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Embedding the weather prediction errors (WPE) into the photovoltaic (PV) forecasting method using deep learning

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Outgoing claims: the papers this work cites, builds on, or argues with.

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inferredcites →https://doi.org/10.1016/j.solener.2014.11.017openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.solener.2015.03.006openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.solener.2016.06.073openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.solener.2018.02.069openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.solener.2019.04.025openalex-snapshot
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inferredcites →https://doi.org/10.1016/s0038-092x(87)80031-2openalex-snapshot
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inferredcites →https://doi.org/10.1109/access.2020.3029291openalex-snapshot
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inferredcites →https://doi.org/10.1109/jphotov.2015.2392938openalex-snapshot
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inferredcites →https://doi.org/10.1109/jphotov.2021.3138223openalex-snapshot
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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A Novel Anomaly Forecasting in Time‐Series Data: Feedback Connection between Forecasting and Detecting Algorithms with Applications to Power Systems
inferred← citeshttps://doi.org/10.1007/978-3-032-29254-4_30openalex-snapshot
Temporal Fusion Transformers for Energy Generation Forecasting in Energy Communities
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A Scene-Aware Meta-learning Framework for Robust Photovoltaic Power Forecasting
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A Stacked GRU Approach to Enhance Predictive Accuracy of Global Horizontal Irradiance
inferred← citeshttps://doi.org/10.1016/j.asoc.2026.115407openalex-snapshot
ResGRU-SC: Hybrid residual gated recurrent units and spectral clustering model for high-accuracy photovoltaic power forecasting
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Promoting solar energy utilization: Prediction, analysis and evaluation of solar radiation on building surfaces at city scale
inferred← citeshttps://doi.org/10.1016/j.engappai.2024.109555openalex-snapshot
Adaptive masked network for ultra-short-term photovoltaic forecast
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.111946openalex-snapshot
Enhancing probabilistic photovoltaic power forecasting with parallel feature interaction and bayesian correction
inferred← citeshttps://doi.org/10.1016/j.knosys.2024.112927openalex-snapshot
Energy assistants for prosumers to enable trading strategies on local electricity markets
inferred← citeshttps://doi.org/10.1016/j.segan.2026.102367openalex-snapshot
Day-ahead PV energy generation forecasting using neural networks: Comparison of history-only and forecast-driven information impact
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Unlocking solar potential through machine learning techniques for roof geometry prediction- A review
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RR-LTNet: Ramp-Rate-Centric Deep Learning Framework for Short-Horizon Photovoltaic Power Prediction
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Bridging the energy divide in a sustainable approach: Analyzing poverty, disparities and green transition in the European Union
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Short-Term Prediction of Photovoltaic Power Based on DBSCAN-SVM Data Cleaning and PSO-LSTM Model
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Two-Stage Neural Network Optimization for Robust Solar Photovoltaic Forecasting
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Simulation and Modelling as Catalysts for Renewable Energy: A Bibliometric Analysis of Global Research Trends
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Evaluating Renewable Energy’s Role in Mitigating CO2 Emissions: A Case Study of Solar Power in Finland Using the ARDL Approach
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Hybrid CNN–GRU-Based Demand–Supply Forecasting to Enhance Sustainability in Renewable-Integrated Smart Grids
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