Non-biomass renewables - COFFEE-TEA: Difference between revisions
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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. | |||
Revision as of 21:33, 20 February 2019
Note: The documentation of COFFEE-TEA is 'under review' and is not yet 'published'!| Corresponding documentation | |
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| Previous versions | |
| Model information | |
| Model link | |
| Institution | COPPE/UFRJ (Cenergia), Brazil, http://www.cenergialab.coppe.ufrj.br/. |
| Solution concept | General equilibrium (closed economy) |
| Solution method | The COFFEE model is solved through Linear Programming (LP). The TEA model is formulated as a mixed complementary problem (MCP) and is solved through Mathematical Programming System for General Equilibrium -- MPSGE within GAMS using the PATH solver. |
| Anticipation | |
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.
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.