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A new active portfolio risk management for an electricity retailer based on a drawdown risk preference

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  • Charwand, Mansour
  • Gitizadeh, Mohsen
  • Siano, Pierluigi

Abstract

This paper addresses the deciding under uncertainty of an electricity retailer in order to maximise its total expected rate of return. The developed methodology is based on the modelling of the stochastic evolution of zonal prices that seeks to manage a portfolio of different contracts. Retailer's load and the price at each zone are forecasted using the seasonal autoregressive integrated moving average (SARIMA) model and a clustering technique is used for scenario reduction. Supply sources include the pool, self-production facilities, forward and bilateral contracts. The risk of cost fluctuation due to uncertainties is explicitly modelled using the multi-scenario drawdown methodology. This risk function quantifies in aggregated format the frequency and magnitude of the portfolio drawdowns over planning horizon. In-sample and out-of-sample runs are performed for a portfolio allocation problem. Carried out experimental results on the basis of realistic data, show that imposing risk constraints improve the “real” performance of a portfolio management in out-of-sample runs.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:118:y:2017:i:c:p:387-398
    DOI: 10.1016/j.energy.2016.12.058
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    References listed on IDEAS

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    Cited by:

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    3. Uddin, Gazi Salah & Tang, Ou & Sahamkhadam, Maziar & Taghizadeh-Hesary, Farhad & Yahya, Muhammad & Cerin, Pontus & Rehme, Jakob, 2021. "Analysis of Forecasting Models in an Electricity Market under Volatility," ADBI Working Papers 1212, Asian Development Bank Institute.
    4. Charwand, Mansour & Gitizadeh, Mohsen, 2018. "Optimal TOU tariff design using robust intuitionistic fuzzy divergence based thresholding," Energy, Elsevier, vol. 147(C), pages 655-662.
    5. Khalili, Reza & Khaledi, Arian & Marzband, Mousa & Nematollahi, Amin Foroughi & Vahidi, Behrooz & Siano, Pierluigi, 2023. "Robust multi-objective optimization for the Iranian electricity market considering green hydrogen and analyzing the performance of different demand response programs," Applied Energy, Elsevier, vol. 334(C).
    6. 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.
    7. Deng, Tingting & Yan, Wenzhou & Nojavan, Sayyad & Jermsittiparsert, Kittisak, 2020. "Risk evaluation and retail electricity pricing using downside risk constraints method," Energy, Elsevier, vol. 192(C).
    8. Ioannis P. Panapakidis & Nikolaos Koltsaklis & Georgios C. Christoforidis, 2020. "A Novel Integrated Profit Maximization Model for Retailers under Varied Penetration Levels of Photovoltaic Systems," Energies, MDPI, vol. 14(1), pages 1-27, December.
    9. MansourLakouraj, Mohammad & Shahabi, Majid & Shafie-khah, Miadreza & Ghoreishi, Niloofar & Catalão, João P.S., 2020. "Optimal power management of dependent microgrid considering distribution market and unused power capacity," Energy, Elsevier, vol. 200(C).
    10. Li-Peng Shao & Jia-Jia Chen & Lu-Wen Pan & Zi-Juan Yang, 2022. "A Credibility Theory-Based Robust Optimization Model to Hedge Price Uncertainty of DSO with Multiple Transactions," Mathematics, MDPI, vol. 10(23), pages 1-20, November.
    11. Philipp M. Möller, 2018. "Drawdown Measures And Return Moments," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(07), pages 1-42, November.
    12. Juan M. Gómez & Yeny E. Rodríguez, 2022. "Multiperiod Portfolio of Energy Purchasing Strategies including Climate Scenarios," Energies, MDPI, vol. 15(9), pages 1-25, April.
    13. Korn, Olaf & Möller, Philipp M. & Schwehm, Christian, 2019. "Drawdown measures: Are they all the same?," CFR Working Papers 19-04, University of Cologne, Centre for Financial Research (CFR).
    14. Seyedhossein, Seyed Saeed & Moeini-Aghtaie, Moein, 2022. "Risk management framework of peer-to-peer electricity markets," Energy, Elsevier, vol. 261(PB).
    15. Tian, Xiaoge & Chen, Weiming & Hu, Jinglu, 2023. "Game-theoretic modeling of power supply chain coordination under demand variation in China: A case study of Guangdong Province," Energy, Elsevier, vol. 262(PA).

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