Network Approach to Analyzing Failure Cascade in Power Networks with Cyber Coupling
DescriptionThis proposal is a resubmission of last year's unfunded proposal, incorporating the keyreviewers' comments as described in detail in Part-II-3. Existing power delivery networks consist of complex interconnection of generators, loads and substations, with sophisticated control incorporated to ensure their safe and robust operation. Conventional power flow models have been used for studying these networks, but complex interactions of causes leading to failure of power components are often not readily analyzed. Cascading failure has been a topic receiving much attention; however, there is no effective tool for analysis and prediction of propagation of the failure cascade due to the lack of adequate models that can incorporate the complex interactions of the connected system. In 2015, we reported a novel approach for robustness study of power networks using a complex network perspective, and our work was immediately put in the IEEEXplore Innovation Spotlight. Following this success, we published in 2017 a contribution demonstrating the use of this model to generate and explain the propagation profiles as typified in the 1996 and 2003 North-American blackouts. In this proposal, we aim to conduct a research study, combining deterministic power flow models with essential stochastic processes, as well as extensive simulations and collection of real data, to identify the topological properties and operational parameters that are crucial in determining the safe and robust operation of power networks. Our research will consist of the following components. First, we develop a model for describing the failure processes in power networks with cyber coupling. While some network theorists had applied complex network models for power network systems, the main shortcoming was the lack of proper description for the physical power flow processes. The key novelty is the combined use of physical power flow equations and complex network models allowing crucial parameters and coupling patterns to be readily examined. This model will also incorporate stochastic processes to allow failure timings to be included, and hence propagation profiles generated in time scale. Extensive simulation study will be conducted, in comparison with historical blackout data, aiming to recover the relationship between the failure propagation profiles, network structure, network parameters, and cyber coupling patterns. Robustness metrics will be developed for indication of the extent and onset time for large-scale blackout upon an initial element failure. Our findings are expected to generate ground-breaking contributions for development of future power grids by providing prediction of the likely failure propagation and extent of damages.
|Effective start/end date||1/01/20 → …|