{"title":"Potential root mean square error skill score","authors":"Martin János Mayer, Dazhi Yang","doi":"10.1063/5.0187044","DOIUrl":null,"url":null,"abstract":"Consistency, in a narrow sense, denotes the alignment between the forecast-optimization strategy and the verification directive. The current recommended deterministic solar forecast verification practice is to report the skill score based on root mean square error (RMSE), which would violate the notion of consistency if the forecasts are optimized under another strategy such as minimizing the mean absolute error (MAE). This paper overcomes such difficulty by proposing a so-called “potential RMSE skill score,” which depends only on (1) the cross-correlation between forecasts and observations and (2) the autocorrelation of observations. While greatly simplifying the calculation, the new skill score does not discriminate inconsistent forecasts as much, e.g., even MAE-optimized forecasts can attain a high RMSE skill score.","PeriodicalId":16953,"journal":{"name":"Journal of Renewable and Sustainable Energy","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Renewable and Sustainable Energy","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1063/5.0187044","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Consistency, in a narrow sense, denotes the alignment between the forecast-optimization strategy and the verification directive. The current recommended deterministic solar forecast verification practice is to report the skill score based on root mean square error (RMSE), which would violate the notion of consistency if the forecasts are optimized under another strategy such as minimizing the mean absolute error (MAE). This paper overcomes such difficulty by proposing a so-called “potential RMSE skill score,” which depends only on (1) the cross-correlation between forecasts and observations and (2) the autocorrelation of observations. While greatly simplifying the calculation, the new skill score does not discriminate inconsistent forecasts as much, e.g., even MAE-optimized forecasts can attain a high RMSE skill score.
期刊介绍:
The Journal of Renewable and Sustainable Energy (JRSE) is an interdisciplinary, peer-reviewed journal covering all areas of renewable and sustainable energy relevant to the physical science and engineering communities. The interdisciplinary approach of the publication ensures that the editors draw from researchers worldwide in a diverse range of fields.
Topics covered include:
Renewable energy economics and policy
Renewable energy resource assessment
Solar energy: photovoltaics, solar thermal energy, solar energy for fuels
Wind energy: wind farms, rotors and blades, on- and offshore wind conditions, aerodynamics, fluid dynamics
Bioenergy: biofuels, biomass conversion, artificial photosynthesis
Distributed energy generation: rooftop PV, distributed fuel cells, distributed wind, micro-hydrogen power generation
Power distribution & systems modeling: power electronics and controls, smart grid
Energy efficient buildings: smart windows, PV, wind, power management
Energy conversion: flexoelectric, piezoelectric, thermoelectric, other technologies
Energy storage: batteries, supercapacitors, hydrogen storage, other fuels
Fuel cells: proton exchange membrane cells, solid oxide cells, hybrid fuel cells, other
Marine and hydroelectric energy: dams, tides, waves, other
Transportation: alternative vehicle technologies, plug-in technologies, other
Geothermal energy