Economic evaluation of battery storage systems bidding on day-ahead and automatic frequency restoration reserves markets. (15th September 2021)
- Record Type:
- Journal Article
- Title:
- Economic evaluation of battery storage systems bidding on day-ahead and automatic frequency restoration reserves markets. (15th September 2021)
- Main Title:
- Economic evaluation of battery storage systems bidding on day-ahead and automatic frequency restoration reserves markets
- Authors:
- Nitsch, Felix
Deissenroth-Uhrig, Marc
Schimeczek, Christoph
Bertsch, Valentin - Abstract:
- Highlights: Implementation of reserves market in an agent-based electricity market model. Evaluation of battery storage bidding on day-ahead market and reserves market. Improved economic potential in German case study 2030 compared to 2019. Main source of revenues shifts from reserves market to day-ahead market. Highest revenues are found for short-term battery storages. Abstract: In future electricity systems, not only electricity generation but also frequency stabilization must be provided by low-carbon technologies. Battery systems are a promising solution to fill this gap. However, uncertainties regarding their revenue potential may hinder investments. Therefore, we apply the agent-based electricity market model AMIRIS to simulate a day-ahead market and an automatic frequency restoration reserves market. Demonstrating the model setup, we chose a scenario with high shares of renewable energies. First, we back-test our model with historic market data from Germany in 2019. The simulation results' mean day-ahead prices of 39.20 EUR/MWh are close to the historic ones of 38.70 EUR/MWh. Second, we model both markets in a scenario for 2030. The simulated day-ahead market prices are higher on average than observed today, although, we find around 550 h/yr in which the load is fully covered by renewable energies. The variance in simulated prices is slightly higher compared to historic values. Bids on the reserve capacity market are derived from opportunity costs of notHighlights: Implementation of reserves market in an agent-based electricity market model. Evaluation of battery storage bidding on day-ahead market and reserves market. Improved economic potential in German case study 2030 compared to 2019. Main source of revenues shifts from reserves market to day-ahead market. Highest revenues are found for short-term battery storages. Abstract: In future electricity systems, not only electricity generation but also frequency stabilization must be provided by low-carbon technologies. Battery systems are a promising solution to fill this gap. However, uncertainties regarding their revenue potential may hinder investments. Therefore, we apply the agent-based electricity market model AMIRIS to simulate a day-ahead market and an automatic frequency restoration reserves market. Demonstrating the model setup, we chose a scenario with high shares of renewable energies. First, we back-test our model with historic market data from Germany in 2019. The simulation results' mean day-ahead prices of 39.20 EUR/MWh are close to the historic ones of 38.70 EUR/MWh. Second, we model both markets in a scenario for 2030. The simulated day-ahead market prices are higher on average than observed today, although, we find around 550 h/yr in which the load is fully covered by renewable energies. The variance in simulated prices is slightly higher compared to historic values. Bids on the reserve capacity market are derived from opportunity costs of not participating in the day-ahead market. This results in prices of up to 45 EUR/MW for positive reserve while the prices for negative reserve are 0 EUR/MW. Finally, we evaluate revenue potentials of battery storages. Compared to 2019, we see an improved economic potential and increased importance of the day-ahead market. High power battery storages perform best whereas improvements in round-trip efficiency only marginally improve revenues. Although demonstrated for Germany, the presented modular approach can be adapted to international markets enabling comprehensive battery storage assessments. … (more)
- Is Part Of:
- Applied energy. Volume 298(2021)
- Journal:
- Applied energy
- Issue:
- Volume 298(2021)
- Issue Display:
- Volume 298, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 298
- Issue:
- 2021
- Issue Sort Value:
- 2021-0298-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-09-15
- Subjects:
- Energy system modeling -- Agent-based modeling -- Battery storage system -- Day-ahead market -- Automatic Frequency Restoration Reserves market
Power (Mechanics) -- Periodicals
Energy conservation -- Periodicals
Energy conversion -- Periodicals
621.042 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03062619 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.apenergy.2021.117267 ↗
- Languages:
- English
- ISSNs:
- 0306-2619
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1572.300000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17537.xml