A practical scenario generation method for electricity prices on day-ahead and intraday spot markets

The increasing interest in demand-side management (DSM) as part of the energy cost optimization calls for effective methods to determine representative electricity prices for energy optimization and scheduling investigations. We propose a practical method to construct price profiles of day-ahead (DA) and intraday (ID) electricity spot markets. We construct single-day and single-week price profiles based on historical market time series to provide ready-to-use price data sets. Our method accounts for dominant mechanisms in price variation to preserve critical statistical features (e.g., mean and standard deviation) and transient patterns in the constructed profiles. Unlike common scenario generation approaches, the method is deterministic, with few degrees of freedom and minimal application effort. Our method ensures consistency between ID and DA price profiles when both are considered and introduces profile scaling to enable multiple scenario generation. Finally, we compare the constructed profiles to clustering techniques in a DSM case study, noting similar cost results.