Operationally Perfect Solar Power Forecasts: A Scalable Strategy to Lowest-Cost Firm Solar Power Generation

摘要

The SUNY solar irradiance forecast model is implemented in the SolarAnywhere platform. In this article, we evaluate its latest version and present a fully independent validation for climatically distinct individual US locations as well as one extended region. In addition to standard performance metrics such as mean absolute error or forecast skill, we apply a new operational metric that quantifies the lowest cost of operationally achieving perfect forecasts. This cost represents the amount of solar production curtailment and backup storage necessary to correct all over/under-prediction situations. This perfect forecast metric applies a recently developed algorithm to optimally transform intermittent renewable power generation into firm power generation with the optimal - least-cost – amount of curtailment and energy storage. We discuss how perfect forecast logistics can gradually evolve and scale up into firm solar power generation logistics, with the objective of cost-optimally displacing conventional [dispatchable] power generation.