Optimized designs were achieved using a genetic algorithm to evaluate multi-objective trade space, including Mean-Time-Between-Failure (MTBF) and volumetric power density. This work provides a foundational platform that can be used to optimize additional power converters, such as an inverter for the EV traction drive system as well as trade-offs in thermal management due to the use of different device substrate materials.
Sandia National Laboratories sponsored a three-year internally funded Laboratory Directed Research and Development (LDRD) effort to investigate the vulnerabilities and mitigations of a high-altitude electromagnetic pulse (HEMP) on the electric power grid. The research was focused on understanding the vulnerabilities and potential mitigations for components and systems at the high voltage transmission level. Results from the research included a broad array of subtopics, covered in twenty-three reports and papers, and which are highlighted in this executive summary report. These subtopics include high altitude electromagnetic pulse (HEMP) characterization, HEMP coupling analysis, system-wide effects, and mitigating technologies.
Flicker, Jack D.; Hernandez-Alvidrez, Javier; Shirazi, Mariko; Vandermeer, Jeremy; Thomson, William
In order to evaluate the ability of a Grid Bridge System(GBS), or energy storage-backed grid forming inverter, to provide spinning reserve in an islanded microgrid with significant variable generation, we have developed a high-fidelity system model. In a loss-of-wind scenario, the GBS system significantly improves both the frequency nadir as well as the transient overvoltage response of the system. This case was analyzed for a system with one, two, and three diesel generators both with and without the GBS. System stability for the one generator plus GBS case outperformed all generator system, even for the three-generator case. This indicates that spinning reserve can be shifted from the generators to the GBS without sacrificing system stability, allowing the diesel generators to operate at more economical conditions, saving significant fuel costs over the long-term implementation of the GBS.
While the concept of aggregating and controlling renewable distributed energy resources (DERs) to provide grid services is not new, increasing policy support of DER market participation has driven research and development in algorithms to pool DERs for economically viable market participation. Sandia National Laboratories recently undertook a 3 year research programme to create the components of a real-world virtual power plant (VPP) that can simultaneously participate in multiple markets. The authors' research extends current state-of-the-art rolling horizon control through the application of stochastic programming with risk aversion at various time resolutions. Their rolling horizon control consists of day-ahead optimisation to produce an hourly aggregate schedule for the VPP operator and sub-hourly optimisation for the real-time dispatch of each VPP subresource. Both optimisation routines leverage a two-stage stochastic programme with risk aversion and integrate the most up-to-date forecasts to generate probabilistic scenarios in real operating time. Their results demonstrate the benefits to the VPP operator of constructing a stochastic solution regardless of the weather. In more extreme weather, applying risk optimisation strategies can dramatically increase the financial viability of the VPP. The methodologies presented here can be further tailored for optimal control of any VPP asset fleet and its operational requirements.