Workshop Proposal: Data-Driven Energy Systems: From Data Collection to Information Technology for Sustainable Services

该项目将组织一次全国性会议，与会者包括工程、计算机科学和政策制定方面的思想领袖，并就未来的能源管理系统（EMS）交换意见。 新的EMS架构的目标将特别讨论，以支持的前提下，IT支持的分布式松散协调的架构是有效的和强大的重大计划外的自然灾害，如飓风和龙卷风。 目前，EMS软件没有应用程序，使电力用户能够在这种重大自然灾害期间积极应对系统状况。 也没有快速自下而上恢复的工具。 研讨会将讨论下一代多层EMS架构的可能问题公式，能够激励用户群体（可以将它们称为智能平衡机构（iBA））以在正常条件下尽可能有效地利用资源，并具有足够的适应性和灵活性，以确保在单/双设备故障期间提供差异化的可靠服务（现在由公用事业通过保持保守的备用最坏情况储备来计划）以及在自然灾害期间（对于自然灾害，公用事业没有方法来确保可靠的优先服务而不需要过多的备用储备）。 研讨会将探讨分布式智能和正确的IT信号以及嵌入不同层的正确并行异步算法如何实现社会选择和系统级性能。

This project is to organize a national conference with leading engineering, computer science and policy making thought leaders and exchange ideas on future energy management systems (EMS). The objectives of the new EMS architectures will particularly be discussed to support the premise that IT-enabled distributed loosely coordinated architecture is both efficient and robust during major unplanned natural disasters, like hurricanes and tornadoes. At present, EMS software does not have applications that enable electricity users to pro-actively respond to system conditions during such major natural disasters. There are no tools for fast bottom-up restoration, either. The workshop will address possible problem formulations for next generation multi-layered EMS architectures capable of incentivizing the groups of users (one may refer to them as the intelligent balancing authorities (iBAs)) to utilize resources as efficiently as possible during normal condition, and be sufficiently adaptive and flexible to ensure differentiated reliable service during single/double equipment outages (planned for by the utilities now by keeping conservative stand-by the worst case reserves) as well as during natural disasters (for which utilities do not have methods to ensure reliable prioritized service without requiring excessive stand-by reserve). The workshop will explore how the distributed intelligence and the right IT signals with the right parallel asynchronous algorithms embedded into different layers would enable both social choice and system-level performance.