Full Title: cnMAE: The Right Metric for Evaluating Solar Forecasts
Author(s): Amperon
Publisher(s): Amperon
Publication Date: July 1, 2024
Full Text: Download Resource
Description (excerpt):
The utility industry has several conventional metrics for assessing predictive error in load forecasting. But none of them are the right fit for the unique characteristics of solar and solar forecasting. Amperon proposes the industry standardize around a new metric, cnMAE, to overcome the current limitations.
With increasing number of solar photovoltaic power plants coming online, solar forecasting is becoming more important for many players within the power and utility industry. With these growing use cases, it’s just as important to understand how accurate your forecasts are. However, any forecast is going to have a margin of predictive error.
The utility industry has several conventional metrics for assessing predictive error in load forecasting. But none of them are the right fit for the unique characteristics of solar and solar forecasting.
In this paper, Amperon experts:
– Evaluate several conventional metrics for assessing predictive error in load forecasting.
– Introduce cnMAE as the better alternative.
– Provides cnMAE comparisons and seasonal context.