Yousu Chen

Bio: Yousu Chen is an academic researcher from Pacific Northwest National Laboratory. The author has contributed to research in topics: Electric power system & Grid. The author has an hindex of 17, co-authored 73 publications receiving 1424 citations. Previous affiliations of Yousu Chen include Battelle Memorial Institute.

Risk Assessment of Cascading Outages: Methodologies and Challenges

Abstract: Cascading outages can cause large blackouts, and a variety of methods are emerging to study this challenging topic. The Task Force on Understanding, Prediction, Mitigation, and Restoration of Cascading Failures, under the IEEE PES Computer Analytical Methods Subcommittee (CAMS), seeks to consolidate and review the progress of the field towards methods and tools of assessing the risk of cascading failure. This paper discusses the challenges of cascading failure and summarizes a variety of state-of-the-art analysis and simulation methods, including analyzing observed data, and simulations relying on various probabilistic, deterministic, approximate, and heuristic approaches. Limitations to the interpretation and application of analytical results are highlighted, and directions and challenges for future developments are discussed.

Modern Grid Initiative Distribution Taxonomy Final Report

Abstract: This is the final report for the development of a toxonomy of prototypical electrical distribution feeders. Two of the primary goals of the Department of Energy's (DOE) Modern Grid Initiative (MGI) are 'to accelerate the modernization of our nation's electricity grid' and to 'support demonstrations of systems of key technologies that can serve as the foundation for an integrated, modern power grid'. A key component to the realization of these goals is the effective implementation of new, as well as existing, 'smart grid technologies'. Possibly the largest barrier that has been identified in the deployment of smart grid technologies is the inability to evaluate how their deployment will affect the electricity infrastructure, both locally and on a regional scale. The inability to evaluate the impacts of these technologies is primarily due to the lack of detailed electrical distribution feeder information. While detailed distribution feeder information does reside with the various distribution utilities, there is no central repository of information that can be openly accessed. The role of Pacific Northwest National Laboratory (PNNL) in the MGI for FY08 was to collect distribution feeder models, in the SynerGEE{reg_sign} format, from electric utilities around the nation so that they could be analyzed to identify regional differences in feeder design and operation. Based on this analysis PNNL developed a taxonomy of 24 prototypical feeder models in the GridLAB-D simulations environment that contain the fundamental characteristics of non-urban core, radial distribution feeders from the various regions of the U.S. Weighting factors for these feeders are also presented so that they can be used to generate a representative sample for various regions within the United States. The final product presented in this report is a toolset that enables the evaluation of new smart grid technologies, with the ability to aggregate their effects to regional and national levels. The distribution feeder models presented in this report are based on actual utility models but do not contain any proprietary or system specific information. As a result, the models discussed in this report can be openly distributed to industry, academia, or any interested entity, in order to facilitate the ability to evaluate smart grid technologies.

Massive contingency analysis with high performance computing

Abstract: Contingency analysis is a key function in the Energy Management System (EMS) to assess the impact of various combinations of power system component failures based on state estimates. Contingency analysis is also extensively used in power market operation for feasibility test of market solutions. Faster analysis of more cases is required to safely and reliably operate today's power grids which have a less margin and more intermittent renewable energy sources. Enabled by the latest development in the computer industry, high performance computing holds the promise of meet the need in the power industry. This paper investigates the potential of high performance computing for massive contingency analysis. The framework of “N-x” contingency analysis is established, and computational load balancing schemes are studied and implemented with high performance computers. Case studies of massive 300,000-contingency-case analysis using the Western Electricity Coordinating Council power grid model are presented to illustrate the application of high performance computing and demonstrate the performance of the framework and computational load balancing schemes.

Survey of tools for risk assessment of cascading outages

Abstract: This paper is a result of ongoing activity carried out by Understanding, Prediction, Mitigation and Restoration of Cascading Failures Task Force under IEEE Computer Analytical Methods Subcommittee (CAMS). The task force's previous papers [1, 2] are focused on general aspects of cascading outages such as understanding, prediction, prevention and restoration from cascading failures. This is the second of two new papers, which extend this previous work to summarize the state of the art in cascading failure risk analysis methodologies and modeling tools. The first paper reviews the state of the art in methodologies for performing risk assessment of potential cascading outages [3]. This paper describes the state of the art in cascading failure modeling tools, documenting the view of experts representing utilities, universities and consulting companies. The paper is intended to constitute a valid source of information and references about presently available tools that deal with prediction of cascading failure events. This effort involves reviewing published literature and other documentation from vendors, universities and research institutions. The assessment of cascading outages risk evaluation is in continuous evolution. Investigations to gain even better understanding and identification of cascading events are the subject of several research programs underway aimed at solving the complexity of these events that electrical utilities face today. Assessing the risk of cascading failure events in planning and operation for power transmission systems require adequate mathematical tools/software.

A novel application of parallel betweenness centrality to power grid contingency analysis

Abstract: In Energy Management Systems, contingency analysis is commonly performed for identifying and mitigating potentially harmful power grid component failures. The exponentially increasing combinatorial number of failure modes imposes a significant computational burden for massive contingency analysis. It is critical to select a limited set of high-impact contingency cases within the constraint of computing power and time requirements to make it possible for real-time power system vulnerability assessment. In this paper, we present a novel application of parallel betweenness centrality to power grid contingency selection. We cross-validate the proposed method using the model and data of the western US power grid, and implement it on a Cray XMT system – a massively multithreaded architecture – leveraging its advantages for parallel execution of irregular algorithms, such as graph analysis. We achieve a speedup of 55 times (on 64 processors) compared against the single-processor version of the same code running on the Cray XMT. We also compare an OpenMP-based version of the same code running on an HP Superdome shared-memory machine. The performance of the Cray XMT code shows better scalability and resource utilization, and shorter execution time for large-scale power grids. This proposed approach has been evaluated in PNNL's Electricity Infrastructure Operations Center (EIOC). It is expected to provide a quick and efficient solution to massive contingency selection problems to help power grid operators to identify and mitigate potential widespread cascading power grid failures in real time.

Research on Resilience of Power Systems Under Natural Disasters—A Review

Abstract: Natural disasters can cause large blackouts. Research into natural disaster impacts on electric power systems is emerging to understand the causes of the blackouts, explore ways to prepare and harden the grid, and increase the resilience of the power grid under such events. At the same time, new technologies such as smart grid, micro grid, and wide area monitoring applications could increase situational awareness as well as enable faster restoration of the system. This paper aims to consolidate and review the progress of the research field towards methods and tools of forecasting natural disaster related power system disturbances, hardening and pre-storm operations, and restoration models. Challenges and future research opportunities are also presented in the paper.

Options for Control of Reactive Power by Distributed Photovoltaic Generators

Abstract: High-penetration levels of distributed photovoltaic (PV) generation on an electrical distribution circuit present several challenges and opportunities for distribution utilities. Rapidly varying irradiance conditions may cause voltage sags and swells that cannot be compensated by slowly responding utility equipment resulting in a degradation of power quality. Although not permitted under current standards for interconnection of distributed generation, fast-reacting, VAR-capable PV inverters may provide the necessary reactive power injection or consumption to maintain voltage regulation under difficult transient conditions. As side benefit, the control of reactive power injection at each PV inverter provides an opportunity and a new tool for distribution utilities to optimize the performance of distribution circuits, e.g., by minimizing thermal losses. We discuss and compare via simulation various design options for control systems to manage the reactive power generated by these inverters. An important design decision that weighs on the speed and quality of communication required is whether the control should be centralized or distributed (i.e., local). In general, we find that local control schemes are able to maintain voltage within acceptable bounds. We consider the benefits of choosing different local variables on which to control and how the control system can be continuously tuned between robust voltage control, suitable for daytime operation when circuit conditions can change rapidly, and loss minimization better suited for nighttime operation.

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