated out of sample with proper scoring rules and reliability diagrams. Rolling-origin evaluation tests performance over time.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method's use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
Energy Nexus

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