Skip to main content

An Optimal Asset Allocation Strategy for Suppliers Paying Carbon Tax in the Competitive Electricity Market

Abstract

The escalating energy demand across the globe has intensified the electricity production. Owing to the unavailability of the reliable techniques for electricity storage for a long duration, it is consumed immediately after its production. Therefore, electricity markets can’t be handled like the conventional stock markets. Power companies are facing immense price and delivery risks owing to the increasing competition in the electricity markets. As a result, risk management is the fundamental concern to be addressed in order to achieve the optimum profit targets. Consequently, the power generation organizations need to allocate their generation in bilateral contracts and spot market. For this purpose, an optimal theory of portfolio selection is proposed in this study for electricity generation by forming a reliable prototype and applying the proposed scheme to obtain the suitable outcomes. The Paris Accord on environmental safety from carbon dioxide and NOx gases is especially considered during the modeling of the proposed technique. The credibility of the proposed scheme is validated by using the real-time market data from the PJM market. Various risk-return tradeoffs are implemented, and their corresponding solutions are acquired for portfolio optimization as corroborated by the results. The suggested technique is found reliable and adequate for the carbon tax paying suppliers around the world for allocating their respective generation based on the demand of the consumers.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

References

  1. Lee KH (2011) Integrating carbon footprint into supply chain management: the case of Hyundai Motor Company (HMC) in the automobile industry. J Clean Prod 19(11):1216–1223

    Article  Google Scholar 

  2. Al-mulali U, Sab CNBC (2012) The impact of energy consumption and CO2 emission on the economic growth and financial development in the Sub Saharan African countries. Energy 39(1):180–186

    Article  Google Scholar 

  3. Wang K, Yu S, Zhang W (2013) China’s regional energy and environmental efficiency: a DEA window analysis based dynamic evaluation. Math Comput Model 58(5–6):1117–1127

    Article  Google Scholar 

  4. Wang Y, Zhu Q, Geng Y (2013) Trajectory and driving factors for GHG emissions in the Chinese cement industry. J Clean Prod 53:252–260

    Article  Google Scholar 

  5. Grubb M (2004) Kyoto and the future of international climate change responses: from here to where? Int Rev Environ Strateg 5(1):15–38

    Google Scholar 

  6. CCSA (2016) What is CCS?—the carbon capture and storage association (CCSA). CCSA, London

    Google Scholar 

  7. Gibbins J, Chalmers H (2008) Carbon capture and storage. Energy Policy 36(12):4317–4322

    Article  Google Scholar 

  8. Chen Y, Tseng CL (2011) Inducing clean technology in the electricity sector: tradable permits or carbon tax policies? Energy J 32(3):149–174

    Article  Google Scholar 

  9. Palmer K, Paul A, Keyes A (2018) Changing baselines, shifting margins: how predicted impacts of pricing carbon in the electricity sector have evolved over time. Energy Econ 73:371–379

    Article  Google Scholar 

  10. W B Group (2018) State and trends of carbon pricing 2018. https://openknowledge.worldbank.org/bitstream/handle/10986/29687/9781464812927.pdf?sequence=5&isAllowed=y. Accessed 13 Apr 2018

  11. Alton T et al (2014) Introducing carbon taxes in South Africa. Appl Energy 116:344–354

    Article  Google Scholar 

  12. Mathur A, Morris AC (2014) Distributional effects of a carbon tax in broader US fiscal reform. Energy Policy 66:326–334

    Article  Google Scholar 

  13. Massetti E (2011) Carbon tax scenarios for China and India: exploring politically feasible mitigation goals. Int Environ Agreem Polit Law Econ 11(3):209–227

    Google Scholar 

  14. Finkenrath M (2011) Cost and performance of carbon dioxide capture from power generation. In: IEA energy papers, pp 51–51

  15. Finkenrath M (2012) Carbon dioxide capture from power generation—status of cost and performance. Chem Eng Technol 35(3):482–488

    Article  Google Scholar 

  16. Gerdes K, Stevens R, Fout T, Fisher J, Hackett G, Shelton W (2014) Current and future power generation technologies: pathways to reducing the cost of carbon capture for coal-fueled power plants. Energy Procedia 63:7541–7557

    Article  Google Scholar 

  17. Liu M, Wu FF (2006) Managing price risk in a multimarket environment. IEEE Trans Power Syst 21(4):1512–1519

    Article  Google Scholar 

  18. Bjorgan R, Liu CC, Lawarree J (1999) Financial risk management in a competitive electricity market. IEEE Trans Power Syst 14(4):1285–1291

    Article  Google Scholar 

  19. Gökgöz F, Atmaca ME (2012) Financial optimization in the Turkish electricity market: Markowitz’s mean-variance approach. Renew Sustain Energy Rev 16(1):357–368

    Article  Google Scholar 

  20. Statman M (1987) How many stocks make a diversified portfolio? J Financ Quant Anal 22:353–363

    Article  Google Scholar 

  21. Markowitz HM (1952) Portfolio selection. J Finance 7(60):77–91

    Google Scholar 

  22. Shahidehpour M, Yamin H, Li Z (2002) Market operations in electric power systems: forecasting, scheduling, and risk management. Wiley, Hoboken, p 531

    Book  Google Scholar 

  23. Gedra TW (1994) Optional forward contracts for electric power markets. IEEE Trans Power Syst 9(4):1766–1773

    Article  Google Scholar 

  24. Menniti D, Musmanno R, Scordino N, Sorrentino N, Violi A (2007) Managing price risk while bidding in a multimarket environment. In: 2007 IEEE power engineering society general meeting. IEEE, pp 1–10

  25. Liu M, Wu FF (2007) Portfolio optimization in electricity markets. Electric Power Syst Res 77(8):1000–1009

    Article  Google Scholar 

  26. Siddiqi SN (2000) Project valuation and power portfolio management in a competitive market. IEEE Trans Power Syst 15:116–121

    Article  Google Scholar 

  27. Xu J, Luh PB, White FB, Ni E, Kasiviswanathan K (2006) Power portfolio optimization in deregulated electricity markets with risk management. IEEE Trans Power Syst 21:1653–1662

    Article  Google Scholar 

  28. Shrestha GB, Pokharel BK, Lie TT, Fleten SE (2005) Medium term power planning with bilateral contracts. IEEE Trans Power Syst 20:627–633

    Article  Google Scholar 

  29. Collins RA (2002) The economics of electricity hedging and a proposed modification for the futures contract for electricity. IEEE Trans Power Syst 17(1):100–107

    Article  Google Scholar 

  30. Bessembinder H, Lemmon ML (2002) Equilibrium pricing and optimal hedging in electricity forward markets. J Finance 57:1347–1382

    Article  Google Scholar 

  31. Gökgöz F, Atmaca M (2013) Optimal asset allocation in the Turkish electricity market: down-side vs semi-variance risk approach. In: Proceedings of the World Congress on …, vol 1, pp 3–8

  32. Vehviläinen I, Keppo J (2003) Managing electricity market price risk. Eur J Oper Res 145(1):136–147

    MATH  Article  Google Scholar 

  33. Campo RA (2002) Probabilistic optimality in long-term energy sales. IEEE Trans Power Syst 17(2):237–242

    Article  Google Scholar 

  34. Mo B, Gjelsvik A, Grundt A (2001) Integrated risk management of hydro power scheduling and contract management. IEEE Trans Power Syst 16(2):216–221

    Article  Google Scholar 

  35. Liu M, Wu FF, Ni Y (2003) Market allocation between bilateral contracts and spot market without financial transmission rights. In: 2003 IEEE power engineering society general meeting (IEEE Cat No 03CH37491), vol 2. IEEE, pp 1007–1011

  36. Lai TY (1991) Portfolio selection with skewness: a multiple-objective approach. Rev Quant Finance Account 1:293

    Article  Google Scholar 

  37. Liu S, Wang SY, Qiu W (2003) Mean-variance-skewness model for portfolio selection with transaction costs. Int J Syst Sci 34:255–262

    MathSciNet  MATH  Article  Google Scholar 

  38. Eydeland A, Wolyniec K (2003) Energy and power risk management. Phys A Stat Mech Appl 285:127–134

    Google Scholar 

  39. Longstaff FA, Wang AW (2004) Electricity forward prices: a high-frequency empirical analysis. J Financ 59(4):1877–1900

    Article  Google Scholar 

  40. Deng SJ, Johnson B, Sogomonian A (2001) Exotic electricity options and the valuation of electricity generation and transmission assets. Decis Support Syst 30:383–392

    Article  Google Scholar 

  41. Chung-Li T, Barz G (2002) Short-term generation asset valuation: a real options approach. Oper Res 50:297–310

    MathSciNet  MATH  Article  Google Scholar 

  42. Schmutz A, Gnansounou E, Sarlos G (2002) Economic performance of contracts in electricity markets: a fuzzy and multiple criteria approach. IEEE Trans Power Syst 17(4):966–973

    Article  Google Scholar 

  43. Fan W, Guan X, Zhai Q (2002) A new method for unit commitment with ramping constraints. Electric Power Syst Res 62:215–224

    Article  Google Scholar 

  44. Zhai Q, Guan X, Cui J (2002) Unit commitment with identical units: successive subproblem solving method based on Lagrangian relaxation. IEEE Trans Power Syst 17:1250–1257

    Article  Google Scholar 

  45. Deng SJ, Xu L (2009) Mean-risk efficient portfolio analysis of demand response and supply resources. Energy 34(10):1523–1529

    Article  Google Scholar 

  46. Olsen DJ, Dvorkin Y, Fernandez-Blanco R, Ortega-Vazquez MA (2018) Optimal carbon taxes for emissions targets in the electricity sector. IEEE Trans Power Syst 33:1

    Article  Google Scholar 

  47. Tütüncü RH, Koenig M (2004) Robust asset allocation. Ann Oper Res 132:157–187

    MathSciNet  MATH  Article  Google Scholar 

  48. Bodie Z, Kane A, Marcus AJ (2005) Investments, 6th edn. McGraw-Hill, New York

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Waqas Ahmad Wattoo.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wattoo, W.A., Kaloi, G.S., Yousif, M. et al. An Optimal Asset Allocation Strategy for Suppliers Paying Carbon Tax in the Competitive Electricity Market. J. Electr. Eng. Technol. 15, 193–203 (2020). https://doi.org/10.1007/s42835-019-00318-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42835-019-00318-3

Keywords

  • Asset allocation
  • Carbon tax
  • Portfolio optimization
  • Power market
  • Risk management