Papers Solar Irradiance Forecasting
“Solar Irradiance Forecasting” 태그가 달린 논문 31편 · 필터 해제
A Controlled Visual-Backbone Benchmark for Multimodal Short-Term Solar Irradiance Forecasting
Sky-image irradiance studies often compare forecasting systems in which the image encoder, temporal model, fusion block, target definition, and training recipe all change together. We use a narrower protocol: the multimo…
Solar Irradiance ForecastingStep-adaptive multimodal fusion network with multi-scale cloud feature learning for ultra-short-term solar irradiance forecasting
Ultra-short-term solar irradiance prediction is critical for photovoltaic system dispatch and power grid stability. Existing approaches suffer from three key shortcomings: single time-series models cannot capture the spa…
Solar Irradiance ForecastingBarrier-enforced multi-objective optimization for direct point and sharp interval forecasting
This paper proposes a multi-step probabilistic forecasting framework using a single neural-network based model to generate simultaneous point and interval forecasts. Our approach ensures non-crossing prediction intervals…
Solar Irradiance ForecastingOutperforming Self-Attention Mechanisms in Solar Irradiance Forecasting via Physics-Guided Neural Networks
Accurate Global Horizontal Irradiance (GHI) forecasting is critical for grid stability, particularly in arid regions characterized by rapid aerosol fluctuations. While recent trends favor computationally expensive Transf…
Solar Irradiance ForecastingPhysics-Informed State Space Models for Reliable Solar Irradiance Forecasting in Off-Grid Systems
The stable operation of off-grid photovoltaic systems requires accurate, computationally efficient solar forecasting. Contemporary deep learning models often suffer from massive computational overhead and physical blindn…
Solar Irradiance ForecastingIntegrating Weather Foundation Model and Satellite to Enable Fine-Grained Solar Irradiance Forecasting
Accurate day-ahead solar irradiance forecasting is essential for integrating solar energy into the power grid. However, it remains challenging due to the pronounced diurnal cycle and inherently complex cloud dynamics. Cu…
Solar Irradiance ForecastingSolarCrossFormer: Improving day-ahead Solar Irradiance Forecasting by Integrating Satellite Imagery and Ground Sensors
Accurate day-ahead forecasts of solar irradiance are required for the large-scale integration of solar photovoltaic (PV) systems into the power grid. However, current forecasting solutions lack the temporal and spatial r…
Solar Irradiance ForecastingSolarSeer: Ultrafast and accurate 24-hour solar irradiance forecasts outperforming numerical weather prediction across the USA
Accurate 24-hour solar irradiance forecasting is essential for the safe and economic operation of solar photovoltaic systems. Traditional numerical weather prediction (NWP) models represent the state-of-the-art in foreca…
Solar Irradiance ForecastingNICE^k Metrics: Unified and Multidimensional Framework for Evaluating Deterministic Solar Forecasting Accuracy
Accurate solar energy output prediction is key for integrating renewables into grids, maintaining stability, and improving energy management. However, standard error metrics such as Root Mean Squared Error (RMSE), Mean A…
Solar Irradiance ForecastingSolar Multimodal Transformer: Intraday Solar Irradiance Predictor using Public Cameras and Time Series
Accurate intraday solar irradiance forecasting is crucial for optimizing dispatch planning and electricity trading. For this purpose, we introduce a novel and effective approach that includes three distinguishing compone…
BenchmarkingSolar Irradiance ForecastingTime SeriesSPIRIT: Short-term Prediction of solar IRradIance for zero-shot Transfer learning using Foundation Models
Traditional solar forecasting models are based on several years of site-specific historical irradiance data, often spanning five or more years, which are unavailable for newer photovoltaic farms. As renewable energy is h…
Solar Irradiance ForecastingTransfer LearningLarge width penalization for neural network-based prediction interval estimation
Forecasting accuracy in highly uncertain environments is challenging due to the stochastic nature of systems. Deterministic forecasting provides only point estimates and cannot capture potential outcomes. Therefore, prob…
Solar Irradiance ForecastingSatellite Sunroof: High-res Digital Surface Models and Roof Segmentation for Global Solar Mapping
The transition to renewable energy, particularly solar, is key to mitigating climate change. Google's Solar API aids this transition by estimating solar potential from aerial imagery, but its impact is constrained by geo…
3D Surface GenerationEarth ObservationInstance SegmentationSegmentation+2Short-Term Solar Irradiance Forecasting Under Data Transmission Constraints
We report a data-parsimonious machine learning model for short-term forecasting of solar irradiance. The model inputs include sky camera images that are reduced to scalar features to meet data transmission constraints. T…
Solar Irradiance ForecastingInput Convex Lipschitz RNN: A Fast and Robust Approach for Engineering Tasks
Computational efficiency and robustness are essential in process modeling, optimization, and control for real-world engineering applications. While neural network-based approaches have gained significant attention in rec…
Chemical ProcessComputational EfficiencyModel Predictive ControlNon-Adversarial Robustness+1Comparative Analysis of Machine Learning Algorithms for Solar Irradiance Forecasting in Smart Grids
The increasing global demand for clean and environmentally friendly energy resources has caused increased interest in harnessing solar power through photovoltaic (PV) systems for smart grids and homes. However, the inher…
Bayesian Optimizationenergy tradingfeature selectionManagement+1Improving day-ahead Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context
Solar power harbors immense potential in mitigating climate change by substantially reducing CO$_{2}$ emissions. Nonetheless, the inherent variability of solar irradiance poses a significant challenge for seamlessly inte…
Solar Irradiance ForecastingTime SeriesTime Series ForecastingZero-shot GeneralizationSolar Irradiance Anticipative Transformer
This paper proposes an anticipative transformer-based model for short-term solar irradiance forecasting. Given a sequence of sky images, our proposed vision transformer encodes features of consecutive images, feeding int…
DecoderSolar Irradiance ForecastingCombined Machine Learning and Physics-Based Forecaster for Intra-day and 1-Week Ahead Solar Irradiance Forecasting Under Variable Weather Conditions
Power systems engineers are actively developing larger power plants out of photovoltaics imposing some major challenges which include its intermittent power generation and its poor dispatchability. The issue is that PV i…
Ensemble LearningSolar Irradiance ForecastingLocal-Global Methods for Generalised Solar Irradiance Forecasting
As the use of solar power increases, having accurate and timely forecasts will be essential for smooth grid operators. There are many proposed methods for forecasting solar irradiance / solar power production. However, m…
Solar Irradiance ForecastingTime Series Analysis