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

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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).