Technological change in energy - REMIND-MAgPIE - Revision history

Rineke Oostenrijk: Text replacement - "REMIND" to "REMIND-MAgPIE"

2021-11-21T13:34:24Z

Text replacement - "REMIND" to "REMIND-MAgPIE"

← Older revision		Revision as of 15:34, 21 November 2021
Line 1:		Line 1:
	{{ModelDocumentationTemplate		{{ModelDocumentationTemplate
	\|IsEmpty=No		\|IsEmpty=No
	\|IsDocumentationOf=REMIND		\|IsDocumentationOf=REMIND-MAgPIE
	\|DocumentationCategory=Technological change in energy		\|DocumentationCategory=Technological change in energy
	}}		}}
	REMIND assumes endogenous technological change through learning-by-doing for wind and solar power, electric (BEV) and fuel cell vehicle (FCV) technologies, as well as variable renewable energy (VRE) storage, through global learning curves and internalized spillovers. The specific investment costs for wind, solar PV, and solar CSP decrease by 12, 20, and 9%, respectively, for each doubling of cumulated capacity. The capital costs of the generalized storage units for VRE, as well as of advanced vehicle technologies (BEV, FCV), decrease with a 10% learning rate. REMIND reduces learning rates as capacities increase such that the investment costs asymptotically approach endogenously prescribed floor costs.		REMIND-MAgPIE assumes endogenous technological change through learning-by-doing for wind and solar power, electric (BEV) and fuel cell vehicle (FCV) technologies, as well as variable renewable energy (VRE) storage, through global learning curves and internalized spillovers. The specific investment costs for wind, solar PV, and solar CSP decrease by 12, 20, and 9%, respectively, for each doubling of cumulated capacity. The capital costs of the generalized storage units for VRE, as well as of advanced vehicle technologies (BEV, FCV), decrease with a 10% learning rate. REMIND-MAgPIE reduces learning rates as capacities increase such that the investment costs asymptotically approach endogenously prescribed floor costs.

	For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan <ref>Sullivan P, Krey V, Riahi K (2013) Impacts of considering electric sector variability and reliability in the MESSAGE model. Energy Strategy Reviews 1:157–163. doi: 10.1016/j.esr.2013.01.001)</ref>.		For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan <ref>Sullivan P, Krey V, Riahi K (2013) Impacts of considering electric sector variability and reliability in the MESSAGE model. Energy Strategy Reviews 1:157–163. doi: 10.1016/j.esr.2013.01.001)</ref>.

	The techno-economic parameters of power technologies used in the model are given in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 2 Techno-economic characteristics of technologies based on exhaustible energy sources and biomass.] for fuel-based technologies and in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 3 echno-economic characteristics of technologies based on non-biomass renewable energy sources.] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"		The techno-economic parameters of power technologies used in the model are given in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND-MAgPIE Table 2 Techno-economic characteristics of technologies based on exhaustible energy sources and biomass.] for fuel-based technologies and in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND-MAgPIE Table 3 echno-economic characteristics of technologies based on non-biomass renewable energy sources.] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"

	As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.		As discussed in Section "Macro-economy", REMIND-MAgPIE represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.
	REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").		REMIND-MAgPIE represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").

Mathijs Harmsen: Mathijs Harmsen moved page Technological change in energy - REMIND to Technological change in energy - REMIND-MAgPIE without leaving a redirect: Text replacement - "REMIND" to "REMIND-MAgPIE"

2021-11-18T12:14:06Z

Mathijs Harmsen moved page Technological change in energy - REMIND to Technological change in energy - REMIND-MAgPIE without leaving a redirect: Text replacement - "REMIND" to "REMIND-MAgPIE"

← Older revision

Revision as of 14:14, 18 November 2021

Laura Delsa at 16:37, 14 March 2017

2017-03-14T16:37:57Z

← Older revision		Revision as of 18:37, 14 March 2017
Line 8:		Line 8:
	For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan <ref>Sullivan P, Krey V, Riahi K (2013) Impacts of considering electric sector variability and reliability in the MESSAGE model. Energy Strategy Reviews 1:157–163. doi: 10.1016/j.esr.2013.01.001)</ref>.		For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan <ref>Sullivan P, Krey V, Riahi K (2013) Impacts of considering electric sector variability and reliability in the MESSAGE model. Energy Strategy Reviews 1:157–163. doi: 10.1016/j.esr.2013.01.001)</ref>.

	The techno-economic parameters of power technologies used in the model are given in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 2 Techno-economic characteristics of technologies based on exhaustible energy sources and biomass (Iwasaki 2003; Hamelinck 2004; Bauer 2005; Ansolabehere et al. 2007; Gül et al. 2007; Ragettli 2007; Schulz 2007; Uddin and Barreto 2007; Rubin et al. 2007; Takeshita and Yamaji 2008; Brown et al. 2009; Klimantos et al. 2009; Chen and Rubin 2009).] for fuel-based technologies and in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 3 echno-economic characteristics of technologies based on non-biomass renewable energy sources ~~(Neij et al. 2003; Nitsch et al. 2004; IEA 2007a; Junginger et al. 2008; Pietzcker et al. 2014)~~.] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"		The techno-economic parameters of power technologies used in the model are given in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 2 Techno-economic characteristics of technologies based on exhaustible energy sources and biomass.] for fuel-based technologies and in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 3 echno-economic characteristics of technologies based on non-biomass renewable energy sources.] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"

	As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.		As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.

Laura Delsa at 14:09, 3 February 2017

2017-02-03T14:09:46Z

← Older revision		Revision as of 16:09, 3 February 2017
Line 12:		Line 12:
	As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.		As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.
	REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").		REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").

Laura Delsa at 14:09, 3 February 2017

2017-02-03T14:09:33Z

← Older revision		Revision as of 16:09, 3 February 2017
Line 12:		Line 12:
	As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.		As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.
	REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").		REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").












			<references />

Laura Delsa at 13:48, 3 February 2017

2017-02-03T13:48:10Z

← Older revision		Revision as of 15:48, 3 February 2017
Line 6:		Line 6:
	REMIND assumes endogenous technological change through learning-by-doing for wind and solar power, electric (BEV) and fuel cell vehicle (FCV) technologies, as well as variable renewable energy (VRE) storage, through global learning curves and internalized spillovers. The specific investment costs for wind, solar PV, and solar CSP decrease by 12, 20, and 9%, respectively, for each doubling of cumulated capacity. The capital costs of the generalized storage units for VRE, as well as of advanced vehicle technologies (BEV, FCV), decrease with a 10% learning rate. REMIND reduces learning rates as capacities increase such that the investment costs asymptotically approach endogenously prescribed floor costs.		REMIND assumes endogenous technological change through learning-by-doing for wind and solar power, electric (BEV) and fuel cell vehicle (FCV) technologies, as well as variable renewable energy (VRE) storage, through global learning curves and internalized spillovers. The specific investment costs for wind, solar PV, and solar CSP decrease by 12, 20, and 9%, respectively, for each doubling of cumulated capacity. The capital costs of the generalized storage units for VRE, as well as of advanced vehicle technologies (BEV, FCV), decrease with a 10% learning rate. REMIND reduces learning rates as capacities increase such that the investment costs asymptotically approach endogenously prescribed floor costs.

	For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan ~~et al~~. (2013).		For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan <ref>Sullivan P, Krey V, Riahi K (2013) Impacts of considering electric sector variability and reliability in the MESSAGE model. Energy Strategy Reviews 1:157–163. doi: 10.1016/j.esr.2013.01.001)</ref>.

	The techno-economic parameters of power technologies used in the model are given in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 2 Techno-economic characteristics of technologies based on exhaustible energy sources and biomass (Iwasaki 2003; Hamelinck 2004; Bauer 2005; Ansolabehere et al. 2007; Gül et al. 2007; Ragettli 2007; Schulz 2007; Uddin and Barreto 2007; Rubin et al. 2007; Takeshita and Yamaji 2008; Brown et al. 2009; Klimantos et al. 2009; Chen and Rubin 2009).] for fuel-based technologies and in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 3 echno-economic characteristics of technologies based on non-biomass renewable energy sources (Neij et al. 2003; Nitsch et al. 2004; IEA 2007a; Junginger et al. 2008; Pietzcker et al. 2014).] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"		The techno-economic parameters of power technologies used in the model are given in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 2 Techno-economic characteristics of technologies based on exhaustible energy sources and biomass (Iwasaki 2003; Hamelinck 2004; Bauer 2005; Ansolabehere et al. 2007; Gül et al. 2007; Ragettli 2007; Schulz 2007; Uddin and Barreto 2007; Rubin et al. 2007; Takeshita and Yamaji 2008; Brown et al. 2009; Klimantos et al. 2009; Chen and Rubin 2009).] for fuel-based technologies and in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 3 echno-economic characteristics of technologies based on non-biomass renewable energy sources (Neij et al. 2003; Nitsch et al. 2004; IEA 2007a; Junginger et al. 2008; Pietzcker et al. 2014).] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"

Laura Delsa at 15:17, 1 February 2017

2017-02-01T15:17:52Z

← Older revision		Revision as of 17:17, 1 February 2017
Line 8:		Line 8:
	For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan et al. (2013).		For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan et al. (2013).

	The techno-economic parameters of power technologies used in the model are given in Table 2 Techno-economic characteristics of technologies based on exhaustible energy sources and biomass (Iwasaki 2003; Hamelinck 2004; Bauer 2005; Ansolabehere et al. 2007; Gül et al. 2007; Ragettli 2007; Schulz 2007; Uddin and Barreto 2007; Rubin et al. 2007; Takeshita and Yamaji 2008; Brown et al. 2009; Klimantos et al. 2009; Chen and Rubin 2009).[http://themasites.pbl.nl/models/advance/~~images/9/9a~~/~~Remind_Table_5.PNG] for fuel~~-~~based technologies and in~~ Table 3 echno-economic characteristics of technologies based on non-biomass renewable energy sources (Neij et al. 2003; Nitsch et al. 2004; IEA 2007a; Junginger et al. 2008; Pietzcker et al. 2014).~~[http://themasites.pbl.nl/models/advance/images/9/9f/Remind_Table_6.PNG~~] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"		The techno-economic parameters of power technologies used in the model are given in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 2 Techno-economic characteristics of technologies based on exhaustible energy sources and biomass (Iwasaki 2003; Hamelinck 2004; Bauer 2005; Ansolabehere et al. 2007; Gül et al. 2007; Ragettli 2007; Schulz 2007; Uddin and Barreto 2007; Rubin et al. 2007; Takeshita and Yamaji 2008; Brown et al. 2009; Klimantos et al. 2009; Chen and Rubin 2009).] for fuel-based technologies and in [http://themasites.pbl.nl/models/advance/index.php/Electricity_-_REMIND Table 3 echno-economic characteristics of technologies based on non-biomass renewable energy sources (Neij et al. 2003; Nitsch et al. 2004; IEA 2007a; Junginger et al. 2008; Pietzcker et al. 2014).] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"

	As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.		As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.
	REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").		REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").

Laura Delsa at 14:35, 1 February 2017

2017-02-01T14:35:31Z

← Older revision		Revision as of 16:35, 1 February 2017
Line 8:		Line 8:
	For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan et al. (2013).		For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan et al. (2013).

	The techno-economic parameters of power technologies used in the model are given in Table 2[http://themasites.pbl.nl/models/advance/images/9/9a/Remind_Table_5.PNG] for fuel-based technologies and in Table 3[http://themasites.pbl.nl/models/advance/images/9/9f/Remind_Table_6.PNG] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"		The techno-economic parameters of power technologies used in the model are given in Table 2 Techno-economic characteristics of technologies based on exhaustible energy sources and biomass (Iwasaki 2003; Hamelinck 2004; Bauer 2005; Ansolabehere et al. 2007; Gül et al. 2007; Ragettli 2007; Schulz 2007; Uddin and Barreto 2007; Rubin et al. 2007; Takeshita and Yamaji 2008; Brown et al. 2009; Klimantos et al. 2009; Chen and Rubin 2009).[http://themasites.pbl.nl/models/advance/images/9/9a/Remind_Table_5.PNG] for fuel-based technologies and in Table 3 echno-economic characteristics of technologies based on non-biomass renewable energy sources (Neij et al. 2003; Nitsch et al. 2004; IEA 2007a; Junginger et al. 2008; Pietzcker et al. 2014).[http://themasites.pbl.nl/models/advance/images/9/9f/Remind_Table_6.PNG] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"

	As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.		As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.
	REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").		REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").

Laura Delsa at 14:33, 1 February 2017

2017-02-01T14:33:28Z

← Older revision		Revision as of 16:33, 1 February 2017
Line 8:		Line 8:
	For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan et al. (2013).		For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan et al. (2013).

	The techno-economic parameters of power technologies used in the model are given in Table 5[http://themasites.pbl.nl/models/advance/images/9/9a/Remind_Table_5.PNG] for fuel-based technologies and in Table 6[http://themasites.pbl.nl/models/advance/images/9/9f/Remind_Table_6.PNG] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"		The techno-economic parameters of power technologies used in the model are given in Table 2[http://themasites.pbl.nl/models/advance/images/9/9a/Remind_Table_5.PNG] for fuel-based technologies and in Table 3[http://themasites.pbl.nl/models/advance/images/9/9f/Remind_Table_6.PNG] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"

	As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.		As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.
	REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").		REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").

Laura Delsa at 13:54, 1 February 2017

2017-02-01T13:54:32Z

← Older revision		Revision as of 15:54, 1 February 2017
Line 8:		Line 8:
	For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan et al. (2013).		For variable renewable energies, we implemented two parameterized cost markup functions for storage and long-distance transmission grids - see Section "Electricity". To represent the general need for flexibility even in a thermal power system, we included a further flexibility constraint based on Sullivan et al. (2013).

	The techno-economic parameters of power technologies used in the model are given in Table 5 for fuel-based technologies and in Table 6 for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"		The techno-economic parameters of power technologies used in the model are given in Table 5[http://themasites.pbl.nl/models/advance/images/9/9a/Remind_Table_5.PNG] for fuel-based technologies and in Table 6[http://themasites.pbl.nl/models/advance/images/9/9f/Remind_Table_6.PNG] for non-biomass renewables. For wind, solar and hydro, capacity factors depend on grades, see Section "Non-biomass renewables"

	As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.		As discussed in Section "Macro-economy", REMIND represents energy efficiency improvements via an exogenously prescribed increase in the efficiency parameters of the CES production function, as well as price induced reductions in energy demand and changes in technology choice.
	REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").		REMIND represents investment dynamics in terms of capital motion equations, vintages for energy supply technologies and adjustment costs related to the acceleration of capacity expansion (for further details see Section "Energy conversion").