Networked Microgrid Optimization and Energy Management

Jane, Robert

doi:10.37099/mtu.dc.etdr/876

Cited by 2 publications

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“…Disclaimer: Reference herein to any specific commercial company, product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or the Department of the Army (DoA). The opinions of the authors expressed herein do not necessarily state or reflect those of the United State Government of the DoA, and shall not be used for advertising or product endorsement purposes; Components of this publication were also used to fulfill the degree requirements for pursuit of a doctoral degree, in the field of Mechanical Engineering-Engineering Mechanics at Michigan Technological University [32]; DISTRIBUTION STATEMENT A. Approved for public release: distribution unlimited.…”

Section: Discussionmentioning

confidence: 99%

Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design

et al. 2020

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A microgrid consists of electrical generation sources, energy storage assets, loads, and the ability to function independently, or connect and share power with other electrical grids. Thefocus of this work is on the behavior of a microgrid, with both diesel generator and photovoltaic resources, whose heating or cooling loads are influenced by local meteorological conditions. Themicrogrid's fuel consumption and energy storage requirement were then examined as a function of the atmospheric conditions used by its energy management strategy (EMS). A fuel-optimal EMS, able to exploit meteorological forecasts, was developed and evaluated using a hybrid microgrid simulation. Weather forecast update periods ranged from 15 min to 24 h. Four representative meteorological sky classifications (clear, partly cloudy, overcast, or monsoon) were considered. Forall four sky classifications, fuel consumption and energy storage requirements increased linearly with the increasing weather forecast interval. Larger forecast intervals lead to degraded weather forecasts, requiring more frequent charging/discharging of the energy storage, increasing both the fuel consumption and energy storage design requirements. The significant contributions of this work include the optimal EMS and an approach for quantifying the meteorological forecast effects on fuel consumption and energy storage requirements on microgrid performance. The findings of this study indicate that the forecast interval used by the EMS affected both fuel consumption and energy storage requirements, and that the sensitivity of these effects depended on the 24-hour sky conditions.

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Section: Discussionmentioning

confidence: 99%

Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design

et al. 2020

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“…Components of this publication were also used to fulfill the degree requirements for pursuit of a doctoral degree, in the field of Mechanical Engineering -Engineering Mechanics at Michigan Technological University. 29 Gordon G Parker specializes in control system design and the correlation of non-linear dynamic models to experimental data. A key area of his research is the optimal control of microgrids with particular attention given to networked topologies.…”

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Adaptive leader election for control of tactical microgrids

Jane

Goldsmith

Parker

et al. 2020

Journal of Defense Modeling & Simulation

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An adaptive leader election protocol (LEP) was developed to control both stationary and mobile generation assets (generators and vehicles), achieved using an energy management system (EMS). The LEP algorithm adapts to changes in both topology and the asset inventory using the longevity criterion (available fuel, future availability), used to compute a desirability index, for election of a leader. The leader then implemented an optimal power flow EMS to ensure sufficient and optimal power flow within the electrical network was maintained in the presence of a complex electrical load, regardless of the asset mix. Both the LEP and EMS algorithms were distributed to the generation assets. This capability supports stationary grid-tied, vehicle-to-grid, and mobile vehicle-to-vehicle-based applications. Simulated case studies illustrate that the adaptive LEP was resistive to deterministic events (maintenance, available fuel), which could yield an inoperable asset, compromising grid stability. The use of the adaptive LEP resulted in a communication complexity of at most [Formula: see text]; in contrast, a fully connected communication system requires [Formula: see text] communications, limiting the scalability of the network. The EMS was optimized, resulting in a computationally efficient and scalable optimal power flow algorithm that can be extended for more general stationary or mobile energy networks.

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Networked Microgrid Optimization and Energy Management

Cited by 2 publications

References 0 publications

Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design

Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design

Adaptive leader election for control of tactical microgrids

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