Energy Market Data & Forecasts

SpotEx: Short Term Price & Fundamental Forecasts

With the increase of wind and solar, it is vital to see how renewable energy generation will change at the short end of the curve. Get a complete overview of your price area of interest and the potential impact of adjoining power markets. Our pan-European short-term model for weather-driven fundamental data, power flows, net positions, and prices.

woman in front of three screens
Complete market overview

Complete market overview

We provide a comprehensive analysis and visualisation of alternative forecasts/scenarios updated continuously and close to real time.

Best in class tools

Best in class tools

Track record overview comparing model performance to actual prices and flows.

Real-time connection

Real-time connection

Updated 24/7 and every 15 minutes.

How is the SpotEx price formed? What are the underlying assumptions?

The SpotEx model is a two-step algorithm composed of an effective merit order forecast and cross-border exchange forecast. For regions that are dominated by hydropower (e.g. Norway, Northern Sweden and Switzerland), bidding curves replicating the behavior of hydropower producers are used. For price areas dominated by renewables and thermal power output, price-volume curves are estimated. We use our high quality in-house fundamental forecasts (e.g. wind, SPV) alongside UMM data and thermal availability forecasts to estimate these curves. The price-volume curves are trained upon the arrival of new actual day-ahead prices in order to ensure that our price forecasts are both dynamic and always fully updated with the newest market information. The underlying models depend on the price area and are a collection of different machine learning models (e.g. random forest or neural network).

We use in-house cross-border capacity forecasts based on:

  • ATC and NTC exchange forecasts from TSOs.
  • Continuously updated UMM data on exchange borders.
  • PTDF forecasts for the flow-based domain based on information and data from JAO (for the Nordic and CORE regions).

Currently, the following borders are incorporated into SpotEx:

European map with interconnectors

Components of the hydropower bidding curves (hydropower-dominated areas):

  • Estimate price-volume curves for each hour of the day that establishes a relationship between the hydropower production and the spot price, replicating how producers bid into the market.
  • Expert knowledge: Direct input from analysts into the model.

Components of cross-border exchange forecasts

SpotEx aims to maximise the total welfare optimisation function for all European countries simultaneously. The welfare optimisation relates to the power production, consumption in the given countries and cross-border flows. The algorithm calculates explicit, implicit and flow-based allocations in one go. The SpotEx algorithm is a simplified version of Euphemia that can be extended to numerous market topologies, including new FBMC regions in Europe.

The SpotEx model is a comprehensive Pan European short-term price model for power prices and cross-border power exchanges. The model provides hourly price forecasts for the majority of price areas in Europe alongside an overview of market coupling between price areas and also the potential impact of adjoining power markets and/or the rest of Europe. The model considers various fundamental forecasts, thermal capacity, UMMs. The model also runs on various types of fundamental forecasts and scenarios (e.g. EC, GFS, and ensemble paths).

  • Implicit Border: market price calculation and cross-border exchanges are calculated simultaneously.
  • External borders: Border from a modeled price area to a price area without a power exchange (e.g. UA, RU, MK).
  • Flow-based market coupling: Both implicit ATC and FBMC maximise social welfare, and the ideal solution in both cases is total market coupling. In FBMC the traditional ATCs are replaced with a set of inequalities that each represent a physical element in the grid (e.g. lines). This set of inequalities allows higher cross-border flows within the given region, followed by a solution closer to total market coupling and often significant welfare gain.
  • The TSOs forecast the flows in the grid for every hour. From this calculation they can find how much extra flow each grid element can handle. This is called the remaining available margin (RAM) and is the limiting factor in each inequality. They also calculate power transfer distribution factors (PTDF) that relate how the net export of every country will affect this element. Together with the RAM the PTDFs make up the constraint on the cross-border flows from that element. The constraints are different from hour to hour and vary with all the elements that affect the flow in the grid.

Our spot price and exchange forecasts cover 90 days into the future at an hourly resolution.

The price areas marked in black below are covered by the SpotEx model. The ones in light grey currently are not. We aim to cover all price areas in Europe and aim to expand the SpotEx model in the near future.

areas_spotex.png

Updated forecasts are published every 15 minutes for deterministic runs and every hour for ensemble runs, enabling for continuously updated price and exchange forecasts upon the arrival of new model input. This means that transfer capacities, nuclear outages, shifts in fundamentals, etc. are quickly incorporated into our forecasts.

The SpotEx model runs on various weather data input:

  • ECMWF deterministic weather data, updated twice per day.
  • ECMWF ensemble weather data, updated twice per day.
  • ECMWF 46-day forecast, updated once a day.
  • GFS deterministic weather data: 9 days, updated four times per day.
  • Scenario data based on normals (used for updating our merged curve for days 47-90)

Get in touch

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Ana Illan

Ana Illan, Account Executive