DDDAS-TMRP: DDDAS for Autonomic Interconnected Systems: The National Energy Infrastructure

用于管理国家电网的基本技术框架是几代人的旧技术，并没有准备好应对经济增长带来的日益增加的压力，特别是在过去几十年输电基础设施投资减少的情况下。专家们认识到，类似于2003年8月美国东北部-加拿大大停电的情况仍然存在。动态数据驱动应用（DDDAS）范式为方法创新提供了一个独特的框架，可以彻底改变国家的能源基础设施，减轻停电的威胁，并确保电网的长期稳定性，可靠性和效率。为国家能源基础设施设计的新技术将通过动态平衡电力供应和需求，并提供在发展为危机之前对潜在的衰弱情况作出反应的能力，来增加能源利用总量。提出的研究将推进态势感知、控制灵活性、自主功能和自我修复的新方法，这将彻底改变能源管理的艺术状态。研究的核心将是电网的集成实时动态传感和仿真能力。DDDAS为方法创新提供了框架，以实现跨越电网中遇到的时间尺度和空间特征的多个边界的测量和动态模拟的无缝和稳健集成。为了实现其目标，该项目将沿着六个综合任务（如仿真、传感、综合方法、可视化、计算机安全和演示）取得进展。本研究的进展包括：1)在高端计算平台上利用集成分布式异构仿真（DHS）和神经网络技术进行实时、高保真的电网仿真；2)利用高成本、高精度和低成本的分布式传感器网络；3)一类新的稳定和鲁棒的数学算法，用于解决复杂的不适定问题，如实时电网仿真/传感应用；4)实时可视化和计算机安全的新方法。为了证明这项研究的智力价值并实现最广泛的影响，该团队将利用与中西部系统独立运营商（MISO）的现有合作，这是美国批准的第一个区域传输组织，技术转移机制基本上已经到位。

The basic technological framework used to manage the national electric power grid is several generations old and is not prepared to meet the increased pressures of a growing economy, especially with the reducedinvestment for transmission infrastructure in the past several decades. Experts recognize thatblackouts similar to the Northeast US - Canadian blackout of August 2003 remain a reality. TheDynamic Data-Driven Applications (DDDAS) paradigm offers a unique framework formethodological innovations that can revolutionize the nation's energy infrastructure, alleviate thethreat of blackouts, and assure the long term stability, reliability, and efficiency of the electric powergrid. New technology designed for the national energy infrastructure would increase the total energy utilized bydynamically balancing power supply and demand, and by providing the ability to respond topotentially debilitating situations before they develop into a crisis. The proposed research willadvance new methodologies for situation awareness, control flexibility, autonomic functionalities, andself-healing that will revolutionize the state of the art in energy management. The centerpiece of theresearch will be an integrated real time dynamic sensing and simulation capability for the electricpower grid. DDDAS provides the framework for the methodological innovations to achieveseamless and robust integration of measurements and dynamic simulations across the multipleboundaries of timescales and spatial characteristics encountered in the power grid.To achieve its objectives the project will make advances along six integrated tasks (e.g. Simulation, Sensing, Integrative Methods, Visualization,Computer Security, and Demonstration). The advances of this research include 1) realtime, high fidelity power grid simulation using integrated distributed heterogeneous simulation (DHS)and neural network techniques on high end computational platforms, 2) the integration of real timesimulation and sensing using both high cost, high precision and low cost distributed sensor networks,3) a new class of stable and robust mathematical algorithms for solving complex ill-posed problemssuch as the real time power grid simulation/sensing application, 4) new approaches to real timevisualization and computer security. To demonstrate the intellectual merit and to achieve thebroadest impact of this research, the team will take advantage of existing collaborations with theMidwest Systems Independent Operators (MISO), the first regional transmission organizationapproved in the United States, and technology transfer mechanisms are essentially already in place.