Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design
Robert Jane,
Gordon Parker,
Gail Vaucher and
Morris Berman
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Robert Jane: US Army Research Laboratory, US Army Combat Capabilities Development Command, US Army Futures Command, Adelphi, MD 20783, USA
Gordon Parker: Department of Mechanical Engineering - Engineering Mechanics, College of Engineering, Michigan Technological University, Houghton, MI 49931, USA
Gail Vaucher: US Army Research Laboratory, US Army Combat Capabilities Development Command, US Army Futures Command, White Sands Missile Range, NM 88002, USA
Morris Berman: US Army Research Laboratory, US Army Combat Capabilities Development Command, US Army Futures Command, Adelphi, MD 20783, USA
Energies, 2020, vol. 13, issue 3, 1-23
Abstract:
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.
Keywords: microgrid; energy management; weather effects; weather forecast; electrical load forecast; fuel consumption; energy storage requirements; model predictive control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)
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