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An interval-based stochastic dominance approach for decision making in forward contracts of electricity market

Author

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  • Jamshidi, Movahed
  • Kebriaei, Hamed
  • Sheikh-El-Eslami, Mohammad-Kazem

Abstract

virtually, all decisions in financial markets are made in the presence of uncertainty. Stochastic dominance is a well-known concept that is broadly implemented for decision making under uncertainty. Thanks to the advantages of this approach, a decision maker is able to exploit available information related to uncertainties with stochastic nature. In this paper, to cope with the uncertainties in the procedure of decision making for forward contracts in an electricity market, a modified stochastic dominance approach is proposed. In the suggested framework, instead of considering a single value for desirable goal in each scenario of benchmark, a profit interval has been allocated to reflect the economic targets of decision maker. In the next step, the allocated profit interval is utilized for decision making problem in the stochastic dominance framework. In order to find the optimal profit profile in such a setting, a two level optimization structure is suggested. To this end, at the lower level of optimization, three different methods namely the prospect stochastic dominance, conditional value at risk (CvaR) and hypothesis testing are applied to find the optimal profit profiles for a number of benchmarks, those are stochastically generated in an interval around a pre-specified profit benchmark. In the upper level, the optimal profit profile is computed by using the Mean-CvaR method. To show the practical aspects and generalizability of our proposed approach, the methods are applied to two different cases, including a retailer and an electricity producer’s decision making problems to determine their involvement in the futures market by maximizing their expected profit over a given planning horizon, while controlling the risk of profit volatility in the electricity market, raised from the uncertainties in the spot market price and the consumer demand. The performance of suggested framework is evaluated through simulation results and relevant conclusions are drawn.

Suggested Citation

  • Jamshidi, Movahed & Kebriaei, Hamed & Sheikh-El-Eslami, Mohammad-Kazem, 2018. "An interval-based stochastic dominance approach for decision making in forward contracts of electricity market," Energy, Elsevier, vol. 158(C), pages 383-395.
    • Handle: RePEc:eee:energy:v:158:y:2018:i:c:p:383-395
    DOI: 10.1016/j.energy.2018.06.050
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    References listed on IDEAS

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    1. Escudero, Laureano F. & Garín, María Araceli & Merino, María & Pérez, Gloria, 2016. "On time stochastic dominance induced by mixed integer-linear recourse in multistage stochastic programs," European Journal of Operational Research, Elsevier, vol. 249(1), pages 164-176.
    2. Tajeddini, Mohammad Amin & Rahimi-Kian, Ashkan & Soroudi, Alireza, 2014. "Risk averse optimal operation of a virtual power plant using two stage stochastic programming," Energy, Elsevier, vol. 73(C), pages 958-967.
    3. Conejo, Antonio J. & Contreras, Javier & Espinola, Rosa & Plazas, Miguel A., 2005. "Forecasting electricity prices for a day-ahead pool-based electric energy market," International Journal of Forecasting, Elsevier, vol. 21(3), pages 435-462.
    4. Charwand, Mansour & Gitizadeh, Mohsen & Siano, Pierluigi, 2017. "A new active portfolio risk management for an electricity retailer based on a drawdown risk preference," Energy, Elsevier, vol. 118(C), pages 387-398.
    5. Dentcheva, Darinka & Martinez, Gabriela, 2012. "Two-stage stochastic optimization problems with stochastic ordering constraints on the recourse," European Journal of Operational Research, Elsevier, vol. 219(1), pages 1-8.
    6. Maria Teresa Vespucci & Marida Bertocchi & Laureano F. Escudero & Stefano Zigrino, 2013. "A risk averse stochastic optimization model for power generation capacity expansion," Working Papers (2013-) 1305_qum, University of Bergamo, Department of Management, Economics and Quantitative Methods.
    7. Feng, Zhen-Hua & Wei, Yi-Ming & Wang, Kai, 2012. "Estimating risk for the carbon market via extreme value theory: An empirical analysis of the EU ETS," Applied Energy, Elsevier, vol. 99(C), pages 97-108.
    8. Alipour, Manijeh & Mohammadi-Ivatloo, Behnam & Zare, Kazem, 2014. "Stochastic risk-constrained short-term scheduling of industrial cogeneration systems in the presence of demand response programs," Applied Energy, Elsevier, vol. 136(C), pages 393-404.
    9. Jammazi, Rania & Reboredo, Juan C., 2016. "Dependence and risk management in oil and stock markets. A wavelet-copula analysis," Energy, Elsevier, vol. 107(C), pages 866-888.
    10. Benjamin Armbruster & James Luedtke, 2015. "Models and formulations for multivariate dominance-constrained stochastic programs," IISE Transactions, Taylor & Francis Journals, vol. 47(1), pages 1-14, January.
    11. Kajal Chatterjee & Samarjit Kar, 2016. "Multi-criteria analysis of supply chain risk management using interval valued fuzzy TOPSIS," OPSEARCH, Springer;Operational Research Society of India, vol. 53(3), pages 474-499, September.
    12. Deng, Shi-Jie & Xu, Li, 2009. "Mean-risk efficient portfolio analysis of demand response and supply resources," Energy, Elsevier, vol. 34(10), pages 1523-1529.
    13. Levy, Haim & Wiener, Zvi, 1998. "Stochastic Dominance and Prospect Dominance with Subjective Weighting Functions," Journal of Risk and Uncertainty, Springer, vol. 16(2), pages 147-163, May-June.
    14. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    15. Miguel Carrión & Uwe Gotzes & Rüdiger Schultz, 2009. "Risk aversion for an electricity retailer with second-order stochastic dominance constraints," Computational Management Science, Springer, vol. 6(2), pages 233-250, May.
    16. Jitka Dupačová & Miloš Kopa, 2012. "Robustness in stochastic programs with risk constraints," Annals of Operations Research, Springer, vol. 200(1), pages 55-74, November.
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