面向经济调度的发电机组智能选择
Intelligent Subset Selection of Power Generators for Economic Dispatch
摘要：
可持续和经济的发电是当今世界基础设施的重要和强制性组成部分。最佳发电（发电机子集选择）需要仔细评估各种因素，如电源类型，发电，传输和存储容量，拥塞等，这使得这是一项艰巨的任务。我们使用Siemens PSS/E软件创建了一个网格来模拟各种条件，包括发电机供电、天气和负载需求等刺激，并使用深度学习方法对这些数据进行训练，随后进行测试。结果非常令人鼓舞。据我们所知，这是第一篇针对这个问题提出一个有效且可扩展的深度学习模型的论文。
英文摘要：
Sustainable and economical generation of electrical power is an essential and mandatory component of infrastructure in today's world. Optimal generation (generator subset selection) of power requires a careful evaluation of various factors like type of source, generation, transmission & storage capacities, congestion among others which makes this a difficult task. We created a grid to simulate various conditions including stimuli like generator supply, weather and load demand using Siemens PSS/E software and this data is trained using deep learning methods and subsequently tested. The results are highly encouraging. As per our knowledge, this is the first paper to propose a working and scalable deep learning model for this problem.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
