文献
J-GLOBAL ID:202202284173490527
整理番号:22A0977795
スポット電力市場における混雑緩和のためのハイブリッド深層ニューラルネットワークベース発電再スケジューリング【JST・京大機械翻訳】
Hybrid Deep Neural Network-Based Generation Rescheduling for Congestion Mitigation in Spot Power Market
著者 (7件):
Agrawal Anjali
(Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, Madhya Pradesh, India)
,
Pandey Seema N.
(Department of Electrical Engineering, Dr. Bhim Rao Ambedkar Polytechnic College, Gwalior, Madhya Pradesh, India)
,
Srivastava Laxmi
(Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior, Madhya Pradesh, India)
,
Walde Pratima
(Department of Electrical Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India)
,
Singh Saumya
(Department of Electrical Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India)
,
Khan Baseem
(Department of Electrical and Computer Engineering, Hawassa University, Hawassa, Ethiopia)
,
Saket R. K.
(Department of Electrical Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India)
資料名:
IEEE Access
(IEEE Access)
巻:
10
ページ:
29267-29276
発行年:
2022年
JST資料番号:
W2422A
ISSN:
2169-3536
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)