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<p>This study proposes an integrated real options framework for photovoltaic (PV) investments in South Korea, jointly optimizing investment timing and the choice between a Spot pathway and a power purchase agreement (PPA) pathway. Rising SMP-REC revenue volatility under the Korean Renewable Portfolio Standard (RPS) and growing corporate demand necessitate incorporating PPA participation into investment decisions. The decision is formulated as a finite-horizon optimal stopping problem with three actions: Wait, Invest-Spot, Invest-PPA. Deterministic trajectories are constructed for PV-weighted SMP and REC prices using market simulations and fundamentals models. The PPA strike price is anchored to RPS fixed-price auction outcomes and projected via an LCOE-linked learning trend with lognormal dispersion. Pathway lifetime values are evaluated as the net present value of discounted after-tax cash flows using scheme-specific discount rates (WACC) to reflect differences in bankability. Optimal exercise policies are obtained via a two-dimensional least squares Monte Carlo (2D-LSMC) algorithm with tensor-product basis functions. A case study across four capacity scenarios (99 kW-20 MW) finds investment concentrated in the late 2020s and shows that adding the PPA option improves valuation and investment stability relative to a Spot-only benchmark.</p>

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An Integrated 2D-LSMC Real Options Method for Solar PV Facility Planning: Optimizing Timing and Spot-PPA Selection

  • 期刊论文

  • 发表日期：

    2026年5月11日

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  • DongKwan Kim,
  • Hanung Nam,
  • Hwanuk Yu,
  • Sung-Kwan Joo,
  • Young-Min Wi

摘要

This study proposes an integrated real options framework for photovoltaic (PV) investments in South Korea, jointly optimizing investment timing and the choice between a Spot pathway and a power purchase agreement (PPA) pathway. Rising SMP-REC revenue volatility under the Korean Renewable Portfolio Standard (RPS) and growing corporate demand necessitate incorporating PPA participation into investment decisions. The decision is formulated as a finite-horizon optimal stopping problem with three actions: Wait, Invest-Spot, Invest-PPA. Deterministic trajectories are constructed for PV-weighted SMP and REC prices using market simulations and fundamentals models. The PPA strike price is anchored to RPS fixed-price auction outcomes and projected via an LCOE-linked learning trend with lognormal dispersion. Pathway lifetime values are evaluated as the net present value of discounted after-tax cash flows using scheme-specific discount rates (WACC) to reflect differences in bankability. Optimal exercise policies are obtained via a two-dimensional least squares Monte Carlo (2D-LSMC) algorithm with tensor-product basis functions. A case study across four capacity scenarios (99 kW-20 MW) finds investment concentrated in the late 2020s and shows that adding the PPA option improves valuation and investment stability relative to a Spot-only benchmark.