Evaluating Day-Ahead Solar Radiation Forecasts from ICON, GFS, and MeteoFrance Global NWP Models DOI
Alisher F. Narynbaev,

Vladislav A. Kremer,

Alexey Vaskov

et al.

Applied Solar Energy, Journal Year: 2024, Volume and Issue: 60(3), P. 491 - 500

Published: June 1, 2024

Language: Английский

Pairing ensemble numerical weather prediction with ensemble physical model chain for probabilistic photovoltaic power forecasting DOI Creative Commons
Martin János Mayer, Dazhi Yang

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 175, P. 113171 - 113171

Published: Jan. 18, 2023

Language: Английский

Citations

52
An archived dataset from the ECMWF Ensemble Prediction System for probabilistic solar power forecasting DOI
Wenting Wang, Dazhi Yang, Tao Hong

et al.

Solar Energy, Journal Year: 2022, Volume and Issue: 248, P. 64 - 75

Published: Nov. 14, 2022

Language: Английский

Citations

43
Comparing global and regional downscaled NWP models for irradiance and photovoltaic power forecasting: ECMWF versus AROME DOI Creative Commons
Martin János Mayer, Dazhi Yang, Balázs Szintai

et al.

Applied Energy, Journal Year: 2023, Volume and Issue: 352, P. 121958 - 121958

Published: Sept. 20, 2023

Inspecting the literature, much effort has been placed on verification of irradiance forecasts from numerical weather prediction (NWP) models, as such are thought to have profound implications photovoltaic (PV) power forecasts, which in turn affects grid operators' confidence integrating into electricity grid. However, perhaps due proprietary nature PV plants and lack access state-of-the-art NWP model output, only few had chance conduct head-to-head comparisons global mesoscale regional downscaled terms how their forecast inaccuracies propagate forecasts. In this regard, work presents a study, European Centre for Medium-Range Weather Forecasts' High-Resolution (HRES) Météo-France's Application Research Operations at Mesoscale (AROME) models thoroughly verified against ground-based measurements 32 research-grade radiometry stations 94 actual Hungary. A wide range techniques case studies concerning is herein considered, including variance ratio analysis, Murphy–Winkler decomposition, point-versus-areal verification, seasonal verification. Despite that results too numerous be summarized sentences, overarching observation exercise performance can used infer certain extent, contrasts conventional wisdom.

Language: Английский

Citations

24
A review of distributed solar forecasting with remote sensing and deep learning DOI
Yinghao Chu, Yiling Wang, Dazhi Yang

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2024, Volume and Issue: 198, P. 114391 - 114391

Published: April 25, 2024

Language: Английский

Citations

13
Probabilistic photovoltaic power forecasting using a calibrated ensemble of model chains DOI Creative Commons
Martin János Mayer, Dazhi Yang

Renewable and Sustainable Energy Reviews, Journal Year: 2022, Volume and Issue: 168, P. 112821 - 112821

Published: Aug. 12, 2022

Physical model chain is a step-by-step modeling framework for the conversion of irradiance to photovoltaic (PV) power. When fed with forecasts, it provides corresponding PV power forecasts. Despite its advantages, forecasting chains has yet receive attention that deserves. In several recent works, however, idea model-chain-based solar been formally modernized, though was restricted deterministic forecasting. this work, extended probability space, in that, calibrated ensemble used generate probabilistic Using two-year data from eight plants Hungary, alongside professional weather forecasts issued by Hungarian Meteorological Services, empirically shown raw model-chain tend be underdispered, but adequate post-processing able improve calibration and reduce continuous ranked score ensembles 20%. Given fact uncertainty quantification cardinal importance grid integration, extension thought beneficial.

Language: Английский

Citations

32
Predictability and forecast skill of solar irradiance over the contiguous United States DOI
Bai Liu, Dazhi Yang, Martin János Mayer

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 182, P. 113359 - 113359

Published: May 19, 2023

Language: Английский

Citations

15
Deep graph gated recurrent unit network-based spatial–temporal multi-task learning for intelligent information fusion of multiple sites with application in short-term spatial–temporal probabilistic forecast of photovoltaic power DOI
Mingliang Bai, Z. C. Zhou, Jingjing Li

et al.

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 240, P. 122072 - 122072

Published: Nov. 10, 2023

Language: Английский

Citations

15
On the use of sky images for intra-hour solar forecasting benchmarking: Comparison of indirect and direct approaches DOI
Guoping Ruan, Xiaoyang Chen, Eng Gee Lim

et al.

Solar Energy, Journal Year: 2024, Volume and Issue: 276, P. 112649 - 112649

Published: June 6, 2024

Language: Английский

Citations

6
Non-crossing Quantile Regression Neural Network as a Calibration Tool for Ensemble Weather Forecasts DOI
Mengmeng Song, Dazhi Yang, Sebastian Lerch

et al.

Advances in Atmospheric Sciences, Journal Year: 2024, Volume and Issue: 41(7), P. 1417 - 1437

Published: March 1, 2024

Language: Английский

Citations

5
Solar irradiance time series forecasting using auto-regressive and extreme learning methods: Influence of transfer learning and clustering DOI
Milan Despotović, Cyril Voyant, Luis Garcia-Gutierrez

et al.

Applied Energy, Journal Year: 2024, Volume and Issue: 365, P. 123215 - 123215

Published: April 17, 2024

Language: Английский

Citations

5