Research Article | OPEN ACCESS
The Electricity Portfolio Decision-making Model Based on the CVaR under Risk Conditions
Ma Tongtao and Li Cunbin
School of Economics and Management, North China Electric Power University, Beijing 102206, China
Research Journal of Applied Sciences, Engineering and Technology 2014 3:570-575
Received: March 04, 2013 | Accepted: March 27, 2013 | Published: January 20, 2014
Abstract
With the gradual opening up of China's power sector, electricity investment is growing. Risk analysis should be applied to the investment optimization decisions. This study describes a CVaR-based investment optimization model, which established electricity portfolio decision-making model to optimize the ratio of investment decision-making and achieve the maximum yield of the total investment target between the various modes of generation. An example was given to verify the validity of the model based on the actual data. Based on simulation results of the example, the ratio of investment in a certain confidence level has been well optimized. The model can play purposes for overall investment risk reduction.
Keywords:
Risk analysis, the electricity investment, the optimization model,
References
-
Alexander, V., 2006. Efficiency of electric power generation in the United States: Analysis and forecast based on date envelopment analysis. J. Energy Econ., 4: 326-3388.
-
Chen, F.Y., 2011. Analytical VaR for international portfolios with common jumps. Comput. Math. Appl., 62: 3066-3076.
CrossRef -
Claro, J. and J.P. Sousa, 2012. A multiobjective metaheuristic for a mean-risk multistage capacity investment problem with process flexibility. Comput. Oper. Res., 39: 838-849.
CrossRef -
Glasserman, P., P. Heidelberger and P. Shahabuddin, 2002. Portfolio value-at-risk with heavy-tailed risk factors. Math. Financ., 12(3): 39-69.
CrossRef -
Goh, J.W., K.G. Lim, M. Sim and W. Zhang, 2012. Portfolio value-at-risk optimization for asymmetrically distributed asset returns. Eur. J. Oper. Res., 221: 397-406.
CrossRef -
Kemal, S. and O Ilhan, 2007. Efficiency assessment of Turkish power plants using date envelopment analysis. J. Energy, 32(8): 1484-1489.
CrossRef -
Lim, A.E.B., J.G. Shanthikumar and G.Y. Vahn, 2011. Conditional value-at-risk in portfolio optimization: Coherent but fragile. Oper. Res. Lett., 39: 163-171.
CrossRef -
Pun, L.L. and A. Shiu, 2001. A date envelopment analysis of the efficiency of China's thermal power generation. J. Utilities Policy, 2: 75-83.
-
Schaumburg, J., 2012. Predicting extreme value at risk: Nonparametric quantile regression with refinements from extreme value theory. Comput. Stat. Data Anal., 56(12): 4081-4096.
CrossRef -
Wenjie, H., W. Jiang, X. Li and H. Lu, 2010. Studies on the performance evaluation system for the constructions of the sustainable ultra supercritical fossil power plants. J. East China Electr. Power, 6: 36-39.
-
Yau, S., R.H. Kwon, J.S. Rogers and D. Wu, 2011. Financial and operational decisions in the electricity sector: Contract portfolio optimization with the conditional value-at-risk criterion. Int. J. Prod. Econ., 134: 67-77.
CrossRef
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
|
|
|
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
|
Information |
|
|
|
Sales & Services |
|
|
|