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Maximum Power Flow and Line Loadability01:23

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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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Predictive mapping of the global power system using open data.

C Arderne1, C Zorn2,3, C Nicolas4

  • 1World Bank Group, Washington, D.C., USA. carderne@worldbank.org.

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|January 17, 2020
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Summary
This summary is machine-generated.

This study maps global power infrastructure, revealing 97% of people live near medium-voltage (MV) lines. This open-access data aids electricity access and climate change adaptation efforts.

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Area of Science:

  • Geospatial data analysis
  • Power systems engineering
  • Climate change adaptation

Background:

  • Limited global power infrastructure data hinders electricity access and climate change response.
  • High-voltage transmission data is available, but medium- and low-voltage data are scarce.
  • This data gap challenges practitioners in electricity access, power sector resilience, and climate adaptation.

Purpose of the Study:

  • To create the first open-license composite map of the global power system.
  • To address the lack of detailed medium- and low-voltage power infrastructure data.
  • To support global efforts in electricity access, power sector resilience, and climate change adaptation.

Main Methods:

  • Utilized state-of-the-art algorithms for geospatial data analysis.
  • Developed a comprehensive global power system map.
  • Validated the data accuracy across 14 countries.

Main Results:

  • 97% of the global population resides within 10 km of a medium-voltage (MV) line.
  • Significant regional and income-based variations in proximity to MV lines were observed.
  • Achieved 75% accuracy on the validation dataset.

Conclusions:

  • The developed global power system map provides crucial data for improved electricity modeling and planning.
  • This resource is vital for advancing Sustainable Development Goals related to energy access and climate action.
  • The findings demonstrate the utility of the data at national and regional scales.