2000 character limit reached
Representative electricity price profiles for European day-ahead and intraday spot markets (2405.14403v1)
Published 23 May 2024 in stat.AP, cs.CE, and physics.soc-ph
Abstract: We propose a method to construct representative price profiles of the day-ahead (DA) and the intraday (ID) electricity spot markets and use this method to provide examples of ready-to-use price data sets. In contrast to common scenario generation approaches, the method is deterministic and relies on a small number of degrees of freedom, with the aim to be well defined and easy to use. We thereby target an enhanced comparability of future research studies on demand-side management and energy cost optimization. We construct the price profiles based on historical time series from the spot markets of interest, e.g., European Power Exchange (EPEX) spot. To this end, we extract key price components from the data while also accounting for known dominant mechanisms in the price variation. Further, the method is able to preserve key statistical features of the historical data (e.g., mean and standard deviation) when constructing the benchmark profile. Finally, our approach ensures comparability of ID and DA price profiles by design, as their cumulative (integral) price can be made identical if needed.
- Electricity price forecasting by averaging dynamic factor models. Energies, 9(8), 600.
- A flexible air separation process: 1. design and steady-state optimizations. AIChE Journal, 65(11), e16705.
- The integration of scheduling and control: Top-down vs. bottom-up. Journal of Process Control, 91. https://doi.org/10.1016/j.jprocont.2020.05.008
- Multivariate probabilistic forecasting of intraday electricity prices using normalizing flows. Applied Energy, 346, 121370. https://doi.org/https://doi.org/10.1016/j.apenergy.2023.121370
- Forecasting electricity spot-prices using linear univariate time-series models. Applied Energy, 77(1), 87–106.
- A non-uniform grid approach for scheduling considering electricity load tracking and future load prediction. Computers & Chemical Engineering, 129, 106506. https://doi.org/https://doi.org/10.1016/j.compchemeng.2019.06.031
- Optimal design and flexible operation of a fully electrified biodiesel production process. Industrial & Engineering Chemistry Research, 63(3), 1487–1500. https://doi.org/10.1021/acs.iecr.3c03074
- EPEX (2023). Accessed: 2023-10-02. https://www.epexspot.com
- Friedler, F. (2010). Process integration, modelling and optimisation for energy saving and pollution reduction. Applied Thermal Engineering, 30(16), 2270–2280. Selected Papers from the 12th Conference on Process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction. https://doi.org/https://doi.org/10.1016/j.applthermaleng.2010.04.030
- The role of grid extensions in a cost-efficient transformation of the european electricity system until 2050. Applied Energy, 104, 642–652. https://doi.org/https://doi.org/10.1016/j.apenergy.2012.11.050
- Data-driven modeling for long-term electricity price forecasting. Energy, 244, 123107.
- Demand response scheduling of copper production under short-term electricity price uncertainty. Computers & Chemical Engineering, 178, 108394.
- Demand Response Potential of Industrial Processes Considering Uncertain Short–term Electricity Prices. AIChE Journal. https://doi.org/10.1002/aic.17828
- High frequency electricity spot price dynamics: An intra-day markets approach. Available at SSRN 367760.
- A review on time series aggregation methods for energy system models. Energies, 13(3). https://doi.org/10.3390/en13030641
- Econometric analysis of 15-minute intraday electricity prices. Energy Economics, 64, 77–90.
- An empirical examination of restructured electricity prices. Energy Economics, 27(5), 791–817. https://doi.org/https://doi.org/10.1016/j.eneco.2004.11.005
- Day-ahead vs. intraday—forecasting the price spread to maximize economic benefits. Energies, 12(4), 631.
- Multi-market optimization of industrial flexibility - market comparison and field test results. CIRED Workshop 2016. https://doi.org/10.1049/cp.2016.0762
- Challenges in process optimization for new feedstocks and energy sources. Computers & Chemical Engineering, 113, 209–221. https://doi.org/10.1016/j.compchemeng.2018.03.013
- New probabilistic price forecasting models: Application to the iberian electricity market. International Journal of Electrical Power & Energy Systems, 103, 483–496.
- Cost-optimal power-to-methanol: Flexible operation or intermediate storage? Journal of Energy Storage, 72, 108614. https://doi.org/https://doi.org/10.1016/j.est.2023.108614
- Nord Pool (2023). Accessed: 2023-11-02. https://www.nordpoolgroup.com
- Recent advances in electricity price forecasting: A review of probabilistic forecasting. Renewable and Sustainable Energy Reviews, 81, 1548–1568. https://doi.org/https://doi.org/10.1016/j.rser.2017.05.234
- Benefits and challenges of electrical demand response: A critical review. Renewable and Sustainable Energy Reviews, 39, 686–699.
- Selecting representative days for capturing the implications of integrating intermittent renewables in generation expansion planning problems. IEEE Transactions on Power Systems, 32(3), 1936–1948. https://doi.org/10.1109/TPWRS.2016.2596803
- Strategic bidding for a virtual power plant in the day-ahead and real-time markets: A price-taker robust optimization approach. IEEE Transactions on Power Systems, 31, 2676–2687. https://api.semanticscholar.org/CorpusID:24517724
- Do investments in flexibility enhance sustainability? a simulative study considering the german electricity sector. AIChE Journal, 66(11), e17010.
- Scott, D. W. (1979). On optimal and data-based histograms. Biometrika, 66(3), 605–610. https://doi.org/10.1093/biomet/66.3.605
- Short-term forecasting for the electricity spot prices with extreme values treatment. IEEE Access, 9, 105451–105462.
- A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets. Energy, 258, 124856. https://doi.org/https://doi.org/10.1016/j.energy.2022.124856
- Systematic comparison of aggregation methods for input data time series aggregation of energy systems optimization problems. 13th International Symposium on Process Systems Engineering (PSE 2018), volume 44 of Computer Aided Chemical Engineering, 955–960. Elsevier. https://doi.org/https://doi.org/10.1016/B978-0-444-64241-7.50154-3
- Clustering methods to find representative periods for the optimization of energy systems: An initial framework and comparison. Applied Energy, 239, 1283–1293. https://doi.org/https://doi.org/10.1016/j.apenergy.2019.02.012
- Weron, R. (2014). Electricity price forecasting: A review of the state-of-the-art with a look into the future. International Journal of Forecasting, 30(4), 1030–1081. https://doi.org/https://doi.org/10.1016/j.ijforecast.2014.08.008
- Electricity price forecasting by a hybrid model, combining wavelet transform, arma and kernel-based extreme learning machine methods. Applied Energy, 190, 291–305. https://doi.org/https://doi.org/10.1016/j.apenergy.2016.12.130
- Economic impact of electricity market price forecasting errors: A demand-side analysis. IEEE Transactions on Power Systems, 25(1), 254–262. https://doi.org/10.1109/TPWRS.2009.2030380
Sponsor
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.