| ■論文No. |
|
| ■ページ数 |
12ページ |
■発行日
|
2020/09/01 |
| ■タイトル |
再生可能エネルギーの予測誤差の時刻間相関が需給計画手法の評価に及ぼす影響―風力発電に対する分析― |
| ■タイトル(英語) |
Impacts of Inter-Temporal Correlation in Prediction Error of Renewable Energy Sources on Generation System Scheduling―Study on Wind Power Generation― |
| ■著者名 |
荒井 有美（東京工業大学 工学院 電気電子系），河辺 賢一（東京工業大学 工学院 電気電子系），七原 俊也（東京工業大学 工学院 電気電子系） |
| ■著者名(英語) |
Narimi Arai (School of Engineering, Tokyo Institute of Technology), Kenichi Kawabe (School of Engineering, Tokyo Institute of Technology), Toshiya Nanahara (School of Engineering, Tokyo Institute of Technology) |
| ■価格 |
会員 ¥550 一般 ¥770 |
| ■書籍種類 |
論文誌(論文単位) |
| ■グループ名 |
【B】電力・エネルギー部門 |
| ■本誌 |
電気学会論文誌B（電力・エネルギー部門誌） Vol.140 No.9 （2020）
|
| ■本誌掲載ページ |
668-679ページ |
| ■原稿種別 |
論文／日本語 |
| ■電子版へのリンク |
https://www.jstage.jst.go.jp/article/ieejpes/140/9/140_668/_article/-char/ja/
|
| ■キーワード |
予測誤差，需給運用，自己回帰モデル，運転予備力，再生可能エネルギー，モンテ・カルロ法 prediction error，power system operation，autoregressive model，operating reserve，renewable energy sources，Monte Carlo method |
| ■要約(日本語) |
|
| ■要約(英語) |
In this paper, we propose a prediction error model of wind power generation considering inter-temporal correlation and examine the impacts of the error on the evaluation of generation system schedules. The increasing installed capacity of renewable energy sources (RESs) raises the risk of supply shortage and surplus in operating power systems. Many researchers have developed a method based on Monte Carlo simulation for generation system scheduling with a large-scale integration of RESs. We propose an autoregressive model for the prediction error of wind power generation to be used for Monte Carlo methods. In addition, we simulated operation of a power system including unit commitment of thermal power plants, and analyzed the impacts of inter-temporal correlation in the prediction error on generation system scheduling. Fuel cost, unsupplied energy and surplus energy were evaluated with the prediction error. The results show the importance of considering inter-temporal correlation in the prediction error of wind power generation on generation system scheduling. |
| ■版 型 |
A4 |
