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関連する概念動画

Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

574
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
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Distributed Loads: Problem Solving01:21

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Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
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Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

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Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
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Potential-Energy Criterion for Equilibrium01:16

Potential-Energy Criterion for Equilibrium

882
Potential energy or potential function plays an essential role in determining the stability of a mechanical system. If a system is subjected to both gravitational and elastic forces, the potential function of the system can be expressed as the algebraic sum of gravitational and elastic potential energy. If the system is in equilibrium and is displaced by a small amount, then the work done on the system equals the negative of the change in the system's potential energy from the initial to the...
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Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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Ampere-Maxwell's Law: Problem-Solving01:17

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A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of the...
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Updated: Jan 8, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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CHARGE-MAP：多基準EV充電インフラ拡張問題を研究するための統合フレームワーク

Kazi Ashik Islam1, Aparna Kishore1, Rounak Meyur2

  • 1Department of Computer Science, Biocomplexity Institute, University of Virginia, Charlottesville, VA 22903.

Proceedings of the National Academy of Sciences of the United States of America
|December 15, 2025
PubMed
まとめ

新しいフレームワークであるCharge-mapは、需要をシミュレートし、ステーションの配置を計画することによって、電気自動車（EV）充電インフラを最適化します。このデータ駆動型アプローチは、充電の迂回と待ち時間を大幅に削減し、広範なEV導入をサポートします。

キーワード:
充電インフラ電気自動車場所の最適化モビリティシミュレーション電力網

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科学分野:

  • 都市計画と交通科学
  • 電気工学と電力システム
  • 計算科学とシミュレーション

背景:

  • 電気自動車（EV）の急速な成長には、堅牢な充電インフラが必要です。
  • EV充電インフラの拡張は、需要、グリッド容量、およびコスト要因が関わる複雑な問題です。

研究 の 目的:

  • 効果的なEV充電インフラ計画のためのデータ駆動型シミュレーション最適化フレームワークであるcharge-mapを提示すること。
  • 個々のEV所有者にとって肯定的な充電体験を保証すること。

主な方法:

  • 需要予測のためのエージェントベースシミュレーションとステーション配置のための最適化を統合したcharge-mapを開発しました。
  • EV採用者の移動と充電行動をモデル化して、時空間的な需要を推定しました。
  • 予算の制約内で迂回距離と待ち時間を最小限に抑えるために、新しいステーション/充電器の場所と容量を最適化しました。
  • 電力網への影響と変圧器の容量要件を評価しました。

主要な成果:

  • charge-mapは、バージニア州で1,305の新しいステーションと2,164の充電器を使用して、約198,600台のEVをサポートできます。
  • 平均迂回距離を66％、待ち時間を72％削減しました。
  • 最小限の変圧器のアップグレードが必要であることを特定しました（住宅の1.8％、商業の80％以上が25〜50 kVAでサポート可能）。

結論:

  • charge-mapは、費用効果の高いEV充電インフラ拡張のためのデータ駆動型洞察を提供します。
  • このフレームワークは、持続可能なEV統合のためのターゲット投資を促進します。
  • EVインフラを開発する上で、政策立案者や都市計画者に重要なデータを提供します。