Evaluation model of new energy consumption capacity based on risk theory
Pages 51 - 56
Abstract
The evaluation of new energy consumption capacity is of great significance in the development of sustainable energy. Based on wind power as the research object, this paper proposes a new energy absorption capacity evaluation model considering risk factors. The model consists of two parts. The first part is the theoretical value of wind power absorption capacity when the comprehensive influence of risk factors is not considered, that is, the wind power absorption capacity defined in the previous paragraph. This part of the calculation is based on the Balmorel model to optimize the potential of wind power consumption. The second part is the adjustment value of the wind power absorption capacity when considering the comprehensive influence of the risk factors, and this part is constructed based on the risk theory. The product of the occurrence probability of risk events and the degree of influence of risk events is used to represent the adjustment value of wind power absorption capacity. Among them, the impact degree of risk events also needs to be optimized based on the Balmorel model to ensure the accurate reflection of the risk factors of wind power absorption capacity. By introducing risk factors into the new energy absorption capacity evaluation model, this study provides a more comprehensive decision support, which helps to accurately estimate the reliability and stability of new energy in the power system. This model can not only be applied to wind power, but also can be extended to other forms of new energy, providing a powerful tool for the sustainable development of new energy. Therefore, the comprehensive evaluation of the new energy absorption capacity in this study is important in promoting the large-scale application of renewable energy and the reliability improvement of the power system.
References
[1]
Haas, R., Resch, G., Panzer, C., Busch, S., & Ragwitz, M. (2011). A historical review of promotion strategies for electricity from renewable energy sources in EU countries. Renewable and Sustainable Energy Reviews, 15(2), 1003-1034.
[2]
Caporin, M., McAleer, M., & Zhang, W. (2019). Minimizing Downside Risk for Energy Investments: The Role of Emissions Markets. Journal of Risk and Financial Management, 12(3), 114.
[3]
Holttinen, H., Meibom, P., Orths, A., Lange, B., O'Malley, M., & Tande, J. O. (2011). Design and operation of power systems with large amounts of wind power—Final summary report. IEA Wind Task 25.
[4]
Awerbuch, S. (2008). Reliable integration of wind and solar generation: How much storage is needed?. Energy Policy, 36(12), 4400-4408.
[5]
Wang, J., & Guo, S. (2011). New combined forecasting approach based on EMD and ARIMA for wind power generation. Energy Conversion and Management, 52(2), 687-693.
[6]
Zhang, X., & Zhou, D. (2017). A review on models and computations of the uncertainty in wind power forecasting. Renewable and Sustainable Energy Reviews, 70, 819-832.
[7]
Pinson, P., & Kariniotakis, G. (2010). Conditional prediction intervals of wind power generation. In 2010 IEEE PES General Meeting (pp. 1-8). IEEE.
[8]
Sioshansi, R. (2009). Market operations in electric power systems: forecasting, scheduling, and risk management. John Wiley & Sons.
[9]
Giebel, G., Brownsword, R., Kariniotakis, G., Denhard, M., Draxl, C., Gómez-Iradi, S., ... & Sempreviva, A. M. (2016). New European Wind Atlas. EWEC.
[10]
Holttinen, H., Jónsson, T., & van Hulle, F. (Eds.). (2015). Integration of wind energy: 20 years of international research. John Wiley & Sons.
[11]
Skov, I., & Sørensen, P. (2006). A statistical model for short-term prediction of the time series of wind speed. Wind Energy, 9(1-2), 61-75.
[12]
Figueiredo, N. C., Azevedo, L. F., Morgado, E., & Pereira, J. C. (2011). Risk assessment of wind power integration into short-term hydrothermal scheduling. IEEE Transactions on Power Systems, 26(1), 219-228.
[13]
Zhang, N., & Zhou, B. (2018). A review of risk assessment and management for wind power. Renewable and Sustainable Energy Reviews, 81, 2607-2618.
[14]
Zhang, J., Zhang, P., Wang, Z., Zhang, X., & Ji, J. (2013). Risk assessment of wind power investment in China. Renewable Energy, 54, 138-143.
[15]
Bertsch, J., Growitsch, C., & Lorenczik, S. (2016). Electricity price forecasts for Europe: The impact of forecast resolution on the profitability of wind energy investments. Energy Economics, 54, 272-282.
[16]
De Felice, M., & Santucci de Magistris, P. (2014). Wind power, EEX prices and banking risk. Energy Policy, 67, 387-395.
[17]
Roulston, M. S., & Smith, L. A. (2003). Evaluating probabilistic forecasts using information theory. Monthly Weather Review, 131(8), 1658-1668.
[18]
Conejo, A. J., Plazas, M. A., Espinola, R., & Molina, A. B. (2005). Day-ahead electricity price forecasting using the wavelet transform and ARIMA models. IEEE Transactions on Power Systems, 20(2), 1035-1042.
[19]
Söder, L., & Söder, L. (2009). Wind power in power systems (Vol. 32). London: Springer.
[20]
Ummels, B. C., Gibescu, M., Pelgrum, E., & Kling, W. L. (2009). Impacts of wind power on thermal generation unit commitment and dispatch. IEEE Transactions on Energy Conversion, 24(2), 165-175.
Index Terms
- Evaluation model of new energy consumption capacity based on risk theory
Index terms have been assigned to the content through auto-classification.
Recommendations
The identification of high-risk factors of banks based on risk matrix
AbstractBank risk management is an important issue in the stability of financial system. How to select risk factors with great impact on banks has become a problem at present. Most of the previous studies have considered the disclosure frequency of the ...
A method for project portfolio risk assessment considering risk interdependencies – a network perspective
AbstractProject portfolios represent the bridge between projects and strategy. However, the final results may not be as expected because materialization of risk factors. Hence, literature has acknowledged project portfolio risk assessment as an element of ...
A New Decomposition Method of Influential Factors on Energy Consumption Intensity
IS3C '12: Proceedings of the 2012 International Symposium on Computer, Consumer and ControlTo study the influential degree of energy consumption influential factors impacting on energy consumption is the foundation of reducing energy consumption and saving energy. Energy consumption intensity influential factors decomposition is a class ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
November 2023
341 pages
ISBN:9798400708091
DOI:10.1145/3635175
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 21 December 2023
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
ICIIP 2023
ICIIP 2023: 2023 8th International Conference on Intelligent Information Processing
November 21 - 22, 2023
Bucharest, Romania
Acceptance Rates
Overall Acceptance Rate 87 of 367 submissions, 24%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 10Total Downloads
- Downloads (Last 12 months)6
- Downloads (Last 6 weeks)0
Reflects downloads up to 16 Feb 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format