The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices

Citations

Cited by:

1. Meng, Anbo & Wang, Peng & Zhai, Guangsong & Zeng, Cong & Chen, Shun & Yang, Xiaoyi & Yin, Hao, 2022. "Electricity price forecasting with high penetration of renewable energy using attention-based LSTM network trained by crisscross optimization," Energy, Elsevier, vol. 254(PA).
2. Yao, Yunting & Gao, Ciwei & Tian, Hongjie & Zhang, Huiling, 2020. "Review of mid-to long-term trading mechanism for renewable electricity consumption in Ningxia, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
3. Sinan Deng & John Inekwe & Vladimir Smirnov & Andrew Wait & Chao Wang, 2023. "Machine Learning and Deep Learning Forecasts of Electricity Imbalance Prices," Working Papers 2023-03, University of Sydney, School of Economics.
4. Marcel Kremer & Rüdiger Kiesel & Florentina Paraschiv, 2020. "Intraday Electricity Pricing of Night Contracts," Energies, MDPI, vol. 13(17), pages 1-14, September.
5. Kuppelwieser, Thomas & Wozabal, David, 2021. "Liquidity costs on intraday power markets: Continuous trading versus auctions," Energy Policy, Elsevier, vol. 154(C).
6. Atherton, John & Hofmeister, Markus & Mosbach, Sebastian & Akroyd, Jethro & Farazi, Feroz & Kraft, Markus, 2023. "British imbalance market paradox: Variable renewable energy penetration in energy markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
7. Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices," Energies, MDPI, vol. 13(14), pages 1-19, July.
   • Katarzyna Maciejowska & Bartosz Uniejewski & Tomasz Serafin, 2020. "PCA forecast averaging - predicting day-ahead and intraday electricity prices," WORking papers in Management Science (WORMS) WORMS/20/02, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
8. Huisman, Ronald & Stet, Cristian, 2022. "The dependence of quantile power prices on supply from renewables," Energy Economics, Elsevier, vol. 105(C).
9. Stefano Frizzo Stefenon & Laio Oriel Seman & Viviana Cocco Mariani & Leandro dos Santos Coelho, 2023. "Aggregating Prophet and Seasonal Trend Decomposition for Time Series Forecasting of Italian Electricity Spot Prices," Energies, MDPI, vol. 16(3), pages 1-18, January.
10. Lee, Seonho & Kim, Jiwon & Byun, Jaewon & Joo, Junghee & Lee, Yoonjae & Kim, Taehyun & Hwangbo, Soonho & Han, Jeehoon & Kim, Sung-Kon & Lee, Jechan, 2023. "Environmentally-viable utilization of chicken litter as energy recovery and electrode production: A machine learning approach," Applied Energy, Elsevier, vol. 350(C).
11. Ilkay Oksuz & Umut Ugurlu, 2019. "Neural Network Based Model Comparison for Intraday Electricity Price Forecasting," Energies, MDPI, vol. 12(23), pages 1-14, November.
12. Grzegorz Marcjasz & Bartosz Uniejewski & Rafał Weron, 2020. "Beating the Naïve—Combining LASSO with Naïve Intraday Electricity Price Forecasts," Energies, MDPI, vol. 13(7), pages 1-16, April.
    • Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2020. "Beating the naive: Combining LASSO with naive intraday electricity price forecasts," WORking papers in Management Science (WORMS) WORMS/20/01, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
13. Cheng, Lilin & Zang, Haixiang & Wei, Zhinong & Zhang, Fengchun & Sun, Guoqiang, 2022. "Evaluation of opaque deep-learning solar power forecast models towards power-grid applications," Renewable Energy, Elsevier, vol. 198(C), pages 960-972.
14. Kazmi, Hussain & Tao, Zhenmin, 2022. "How good are TSO load and renewable generation forecasts: Learning curves, challenges, and the road ahead," Applied Energy, Elsevier, vol. 323(C).
15. Thomas Kuppelwieser & David Wozabal, 2023. "Intraday power trading: toward an arms race in weather forecasting?," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 57-83, March.
16. Yuan Yuan & Feng Cai & Lingling Yang, 2020. "Renewable Energy Investment under Carbon Emission Regulations," Sustainability, MDPI, vol. 12(17), pages 1-15, August.
17. Heeseung Moon & Dongsu Lee & Jeongmin Han & Yongtae Yoon & Seungwan Kim, 2021. "Impact of Imbalance Pricing on Variable Renewable Energies with Different Prediction Accuracies: A Korean Case," Energies, MDPI, vol. 14(13), pages 1-19, July.
18. Li, Ranran, 2023. "Forecasting energy spot prices: A multiscale clustering recognition approach," Resources Policy, Elsevier, vol. 81(C).
19. Kaneko, Nanae & Fujimoto, Yu & Hayashi, Yasuhiro, 2022. "Sensitivity analysis of factors relevant to extreme imbalance between procurement plans and actual demand: Case study of the Japanese electricity market," Applied Energy, Elsevier, vol. 313(C).
20. Michail Nektarios A. & Melas Konstantinos D., 2022. "Geopolitical Risk and the LNG-LPG Trade," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 28(3), pages 243-265, September.
21. Afentoulis, Konstantinos D. & Bampos, Zafeirios N. & Vagropoulos, Stylianos I. & Keranidis, Stratos D. & Biskas, Pantelis N., 2022. "Smart charging business model framework for electric vehicle aggregators," Applied Energy, Elsevier, vol. 328(C).
22. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
23. Huisman, Ronald & Koolen, Derck & Stet, Cristian, 2021. "Pricing forward contracts in power markets with variable renewable energy sources," Renewable Energy, Elsevier, vol. 180(C), pages 1260-1265.
24. Corinaldesi, Carlo & Lettner, Georg & Auer, Hans, 2022. "On the characterization and evaluation of residential on-site E-car-sharing," Energy, Elsevier, vol. 246(C).
25. Ruhang, Xu & Jia, Jia, 2023. "Towards reliability competition: Non-cooperative market mechanism under high variable renewable energy penetration," Applied Energy, Elsevier, vol. 331(C).
26. Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2022. "Short-term risk management of electricity retailers under rising shares of decentralized solar generation," Energy Economics, Elsevier, vol. 109(C).
    • Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2021. "Short-term risk management for electricity retailers under rising shares of decentralized solar generation," Working Paper Series in Production and Energy 57, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
27. Akylas Stratigakos & Athanasios Bachoumis & Vasiliki Vita & Elias Zafiropoulos, 2021. "Short-Term Net Load Forecasting with Singular Spectrum Analysis and LSTM Neural Networks," Energies, MDPI, vol. 14(14), pages 1-13, July.
28. Sirin, Selahattin Murat & Yilmaz, Berna N., 2021. "The impact of variable renewable energy technologies on electricity markets: An analysis of the Turkish balancing market," Energy Policy, Elsevier, vol. 151(C).
29. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).