Probability‐based capacity factor in uncertainty analysis of electricity cost for individual wind projects: A novel approach

Abstract

The Levelized Cost of Electricity (LCOE) is a widely used indicator to assess the electricity cost of wind energy. The probabilistic approach and Monte Carlo technique are commonly used to capture the uncertainty of input variables in the LCOE calculation at the country level. However, a simple assumption for the range value of capacity factor (CF), a main input variable in the LCOE calculation, is inappropriate for analyzing an individual wind project. To apply the probabilistic approach in the assessment of electricity cost for individual wind projects, the study develops a new approach for estimating the CF distribution for a specific project. We focus on simulating the CF distribution for a specific wind farm based on the historical CF values computed from historical wind speed at the site. In comparison to traditional approaches, the proposed method provides a reliable range of capacity factor values and reduces the uncertainty in estimating energy generation by half for four example projects. As a result, the generated LCOE distribution is relatively closer to the real value of the projects, enhancing more realistic decisions for both project developers and policymakers.