An optimal sequential investment decision model for generation-side energy storage projects in China considering policy uncertainty

Abstract

Energy storage systems (ESS) are crucial for addressing the intermittent nature of renewable energy, and improving the flexibility of power systems. However, the uncertainties in the investment decision process pose a challenge for investment evaluation of ESS. This study develops a sequential investment decision model for ESS projects based on real options, aiming to derive the optimal investment timing and value of the project under electricity price and subsidy policy uncertainties. Considering the policy uncertainty caused by the possible retraction or provision of subsidies, sequential investments under four subsidy policies of stable, retraction, provision, and transformation are analyzed separately. The model is empirically and simulatively analyzed using a generation-side ESS project in Qinghai Province, China, as an example. The results show that: First, the sequential investment strategy promotes earlier project deployment compared to the lumpy investment strategy. Second, stochastic provision of subsidies incentivizes investment, but stochastic retraction of subsidies is a greater disincentive to investment, whereas stable subsidy policies provide the best incentives. However, local subsidies still need to increase to 0.15 yuan/kWh to trigger investment. Third, under subsidy recovery uncertainty, excessive subsidy levels discourage investment; meanwhile, under subsidy provision uncertainty, low subsidy levels become almost incentive-less.