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Existing capacity-based network pricing uses discounted cash flows to calculate costs, unable to reflect the uncertainties and flexibilities in distribution networks. Such shortcoming could distort the cost-reflectivity of pricing signals, particularly those for renewables and flexible technologies, causing more constraints and curtailment issues in networks. This paper proposes a new pricing method, Incremental Cost Network Pricing based on Real Options (ICOC), which can reflect network user uncertainties on network investment by using real options. Under this concept, network operators can delay investment for a certain period by paying waiting cost based on options value until more information is available, thus avoiding non-reversible investment due to uncertainties. The options cost will be levied on network users as i) rewards if they can provide flexibilities to the system; or ii) waiting costs if they present uncertainties to the system. The reward or cost is determined by a binomial tree pricing under a risk-neutral condition, which is added onto asset present value as the total cost to be recovered. Such cost is allocated to network users based on their nodal incremental costs. The proposed method is demonstrated on a practical network with different users, i) uncertain, ii) flexible; iii) certain and nonflexible.

Original languageEnglish
Article number9732661
JournalIEEE Transactions on Power Systems
Issue number1
Early online date10 Mar 2022
Publication statusPublished - 31 Jan 2023

Bibliographical note

Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 52107090 and in part by the fellowship of China Postdoctoral Science Foundation under Grant 2021M690991. Paper no. TPWRS-01145-2021.


  • Costs
  • Energy storage
  • Investment
  • Load flow
  • Long-run Incremental Cost
  • Network Charges
  • Network investment
  • Pricing
  • Real Options
  • Resource management
  • Uncertainty

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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