Deviations from the seasonal norm for water, snow and groundwater reservoirs. Keeping a detailed record of the history, status and expected future developments. The key variable in assessing the timing of future hydro production and corresponding price pressure or hikes.
Monitoring and forecasting power production from reservoirs and run-of-river units. The first source is highly dependent on price expectations, the latter mostly price independent.
Monitoring forecasting reservoir levels, quantified as energy potential. Evaluating when producers are likely to increase or decrease their production based on current and expected future prices and water value.
Energy content in water originating from net precipitation energy, melting from snow/glacier pack and runoff from groundwater into water reservoir and run-of-river production units.
Keeping track of the potential energy that is not stored in observable water reservoirs. Reporting on when it is likely to accumulate/melt/dry up, how much and when it will affect the inflow, and how it will affect production from reservoirs and run-of-river units.
Location of capture fields, installed hydro production capacity and reservoirs, combined with precipitation and evaporation quantified into potential energy content.
All available actual data are prone to errors. Using our forecasting model, EQ provide curated historical data, creating a consistent history going back several years. A perfect source for modelling purposes.
Daily forecasts for hydrological balance, precipitation energy, inflow, production and reservoirs. Based on the hydrological catchment model HYPE which simulates water flow and substances on their way from precipitation through soil, river and lakes to the river outlet.
Seasonal normals are estimated running 30-40 weather years through each model, factoring in social patterns, expected consumption trends, capacity changes, efficiency improvements for wind and solar, etc.
Analyse the potential weather-driven variations in demand and supply for each variable separately or combined. Use the true variability distribution in our risk assessments and get rid of the black swans.
