Real option-based network investment assessment considering energy storage systems under long-term demand uncertainties

Shuang Cheng, Chenghong Gu, Ignacio Hernando-Gil, Shuangqi Li, Furong Li

Research output: Contribution to journalArticlepeer-review


This paper proposes a novel real option (RO)-based network investment assessment method to quantify the flexibility value of battery energy storage systems (BESS) in distribution network planning (DNP). It applied geometric Brownian motion (GBM) to simulate the long-term load growth uncertainty. Compared with commonly used stochastic models (e.g. normal probability model) that assume a constant variance, it reflects the fact that from the point of prediction, uncertainty would increase as time elapses. Hence, it avoids the bias of traditional net present value (NPV) frameworks towards lumpy investments that cannot provide strategic flexibility relative to more flexible alternatives. It is for the first time to adopt the option pricing method to evaluate the flexibility value of distribution network planning strategies. To optimize the planning scheme, this paper compares the static NPVs and flexibility values of different investment strategies. A 33-bus system is used to verify the effectiveness of the formulated model. Results indicate that flexibility values of BESS are of utmost importance to DNP under demand growth uncertainties. It provides an analytical tool to quantify the flexibility of planning measures and evaluate the well-timed investment of BESS, thus supporting network operators to facilitate flexibility services and hedge risks from the negative impact of long-term uncertainty.

Original languageEnglish
Pages (from-to)2721-2934
Number of pages14
JournalIET Renewable Power Generation
Issue number13
Early online date12 Jul 2022
Publication statusPublished - 5 Oct 2022

Bibliographical note

The author(s) received no specific funding for this work.

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment


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