- Energy supply & demand
- Weather data
- Hydrology
- REMIT data
- Interconnector flows
- Futures, fuels and costs
- Intraday power prices
- Day ahead power forecasts
- PPA prices
- Carbon intensity toolkit
- Balancing market data
- Ancillary services data
- EU power plant database
- Power price scenarios
- Hydrogen Prices
- Advisory reports
- Production forecasting
- Demand forecasting
- Geolocation analysis
- Power 2 Sim
Hydrology
The whole chain of causes and effects in hydrology, quantified into power prices to save you time.
Overview
Historical data, current status and expectations of how stored energy affects future price formation in the power market.
Deviations from the seasonal norm for water, snow and groundwater reservoirs. The key variable in helping you assess the timing of future hydro production and corresponding price movements.
Monitoring and forecasting of power produced from reservoirs and run-of-river units allows you to see how market prices affect which of these two production types are used.
Monitoring and forecasting of reservoir levels, shown as energy potential. This helps you to evaluate when producers are likely to increase or decrease their production based on current and expected future prices and water value.
Understanding the energy content in water originating from net precipitation energy, melting from snow/glacier packs and runoff from groundwater into water reservoir and run-of-river production units help you identify the impacts of changing water resources.
Keep 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.
Understand the location of capture fields, installed hydro production capacity and reservoirs, combined with precipitation and evaporation expressed as potential energy content.
Curated actuals
Using our forecasting model, Montel Analytics provide curated historical data. This removes errors, creates a consistent history going back several years and gives you corrected datasets you can trust.
Seasonal normals
Estimated by running between 30-40 weather years through each model. We factor in social patterns, expected consumption trends, capacity changes, efficiency improvements for renewables and more so you can identify baseline scenarios.
Forecasts
Be confident your models are current with 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.
Fundamental climate data
Analyse the potential weather-driven variations in demand and supply for each variable individually or combined. Use true variability distribution in our risk assessments to identify black swan events.
Try hydrology for free
With so much data available, Montel Analytics often requires tailored solutions. Get in touch with our product experts so we can build the exact package to meet your needs.