DDDAS-TMRP: Auto-Steered Information-Decision Processes for Electric System Asset Management

粗略估计，组成美国输电系统(138-765千伏)的电力变压器和断路器的数量分别为15万和60万；此外，还有25.4万英里的高压输电线路。仅线路的总重置价值(不包括土地)就保守地估计超过1000亿美元[1]，如果包括变压器和断路器，则是原来的三倍。在过去15年中，对新传输设备的投资大幅下降。维持可接受的电力传输系统可靠性并以低能源价格提供电能需要在传感、诊断、通信、数据管理、处理、算法、风险评估、决策(用于操作、维护和规划)和过程协调方面的创新。在这些资产管理问题中，数据驱动的电力行业在传感和诊断方面取得了长足进步。然而，在通信、数据管理、信息处理和相关算法、风险评估方法和决策范式方面进展较少，在进程协调方面几乎不存在进展；我们正是在这些领域提出了我们的工作。该项目的目标是开发一种硬件-软件原型，能够自动控制高压电力传输系统的运行、维护和规划所固有的信息决策周期。为实现这一目标，我们将针对资本密集型、地理分布的有形资产管理所固有的5个主要问题采取并推进创造性办法：(A)传感和通信；(B)整合数据；(C)将条件计量转变为可靠性计量；(D)开发和连接多时间尺度随机决策算法；(E)信息估值和随后的传感器部署。该项目还将在一个代表爱荷华州电力系统的新型模拟环境上建立一个自动驾驶信息决策过程的原型，该环境由现场安装驱动。直接影响将是增强处理和使用与拥有和运营传输设备相关的海量数据流的能力和信心，从而实现更好的投资、维护和运营决策，最终实现更经济、更可靠的电力输送。

A rough estimate of the numbers of power transformers and circuit breakers comprising the US transmission system (138-765 kV) are 150,000 and 600,000, respectively; in addition, there are 254,000 miles of high voltage transmission lines. Total replacement value of the lines alone (excluding land) is conservatively estimated at over $100 billion dollars [1] and triples when including transformers and circuit breakers. Investment in new transmission equipment has significantly declined over the past 15 years. Maintaining acceptable electric transmission system reliability and delivering electric energy at low energy prices requires innovations in sensing, diagnostics, communications, data management, processing, algorithms, risk-assessment, decision-making (for operations, maintenance, and planning), and process coordination. Among these asset management problems, the data-driven electric power industry has made strides in sensing and diagnostics. Yet there has been less progress in communications, data management, information processing and associated algorithms, risk assessment methods, and decision-making paradigms, and progress has been almost nonexistent in process coordination; it is precisely in these areas that we propose our work. The objective of this project is to develop a hardware-software prototype capable of auto-steering the information-decision cycles inherent to managing operations, maintenance, and planning of the high-voltage electric power transmission systems. In pursuing this objective, we will implement and advance creative approaches to 5 main problems inherent to management of capital-intensive, geographically distributed physical assets: (a) Sensing and communications; (b) Integrating data;(c) Transforming condition measurements to reliability metrics; (d) Developing and linking multi-time scale stochastic decision algorithms; (e) Valuation of information and subsequent sensor deployment. The project will also build a prototype auto-steered information-decision process on top of a novel simulation environment representing the Iowa power system that is driven by, and drives, field installations. The immediate impact will be an increased ability and confidence therein to handle and use the massive data streams associated with owning and operating transmission equipment, resulting in better investment, maintenance, and operating decisions, and ultimately, more economic and more reliable electric delivery of electric power.