Abstract
To push the boundaries of self-sufficiency, local energy communities may rely on load demand forecasts to schedule energy usage ahead of time. In the perspective of selecting a forecasting method, this work explores goodness of a forecast from two sides: its quality, and its value. Traditionally, forecasting methods are ranked based on quality metrics such as the Mean Absolute Percentage Error (MAPE). This work additionally considers the value of a forecast, quantifying practical outcomes for local energy communities such as self-sufficiency, cost of electricity, and fairness. Our contribution is twofold: first in creating a broader framework to evaluate forecasting performance with regards to energy communities, and second, in highlighting the relationship between quality and value metrics for energy communities ranging from 2 to 95 participants. When selecting a forecasting method, our results show that simply relying on quality metrics is misleading. This paper illustrates with a study case, the clear difference in considering value metrics rather than quality metrics, and the potential impact on the design of a coordination platform for local energy communities.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal of Electrical Power & Energy Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.