Determining the Economical Wind Power Sites for the Needed Power Loads Accounting for Geographical Terrains

Wen Li Wang, Mei Huei Tang

Research output: Contribution to journalConference article

Abstract

Green power has attracted the world's attention and the proliferation of wind farms serve this purpose. However, wire connections among power sources and loads can be very costly in addition to the investment on the equipment. The geographical terrains also affect the routing cost, because the connection between two coordinates are often impractical to be a straight Euclidean distance. The Earth is a globe shape with curvature and a terrain can have rugged floors or water surfaces that hinder the convenience of wiring. The objective of this paper is to take advantage of a developed heuristic and apply learning algorithms to determine the best wind power sites. The goal is to conserve wiring expense and accommodate power loads. Terrain knowledge is incorporated by utilizing the geographical databases. Experiments are conducted to demonstrate the approach and justify cost savings. It is expected that this paradigm can be expanded to address more factors and support other green energy application domains.

Original languageEnglish (US)
Pages (from-to)217-222
Number of pages6
JournalProcedia Computer Science
Volume95
DOIs
StatePublished - Jan 1 2016
EventComplex Adaptive Systems, 2016 - Los Angeles, United States
Duration: Nov 2 2016Nov 4 2016

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Electric wiring
Wind power
Farms
Learning algorithms
Costs
Earth (planet)
Wire
Water
Experiments

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

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abstract = "Green power has attracted the world's attention and the proliferation of wind farms serve this purpose. However, wire connections among power sources and loads can be very costly in addition to the investment on the equipment. The geographical terrains also affect the routing cost, because the connection between two coordinates are often impractical to be a straight Euclidean distance. The Earth is a globe shape with curvature and a terrain can have rugged floors or water surfaces that hinder the convenience of wiring. The objective of this paper is to take advantage of a developed heuristic and apply learning algorithms to determine the best wind power sites. The goal is to conserve wiring expense and accommodate power loads. Terrain knowledge is incorporated by utilizing the geographical databases. Experiments are conducted to demonstrate the approach and justify cost savings. It is expected that this paradigm can be expanded to address more factors and support other green energy application domains.",
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Determining the Economical Wind Power Sites for the Needed Power Loads Accounting for Geographical Terrains. / Wang, Wen Li; Tang, Mei Huei.

In: Procedia Computer Science, Vol. 95, 01.01.2016, p. 217-222.

Research output: Contribution to journalConference article

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