A combined probabilistic framework to support investment appraisal under uncertainty in desalination projects: an application to Kuwait's water/energy nexus

Abstract

Quantifying uncertainty over technologies, costs, and prices that stem from site-specific conditions, technological particularities and future projections is an important element in the investment appraisal of desalination facilities. Yet, the majority of economic assessments in the field of desalination plants, so far, use deterministic estimation methods based on ‘best guess’ estimates and ceteris paribus sensitivity analyses. Aiming to fill this gap, this paper introduces a new approach towards comparing alternative technological options for desalination facilities under uncertainty based on the Levelized Cost of Water (LCOW). The proposed framework combines Monte Carlo simulations with scenario analysis and random-walk-based models to account for the cone of uncertainty of the LCOW. For purely illustrative purposes, five alternative combinations of desalination technologies and energy sources are examined in the State of Kuwait. The findings show that the proposed framework, although it cannot eliminate uncertainty, can assist decision-makers in managing it by framing the range of possible outcomes of the LCOW. In this way, it offers an insight into the accuracy of the estimates and allows the validation of the impact of risks and uncertainties against the acceptable tolerance level. Yet, several issues need to be addressed in future research.

Keywords

• desalination
• investment appraisal
• monte carlo simulation
• random walk models
• renewable energy