Non-biomass renewables - COFFEE-TEA - Revision history

Rineke Oostenrijk: Text replacement - "IsDocumentationOf=TEA" to "IsDocumentationOf=COFFEE-TEA"

2019-09-06T10:58:36Z

Text replacement - "IsDocumentationOf=TEA" to "IsDocumentationOf=COFFEE-TEA"

← Older revision		Revision as of 12:58, 6 September 2019
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	{{ModelDocumentationTemplate		{{ModelDocumentationTemplate
	\|IsDocumentationOf=TEA		\|IsDocumentationOf=COFFEE-TEA
	\|DocumentationCategory=Non-biomass renewables		\|DocumentationCategory=Non-biomass renewables
	}}		}}

Rineke Oostenrijk: Rineke Oostenrijk moved page Non-biomass renewables - TEA to Non-biomass renewables - COFFEE-TEA without leaving a redirect: Text replacement - " - TEA" to " - COFFEE-TEA"

2019-09-06T10:51:57Z

Rineke Oostenrijk moved page Non-biomass renewables - TEA to Non-biomass renewables - COFFEE-TEA without leaving a redirect: Text replacement - " - TEA" to " - COFFEE-TEA"

← Older revision

Revision as of 12:51, 6 September 2019

Rafael Garaffa at 02:17, 3 August 2019

2019-08-03T02:17:46Z

← Older revision		Revision as of 04:17, 3 August 2019
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	</figure>.		</figure>.

	In the COFFEE model, the quality of the hydro resources derives from two major components: capacity factors and resource availability. These aspects are directly associated with exploitation costs. Thus, the total resources can be separated in terms of costs in order to create a supply curve for Hydro power~~. The only available information of this kind was provided by the International Renewable Energy Agency (IRENA)~~. [[CiteRef::ireana2014]] and other related literature provide regional profiles for hydro projects~~. The unexploited potential~~ was used ~~and condensed~~ to estimate the hydro resource availability for the 18 regions of the model.		In the COFFEE model, the quality of the hydro resources derives from two major components: capacity factors and resource availability. These aspects are directly associated with exploitation costs. Thus, the total resources can be separated in terms of costs in order to create a supply curve for Hydro power. [[CiteRef::ireana2014]] and other related literature provide regional profiles for hydro projects and was used to estimate the hydro resource availability for the 18 regions of the model.

	<figure id="fig:hydro">		<figure id="fig:hydro">
	[[File:hydro.png\|600px\|thumb\|<caption>Estimated installed capacity, total potential and potential by category for the hydro resource (GW).</caption>]]		[[File:hydro.png\|600px\|thumb\|<caption>Estimated installed capacity, total potential and potential by category for the hydro resource (GW).</caption>]]
	</figure>.		</figure>.

Rafael Garaffa at 02:16, 3 August 2019

2019-08-03T02:16:39Z

← Older revision		Revision as of 04:16, 3 August 2019
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	}}		}}

	Solar and Wind energy resources were estimated in the COFFEE model from ~~data mostly from NREL (2015), with additional information from WEC (2013)~~ and ~~NREL (2015b, 2015c)~~, especially for cost estimation. For solar resource the supply curve introduced in the model was based on solar radiance itself, instead of on electricity or power. Additionally, resources are split in four steps of increasing capacity factor.		Solar and Wind energy resources were estimated in the COFFEE model from [[CiteRef::nrel2015]] and other related engineering literature, especially for cost estimation. For solar resource the supply curve introduced in the model was based on solar radiance itself, instead of on electricity or power. Additionally, resources are split in four steps of increasing capacity factor.

	For wind resources the capacity factor is split in offshore and onshore and the distance to major consumers and to the coastline are considered. This is important to generate better supply curves for energy resources, since the optimum decision from the model may be to use a lower capacity factor that is closer to the end consumer, depending on the costs associated. In the COFFEE model, wind resource was estimated considering 12 step curves for and 27 step discrete curves were created combining capacity factor, distance to shore and water depth for onshore and offshore, respectively. <xr id="fig:~~Gas~~"/> summarizes the wind and solar resource categories.		For wind resources the capacity factor is split in offshore and onshore and the distance to major consumers and to the coastline are considered. This is important to generate better supply curves for energy resources, since the optimum decision from the model may be to use a lower capacity factor that is closer to the end consumer, depending on the costs associated. In the COFFEE model, wind resource was estimated considering 12 step curves for and 27 step discrete curves were created combining capacity factor, distance to shore and water depth for onshore and offshore, respectively. <xr id="fig:Wind_solar"/> summarizes the wind and solar resource categories.

	<figure id="fig:Wind_solar">		<figure id="fig:Wind_solar">
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	</figure>.		</figure>.

	In the COFFEE model, the quality of the hydro resources derives from two major components: capacity factors and resource availability. These aspects are directly associated with exploitation costs. Thus, the total resources can be separated in terms of costs in order to create a supply curve for Hydro power. The only available information of this kind was provided by the International Renewable Energy Agency (IRENA). ~~In both IRENA (2014a)~~ and ~~IRENA (2014b) several~~ regional profiles for hydro projects ~~are presented, but from the IRENA database, the~~ unexploited potential was used and condensed to estimate the hydro resource availability for the 18 regions of the model.		In the COFFEE model, the quality of the hydro resources derives from two major components: capacity factors and resource availability. These aspects are directly associated with exploitation costs. Thus, the total resources can be separated in terms of costs in order to create a supply curve for Hydro power. The only available information of this kind was provided by the International Renewable Energy Agency (IRENA). [[CiteRef::ireana2014]] and other related literature provide regional profiles for hydro projects. The unexploited potential was used and condensed to estimate the hydro resource availability for the 18 regions of the model.

	<figure id="fig:hydro">		<figure id="fig:hydro">
	[[File:hydro.png\|600px\|thumb\|<caption>Estimated installed capacity, total potential and potential by category for the hydro resource (GW).</caption>]]		[[File:hydro.png\|600px\|thumb\|<caption>Estimated installed capacity, total potential and potential by category for the hydro resource (GW).</caption>]]
	</figure>.		</figure>.

Rafael Garaffa at 15:27, 25 February 2019

2019-02-25T15:27:22Z

← Older revision		Revision as of 17:27, 25 February 2019
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	}}		}}

	Solar and Wind energy resources were estimated from data mostly from NREL (2015), with additional information from WEC (2013) and NREL (2015b, 2015c), especially for cost estimation.		Solar and Wind energy resources were estimated in the COFFEE model from data mostly from NREL (2015), with additional information from WEC (2013) and NREL (2015b, 2015c), especially for cost estimation. For solar resource the supply curve introduced in the model was based on solar radiance itself, instead of on electricity or power. Additionally, resources are split in four steps of increasing capacity factor.

	For ~~solar resource~~ the supply ~~curve introduced in~~ the model ~~was based on solar radiance itself~~, ~~instead of~~ on ~~electricity or power~~. ~~Additionally~~, ~~in this model resources are split in four steps of increasing~~ capacity factor.		For wind resources the capacity factor is split in offshore and onshore and the distance to major consumers and to the coastline are considered. This is important to generate better supply curves for energy resources, since the optimum decision from the model may be to use a lower capacity factor that is closer to the end consumer, depending on the costs associated. In the COFFEE model, wind resource was estimated considering 12 step curves for and 27 step discrete curves were created combining capacity factor, distance to shore and water depth for onshore and offshore, respectively. <xr id="fig:Gas"/> summarizes the wind and solar resource categories.

	~~For wind resources the capacity factor is split in offshore and onshore and the distance to major consumers~~ and ~~to the coastline are considered~~. This is important to generate better supply curves for energy resources, since the optimum decision from the model may be to use a lower capacity factor that is closer to the end consumer, depending on the costs associated		<figure id="fig:Wind_solar">
			[[File:wind_solar.png\|600px\|thumb\|<caption>Wind and solar resource categories</caption>]]
			</figure>.

	In the COFFEE model, ~~wind~~ resource was ~~estimated considering 12 step curves~~ for and ~~27 step discrete curves were created combining capacity factor, distance~~ to ~~shore and water depth~~ for ~~onshore and offshore, respectively~~.		In the COFFEE model, the quality of the hydro resources derives from two major components: capacity factors and resource availability. These aspects are directly associated with exploitation costs. Thus, the total resources can be separated in terms of costs in order to create a supply curve for Hydro power. The only available information of this kind was provided by the International Renewable Energy Agency (IRENA). In both IRENA (2014a) and IRENA (2014b) several regional profiles for hydro projects are presented, but from the IRENA database, the unexploited potential was used and condensed to estimate the hydro resource availability for the 18 regions of the model.

	Hydropower plays an important role in some regions of the world, however when compared to other renewable resources, such as wind, solar and bioenergy, there are relatively fewer studies and reports assessing hydro ~~resources for a group of countries. Even in studies where there are assessments of total~~ hydro ~~potential, the quality of the resources is not detailed (WEC, 2013)~~.		<figure id="fig:hydro">
			[[File:hydro.png\|600px\|thumb\|<caption>Estimated installed capacity, total potential and potential by category for the hydro resource (GW).</caption>]]
	~~The quality of the hydro resources derives from two major components:~~ capacity ~~factors and resource availability. These aspects are directly associated with exploitation costs. Thus~~, ~~the~~ total ~~resources can be separated in terms of costs in order to create a supply curve~~ for ~~Hydro power.~~		</figure>.

	~~The only available information of this kind was provided by~~ the ~~International Renewable Energy Agency~~ (~~IRENA~~). In both IRENA (2014a) and IRENA (2014b ) several regional profiles for hydro projects are presented, but from the IRENA database, the unexploited potential was used and condensed to estimate the hydro resource availability for the 18 regions of the model.

Rafael Garaffa at 20:33, 20 February 2019

2019-02-20T20:33:37Z

← Older revision		Revision as of 22:33, 20 February 2019
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	In the COFFEE model, wind resource was estimated considering 12 step curves for and 27 step discrete curves were created combining capacity factor, distance to shore and water depth for onshore and offshore, respectively.		In the COFFEE model, wind resource was estimated considering 12 step curves for and 27 step discrete curves were created combining capacity factor, distance to shore and water depth for onshore and offshore, respectively.

			Hydropower plays an important role in some regions of the world, however when compared to other renewable resources, such as wind, solar and bioenergy, there are relatively fewer studies and reports assessing hydro resources for a group of countries. Even in studies where there are assessments of total hydro potential, the quality of the resources is not detailed (WEC, 2013).

			The quality of the hydro resources derives from two major components: capacity factors and resource availability. These aspects are directly associated with exploitation costs. Thus, the total resources can be separated in terms of costs in order to create a supply curve for Hydro power.

			The only available information of this kind was provided by the International Renewable Energy Agency (IRENA). In both IRENA (2014a) and IRENA (2014b ) several regional profiles for hydro projects are presented, but from the IRENA database, the unexploited potential was used and condensed to estimate the hydro resource availability for the 18 regions of the model.

Rafael Garaffa at 20:32, 20 February 2019

2019-02-20T20:32:59Z

← Older revision		Revision as of 22:32, 20 February 2019
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	\|DocumentationCategory=Non-biomass renewables		\|DocumentationCategory=Non-biomass renewables
	}}		}}

			Solar and Wind energy resources were estimated from data mostly from NREL (2015), with additional information from WEC (2013) and NREL (2015b, 2015c), especially for cost estimation.

			For solar resource the supply curve introduced in the model was based on solar radiance itself, instead of on electricity or power. Additionally, in this model resources are split in four steps of increasing capacity factor.

			For wind resources the capacity factor is split in offshore and onshore and the distance to major consumers and to the coastline are considered. This is important to generate better supply curves for energy resources, since the optimum decision from the model may be to use a lower capacity factor that is closer to the end consumer, depending on the costs associated

			In the COFFEE model, wind resource was estimated considering 12 step curves for and 27 step discrete curves were created combining capacity factor, distance to shore and water depth for onshore and offshore, respectively.

Rineke Oostenrijk: Edited automatically from page TEA setup.

2018-12-13T11:28:31Z

Edited automatically from page TEA setup.

New page

{{ModelDocumentationTemplate
|IsDocumentationOf=TEA
|DocumentationCategory=Non-biomass renewables
}}