J-GLOBAL ID:201001058475096050   Update date: Jul. 07, 2022

Fonseca Jr. João G. S.

Fonseca Jr. João G. S.
Research field  (6): Energy chemistry ,  Control and systems engineering ,  Control and systems engineering ,  Mechanics and mechatronics ,  Robotics and intelligent systems ,  Thermal engineering
Research keywords  (10): 日射量予測 ,  太陽光発電システム ,  Artificial Intelligence Techniques ,  Exergy Analysis ,  Thermodynamics ,  エネルギーシステムシミュレーション ,  エゼルギー分析 ,  人工の神経回路網 ,  太陽光発電 ,  日射量予測
Research theme for competitive and other funds  (2):
  • 2021 - 2024 太陽光発電システム上の積雪動態の解明と予測への展開
  • 日射量予測と太陽光発電の予測
Papers (50):
MISC (49):
Books (4):
  • Machine Learning Applications on Integration of Renewable Energy to Power Systems
  • 連載 スマートグリッドへの利用に向けた 最新の日射量・太陽光発電電力量の予測技術 (第3回)
    大河出版 2020
  • 連載:スマートグリッドへの利用に向けた最新の日射量・太陽光発電電力量の予測技術(第2回)
    大河出版 2020
  • 次世代電力システム設計論 : 再生可能エネルギーを活かす予測と制御の調和
    オーム社 2019 ISBN:9784274507533
Lectures and oral presentations  (40):
  • A Comparison of Two Methods to Forecast Residual Demand One Day Ahead of Time
    (Solar World Congress 2021 2021)
  • Initial Results on Forecasting Residual Power Demand with Gradient Boosting Trees
    (The 2020 Annual Conference of Power & Energy Society IEE of Japan 2020)
  • Characteristics of Day-Ahead Residual Demand, PV Power and Demand Forecasts in a Scenario of Large Penetration of PV
    (37th European Photovoltaic Solar Energy Conference and Exhibition 2020)
  • Characterizing Day-ahead Forecast Errors of PV Power in Hokkaido: An Assessment with 2 Years of Data
    (Annual Conference of Power & Energy Society IEE of Japan 2019)
  • On the Improvement of Day-ahead Forecasts of Solar Irradiation with Simple Ensembles and Training Data Selection in Japan: A Countrywide Assessment
    (8th International Workshop on Integration of Solar Power into Power Systems, 2018 2018)
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