Collaborative Research: Factor-Graph Approach to Monitoring and Failure Assessment in Smart-Grid Networks

这项提议的动机是需要引入概率概念来监测和管理不断变化的电力系统。许多新的分布式资源的性质，包括响应性需求，是高度可变的，很难预测。此外，该系统可能容易受到网络安全威胁，这些威胁代表着低概率的高影响事件。这挑战了今天的基本假设？S的运营和规划，它们基本上是确定性的。特别是，需要一个整体的随机公式来说明在正常情况下以及在故障期间作为供应/需求调度的组成部分的传感和通信问题。故障可能由强制停机或对部分系统的有意攻击造成。发生威胁系统完整性和供需平衡能力的事件的概率通常取决于系统状况，不能一劳永逸地确定。为了开始填补这一空白，本项目提出将不断变化的电网视为具有许多高度可变的分布式资源的电网，特别是微型太阳能和微型风力发电厂。许多分布式负载也是变化的，必须进行监控；此外，它们还对感知和传递的信息做出响应。该方案的核心思想是将这样的未来网格表示为因子图。一旦这样做了，就有可能利用正式的通信理论方法来计算系统的某些部分处于特定感兴趣状态的概率。这反过来又为经济实惠的传感器和通信架构设计奠定了基础，以支持新的操作实践。将概率推理引入供需平衡是关键，因为如果没有这种对系统状态的主动跟踪，确保可靠服务的最坏情况设计方法变得效率低得令人无法接受，同时也无法提供关于最坏情况服务情况可能性的信息。本项目中提出的方法将基于感知和交流信息的概率估计结合在一起。然后，这些估计被用来引入由不同分布式资源在系统操作员进行最小协调的情况下的自调度，正如联合PI之一已经提出的，用于平衡正常条件下的供需。在该项目中，将与通信和安全协管人员合作，进一步推广自我调度的概念，以便以概率方式说明设备故障。这些故障可能是被迫的设备停机，也可能是由电网上的网络攻击引发的。其目的是提供概念验证说明，通过启用因子图的关于系统状态严重程度的概率估计来促进概率自调度。以夏威夷瓦胡岛的电网为例，说明传感器和通信对整体性能的影响。智力优势：该提议的基本智力新颖性是将概率推理渗透到电网监测和控制领域。该项目将应用因子图和安全信任传播形式，为电网中的分布式监测、评估、安全防护、控制和风险管理铺平道路。目标是对夏威夷瓦胡岛部分电网的概率自我调度进行概念验证说明。广泛影响：该项目中的研究活动将导致有效利用分散的可再生能源资源的方法。这将有助于加快向清洁/可再生能源经济转型的步伐。在夏威夷原住民科学与工程导师计划(NHSEMP)的框架下，联合PIS将继续致力于通过本科生研究体验计划(NHSEMP)整合未被充分代表的群体对工程学的参与。

The proposal is motivated by the need to introduce probabilistic concepts for sensing and managing changing electric energy systems. The very nature of many new distributed resources, including responsive demand, is highly variable and hard to predict. Moreover, the system may be prone to cyber-security threats which represent low-probability high-impact events. This challenges the fundamental assumptions underlying today?s operations and planning which are by and large deterministic. In particular, a holistic stochastic formulation is needed to state the problem of sensing and communications as an integral part of supply/demand dispatch during normal conditions as well as during failures. Failures could be caused by either forced outages or intended attacks on portions of the system. The probabilities of events threatening the integrity of the system and the ability to balance supply and demand are generally dependent on system conditions and are not determined once for good. In order to begin to fill this gap, it is proposed in this project to view the changing electric power grid as an electric network with many highly variable distributed resources, micro-solar and micro-wind plants, in particular. Very many distributed loads are also varying and must be monitored; moreover, they are also responsive to the sensed and communicated information. The key idea in this proposal is to represent such future grid as a factor graph. Once this is done, it becomes possible to draw on formal communications theory methods to compute the probabilities of portions of the system being in certain states of interest. This, in turn, creates the basis for an affordable sensors and communications architecture design in support of novel operating practices. It is key to bring probabilistic reasoning into supply and demand balancing because without such proactive tracking of system state the worst-case design approach to ensuring reliable services becomes unacceptably inefficient, and, at the same time, does not provide information about the likelihood of the worst-case service scenario. The approach proposed in this project brings together the probability estimates based on the sensed and communicated information. These estimates are then used to introduce a self-dispatch by different distributed resources with minimal coordination by the system operators, as already proposed by one of the co-PIs for balancing supply and demand during normal conditions. In collaboration with the communications and security co-PIs on this project, the self-dispatch concept will be further generalized to probabilistically account for equipment failures. These failures could be either forced equipment outages, or initiated by cyber attacks on the power grid. The objective is to provide proof-of-concept illustrations of probabilistic self-dispatch facilitated by the factor-graph-enabled probability estimates about the severity of system state. The effects of sensors and communications on the overall performance will be illustrated using the grid of the Hawaiian island of Oahu as the experimental example.Intellectual merit: The fundamental intellectual novelty in this proposal is the penetration of probabilistic reasoning into the field of power-grid monitoring and control. The project will apply factor-graph and secure-belief-propagation formalisms to pave the way towards distributed monitoring, assessment, safe-guarding, control and risk management in power grids ? the goal being a proof-of-concept illustration of probabilistic self-dispatch on a portion of the power grid of the Hawaiian island of Oahu.Broader impact: The research activities in this project will lead to methods for efficient utilization of scattered renewable energy resources. This will contribute to the accelerated pace of transformation towards a clean/renewable energy economy. The co-PIs will continue to be engaged in integrating the participation of under-represented groups in engineering through research experience programs for undergraduates under the umbrella of the Native Hawaiian Science and Engineering Mentorship Program (NHSEMP).