DAISY

The DAISY model (Day-Ahead and Intraday Prices under Consideration of Short-term Flexibility) fundamentally represents the essentials of price formation in the intraday market by optimizing the coverage of quarter-hourly forecast deviations through the deployment of dispatchable power plants and storage at minimum system cost. DAISY builds on the simulation results of a representative day-ahead market model (e.g. DIMENSION, SPIDER, MELI) and derives from them price time series as well as storage dispatch decisions for the intraday market. On this basis, revenue potentials of battery storage as well as cannibalization effects caused by changing market structures can be analyzed, among other things.

DAISY for Consulting and Research

The model supports the analysis of future intraday market developments and provides a consistent basis for assessing short-term flexibilities in the German electricity system. In particular, DAISY delivers intraday price time series, assesses storage revenues, examines market and cannibalization effects, and serves as an input for the asset valuation of technologies with EASE.

DAISY in Practice:

• Price projections: derive quarter-hourly intraday price time series consistent with day-ahead prices
• Economic analysis: assess revenue potentials and market values of battery storage in the intraday market
• Market mechanics: analyze cannibalization effects and price impacts of additional short-term flexibilities
• Model coupling: provide intraday price time series as an input for asset valuation with EASE

DAISY in Detail

DAISY is a mixed-integer quadratic programming model and represents the essentials of the German intraday market. The model minimizes the cost of covering quarter-hourly forecast deviations by optimizing the deployment of dispatchable power plants and battery storage. Starting from hourly day-ahead price time series, DAISY thus derives consistent quarter-hourly intraday price time series. The focus is on analyzing how intraday prices develop with the transformation of the energy system and which revenue potentials arise from this, in particular for battery storage.

A particular focus lies on representing the short-term market mechanics of intraday trading. DAISY takes into account that forecast deviations arise from deviations between forecast and realized renewable feed-in, demand, and power plant outages, while on the supply side only a limited part can react to this at short notice. These restrictions, as well as commitments already entered into by market participants in the day-ahead market, change the short-term merit order and thereby shape price formation in the intraday market.

Schematic Representation of the Model

The optimization of short-term market balancing in DAISY is carried out on a quarter-hourly basis for a freely selectable time horizon. As central input variables, DAISY uses day-ahead prices, renewable energy feed-in, power plant dispatch, demand time series, and the storage deployment already carried out in the day-ahead market. The model represents forecast deviations via deviations between expected and actual feed-in and demand as well as via power plant outages; the resulting shadow prices are interpreted as intraday prices.