A new thinking for renewable energy model: Remote sensing-based renewable energy model

Shifeng Wang; Sylvain Leduc; Sicong Wang; Michael Obersteiner; Christian Schill; Barbara Koch

doi:10.1002/er.1518

A new thinking for renewable energy model: Remote sensing-based renewable energy model

Shifeng Wang, Sylvain Leduc, Sicong Wang, Michael Obersteiner, Christian Schill, Barbara Koch

Research output: Contribution to journal › Article › peer-review

12 Citations (Scopus)

Abstract

This paper mainly focuses on the two issues through remote sensing: assessment of the renewable energy potential and integration of the renewable energy model. Three methods for assessing the renewable energy potential with remote sensing (RS) are proposed. The methods can provide more precise evaluation of renewable energy potential, which is the first vital step to develop renewable energy model. The paper then first presents three integrations of the renewable energy model with RS and points out that with respect to the problems one of them is employed. The assessment methods based on RS and the integrations with RS are illustrated by a simple example with Europe solar energy data set. The results show that Germany is the optimal country to install photovoltaic with a capacity of 137 125GW.

Original language	English
Pages (from-to)	778-786
Number of pages	9
Journal	International Journal of Energy Research
Volume	33
Issue number	8
Early online date	26 Jan 2009
DOIs	https://doi.org/10.1002/er.1518
Publication status	Published - 25 Jun 2009
Externally published	Yes

Funder

EU project. Grant Number: GOCE 037063

Keywords

Integrations with remote sensing
Remote sensing
Renewable energy model
Renewable energy potential

ASJC Scopus subject areas

Renewable Energy, Sustainability and the Environment
Nuclear Energy and Engineering
Fuel Technology
Energy Engineering and Power Technology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1002/er.1518

Cite this

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title = "A new thinking for renewable energy model: Remote sensing-based renewable energy model",

abstract = "This paper mainly focuses on the two issues through remote sensing: assessment of the renewable energy potential and integration of the renewable energy model. Three methods for assessing the renewable energy potential with remote sensing (RS) are proposed. The methods can provide more precise evaluation of renewable energy potential, which is the first vital step to develop renewable energy model. The paper then first presents three integrations of the renewable energy model with RS and points out that with respect to the problems one of them is employed. The assessment methods based on RS and the integrations with RS are illustrated by a simple example with Europe solar energy data set. The results show that Germany is the optimal country to install photovoltaic with a capacity of 137 125GW.",

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author = "Shifeng Wang and Sylvain Leduc and Sicong Wang and Michael Obersteiner and Christian Schill and Barbara Koch",

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T1 - A new thinking for renewable energy model

T2 - Remote sensing-based renewable energy model

AU - Wang, Shifeng

AU - Leduc, Sylvain

AU - Wang, Sicong

AU - Obersteiner, Michael

AU - Schill, Christian

AU - Koch, Barbara

PY - 2009/6/25

Y1 - 2009/6/25

N2 - This paper mainly focuses on the two issues through remote sensing: assessment of the renewable energy potential and integration of the renewable energy model. Three methods for assessing the renewable energy potential with remote sensing (RS) are proposed. The methods can provide more precise evaluation of renewable energy potential, which is the first vital step to develop renewable energy model. The paper then first presents three integrations of the renewable energy model with RS and points out that with respect to the problems one of them is employed. The assessment methods based on RS and the integrations with RS are illustrated by a simple example with Europe solar energy data set. The results show that Germany is the optimal country to install photovoltaic with a capacity of 137 125GW.

AB - This paper mainly focuses on the two issues through remote sensing: assessment of the renewable energy potential and integration of the renewable energy model. Three methods for assessing the renewable energy potential with remote sensing (RS) are proposed. The methods can provide more precise evaluation of renewable energy potential, which is the first vital step to develop renewable energy model. The paper then first presents three integrations of the renewable energy model with RS and points out that with respect to the problems one of them is employed. The assessment methods based on RS and the integrations with RS are illustrated by a simple example with Europe solar energy data set. The results show that Germany is the optimal country to install photovoltaic with a capacity of 137 125GW.

KW - Integrations with remote sensing

KW - Remote sensing

KW - Renewable energy model

KW - Renewable energy potential

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DO - 10.1002/er.1518

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JO - International Journal of Energy Research

JF - International Journal of Energy Research

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ER -

A new thinking for renewable energy model: Remote sensing-based renewable energy model

Abstract

Funder

Keywords

ASJC Scopus subject areas

UN SDGs

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