Adaptive Dynamic Simulations for Distribution Systems using Multi-State Load Models

Schneider, Kevin P.; Tuffner, Francis K.; Elizondo, Marcelo A.; Hansen, Jacob; Fuller, Jason C.; Chassin, David P.

doi:10.1109/tsg.2018.2794180

Title: Adaptive Dynamic Simulations for Distribution Systems using Multi-State Load Models

Journal Article · 23 January 2018 · IEEE Transactions on Smart Grid

DOI: https://doi.org/10.1109/tsg.2018.2794180 · OSTI ID:1505427

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Pacific Northwest National Lab. (PNNL), Seattle, WA (United States)
SLAC National Accelerator Lab., Menlo Park, CA (United States)

The deployment of new sensors and devices on electric distribution systems is increasing the awareness of phenomena characterized by intermittent periods of highly dynamic activity that occur within extended periods of relatively static behavior. The deployment of new devices has enabled the observation of these phenomena; however, the currently available simulation methods cannot accurately reproduce the entire system behavior. Existing simulation methods, and their associated models, are able to capture portions of these phenomena, but there is not a method for efficiently modeling the entire event in a single simulation. This paper presents a novel method of adaptive simulation that enables automated transitions between quasi-static time-series and electromechancial simulation modes, as necessary to capture relevant system dynamics. The transitions between the simulation modes are triggered automatically during the running simulation based on the evolution of the system variables, utilizing multistate modes for generators and motors. This method allows for a single simulation that spans the entire time-frame, has the ability to capture dynamic events, and includes all relevant power system controls. In conclusion, the method of adaptive simulation can support the direct analysis of dynamic power system events, co-simulation of transmission and distribution systems, the development of control systems, and the development of reduced-order models.

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Research Organization:: SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)