メソアンサンブル予報を用いた Just-In-Time Modeling による翌日エリア太陽光発電予測

Translated title of the contribution: Area Day-ahead Photovoltaic Power Prediction by Just-In-Time Modeling with Meso-scale Ensemble Prediction System

Yusuke Mori*, Shinji Wakao, Hideaki Ohtake, Takahiro Takamatsu, Takashi Oozeki

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Photovoltaics (PV) output prediction, which is indispensable for power system operation, can affects demand and supply adjustment adversely when large prediction error occurs. Thus, the reduction of large error as well as average error is required in PV power prediction. In 2019, the operation of the Meso-scale Ensemble Prediction System (MEPS) of numerical weather prediction started from the Japan Meteorological Agency, and the amount of forecasting information would be potentially useful for the improvement of PV power prediction. However, very few studies on inputting multiple meteorological elements of the MEPS have been reported. In this paper, we newly develop the prediction model for an area day-ahead PV power output composed of Just-In-Time Modeling (JIT Modeling) with multiple elements of the MEPS. The developed method achieves precise forecasts with low computational load by both selecting meteorological elements valid for improving prediction accuracy and adequately devising the structure of JIT Modeling. Some numerical examples demonstrating the effectiveness of the developed method are also presented. In particular, the proposed method reduces large error significantly.

Translated title of the contributionArea Day-ahead Photovoltaic Power Prediction by Just-In-Time Modeling with Meso-scale Ensemble Prediction System
Original languageJapanese
Pages (from-to)16-24
Number of pages9
JournalIEEJ Transactions on Power and Energy
Volume143
Issue number1
DOIs
Publication statusPublished - 2023

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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