---
title: RealTime PV Power Forecasting
url: https://www.ml-quant.com/papers/ssrn/5241274/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 5241274
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5241274
featured: 2025-05-14
citations: unknown
topic: Econometrics & Forecasting
---


# RealTime PV Power Forecasting

The XGBoost model, using historical weather and PV output data, offers more precise ultrashort-term PV power predictions than the SVR model, contributing to grid stability.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5241274
- Identifier: SSRN 5241274
- Released: 2025-03-01
- First featured: Quant Letter No. 97 (2025-05-14): https://www.ml-quant.com/issues/2025-05-14/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting

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