Estimating the Option Value of Grid-Scale Battery Systems to Distribution Network Service Providers

Grid-scale energy storage systems} (ESS) have been widely recognized as a technically viable alternative to network augmentation in integrating growing renewable penetration in distribution networks. However, it is challenging to determine efficient and well-timed investment in the grid-scale ESS, considering battery schedules and future uncertainties. Within this context, we develop a methodology that explicitly (i) incorporates ESS schedules within Monte Carlo power flow simulations, and (ii) determine the optimal investment strategy using real options valuation (ROV). Specifically, we develop a mixed integer quadratic programming to determine the optimal size and schedules of a grid-scale ESS in an Australian distribution network. The benefits from battery operations to the network are quantitatively incorporated in the ROV to capture the value of managerial flexibility, and hence the optimal investment strategy. Driven by the declining battery cost, the results suggest to delay the investment to a later year to maximize the investment value.