Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design
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, whos...
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MDPI AG
2020-01-01
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Series: | Energies |
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Online Access: | https://www.mdpi.com/1996-1073/13/3/577 |
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author | Robert Jane Gordon Parker Gail Vaucher Morris Berman |
author_facet | Robert Jane Gordon Parker Gail Vaucher Morris Berman |
author_sort | Robert Jane |
collection | DOAJ |
description | 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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format | Article |
id | doaj.art-1f3b7a92685e4d66ae62504f345f1541 |
institution | Directory Open Access Journal |
issn | 1996-1073 |
language | English |
last_indexed | 2024-04-11T22:07:43Z |
publishDate | 2020-01-01 |
publisher | MDPI AG |
record_format | Article |
series | Energies |
spelling | doaj.art-1f3b7a92685e4d66ae62504f345f15412022-12-22T04:00:39ZengMDPI AGEnergies1996-10732020-01-0113357710.3390/en13030577en13030577Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and DesignRobert Jane0Gordon Parker1Gail Vaucher2Morris Berman3US Army Research Laboratory, US Army Combat Capabilities Development Command, US Army Futures Command, Adelphi, MD 20783, USADepartment of Mechanical Engineering - Engineering Mechanics, College of Engineering, Michigan Technological University, Houghton, MI 49931, USAUS Army Research Laboratory, US Army Combat Capabilities Development Command, US Army Futures Command, White Sands Missile Range, NM 88002, USAUS Army Research Laboratory, US Army Combat Capabilities Development Command, US Army Futures Command, Adelphi, MD 20783, USAA 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.https://www.mdpi.com/1996-1073/13/3/577microgridenergy managementweather effectsweather forecastelectrical load forecastfuel consumptionenergy storage requirementsmodel predictive control |
spellingShingle | Robert Jane Gordon Parker Gail Vaucher Morris Berman Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design Energies microgrid energy management weather effects weather forecast electrical load forecast fuel consumption energy storage requirements model predictive control |
title | Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design |
title_full | Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design |
title_fullStr | Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design |
title_full_unstemmed | Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design |
title_short | Characterizing Meteorological Forecast Impact on Microgrid Optimization Performance and Design |
title_sort | characterizing meteorological forecast impact on microgrid optimization performance and design |
topic | microgrid energy management weather effects weather forecast electrical load forecast fuel consumption energy storage requirements model predictive control |
url | https://www.mdpi.com/1996-1073/13/3/577 |
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