A Real Options Analysis model for generation expansion planning under uncertain demand
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2023
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Abstract
Generation expansion planning is finding an optimal solution for installing new generation units with technical and financial limits. This study proposes a Real Options Analysis (ROA) model for evaluating a generation system expansion plan where the electricity demand fluctuates with volatility. We construct a binomial lattice to map the demand following a geometric Brownian motion (GBM) process. We obtain the Locational Marginal Pricing (LMP) at buses representing communities from an Optimal Power Flow (OPF) problem following Kirchhoff’s laws. Subsequently, we re-solve the OPF problem with additional generation capacity and attain LMPs associated with the expanded electrical network. The difference between these two LMPs is the benefit provided by the generation expansion. Considering generation expansion as a real option, we construct the option value tree for the economic valuation and demonstrate how the value of this option can be obtained at the initial node. A large option value expresses a substantial need for added generation capacity. This framework can detect necessary expansions along with their optimal timing. This decision-making tool is based on LMP differences, so a valuable expansion option reduces system congestion. We illustrate the key features of this model via a numerical example and present managerial insights with economic implications.
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This article is published as Nur, Gazi Nazia, Cameron MacKenzie, and Kyung Jo Min. "A Real Options Analysis model for generation expansion planning under uncertain demand." Decision Analytics Journal 8 (2023): 100263. doi:10.1016/j.dajour.2023.100263. © 2023 The Authors. Posted with permission.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ ).
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ ).