Reproducing solar curtailment with Fourier analysis using Japan dataset

Abstract

Curtailment of variable renewable energy increases the Levelized Cost of Energy (LCOE), which is the tool often used to compare its profitability against traditional energy sources. Recently, the Kyushu Region of Japan had to curtail some of its solar production to meet energy balance. As many countries increase their solar energy production, curtailment will be inevitable. It is therefore important to develop methodologies to calculate it. In the case of Japan, curtailment can easily be estimated using hourly data. However, such data is unavailable in other countries. In this study, a methodology to reproduce curtailment using known periodicity and statistical data is presented. Insights were initially generated by simulating future curtailment scenarios of Kyushu to extract the factors that affect curtailment. Fourier analysis was used to identify the periodicity of demand and solar production. The Fourier representation was simplified using the identified factors. Along with statistical data, the demand and solar data were approximated and the curtailment was reproduced. Results show that curtailment can be closely reproduced using the proposed methodology on a yearly and monthly level. Further research is necessary to test the methodology for other conditions like having different climate, varying daily fluctuations, and other human-related fluctuations.