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Titlebook: Data Analytics in Power Markets; Qixin Chen,Hongye Guo,Yi Wang Book 2021 Science Press 2021 Power markets.bidding strategy.machine learnin

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樓主: 僵局
21#
發(fā)表于 2025-3-25 05:35:43 | 只看該作者
Aggregated Supply Curves Forecastingfficult to directly forecast the rivals’ individual bids due to the information privacy and volatile characteristics of individual bidding behaviors. From another point of view, the aggregation of individual bids, denoted as aggregated supply curve (ASC), might be helpful to offset the uncertainties
22#
發(fā)表于 2025-3-25 09:56:42 | 只看該作者
23#
發(fā)表于 2025-3-25 12:04:18 | 只看該作者
Reward Function Identification of?GENCOss accurately defining the individual reward function (or objective function). Considering the information barriers between market participants and researchers, the common way is to develop reward functions based on theoretical assumptions, which will inevitably cause deviations from the real world.
24#
發(fā)表于 2025-3-25 16:23:17 | 只看該作者
25#
發(fā)表于 2025-3-25 21:11:57 | 只看該作者
26#
發(fā)表于 2025-3-26 03:25:00 | 只看該作者
https://doi.org/10.1007/978-981-16-4975-2Power markets; bidding strategy; machine learning; price forecasting; load forecasting
27#
發(fā)表于 2025-3-26 04:40:58 | 只看該作者
28#
發(fā)表于 2025-3-26 09:01:14 | 只看該作者
Correction to: Introduction to Power Market Data,In the original version of the book, the following belated corrections have been made
29#
發(fā)表于 2025-3-26 15:35:56 | 只看該作者
Meredith E. Safran,Monica S. Cyrinomatic changes for system operators, generation companies, and electricity consumers. The operation of power markets constantly produces valuable market data which can support the decision of both market organizers and market participants. This chapter presents an introduction to power market data. F
30#
發(fā)表于 2025-3-26 17:12:27 | 只看該作者
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