Non-biomass renewables - MESSAGE-GLOBIOM

Model Documentation - MESSAGE-GLOBIOM
Model scope and methods - MESSAGE-GLOBIOM Model concept, solver and details - MESSAGE-GLOBIOM Temporal dimension - MESSAGE-GLOBIOM Spatial dimension - MESSAGE-GLOBIOM Policy - MESSAGE-GLOBIOM Socio-economic drivers - MESSAGE-GLOBIOM Population - MESSAGE-GLOBIOM Economic activity - MESSAGE-GLOBIOM Macro-economy - MESSAGE-GLOBIOM Trade - MESSAGE-GLOBIOM Energy - MESSAGE-GLOBIOM Energy resource endowments - MESSAGE-GLOBIOM Fossil energy resources - MESSAGE-GLOBIOM Uranium and other fissile resources - MESSAGE-GLOBIOM Bioenergy - MESSAGE-GLOBIOM Non-biomass renewables - MESSAGE-GLOBIOM Energy conversion - MESSAGE-GLOBIOM Electricity - MESSAGE-GLOBIOM Heat - MESSAGE-GLOBIOM Gaseous fuels - MESSAGE-GLOBIOM Liquid fuels - MESSAGE-GLOBIOM Grid, pipelines and other infrastructure - MESSAGE-GLOBIOM Energy end-use - MESSAGE-GLOBIOM Transport - MESSAGE-GLOBIOM Residential and commercial sectors - MESSAGE-GLOBIOM Industrial sector - MESSAGE-GLOBIOM Energy demand - MESSAGE-GLOBIOM Technological change in energy - MESSAGE-GLOBIOM Land-use - MESSAGE-GLOBIOM Emissions - MESSAGE-GLOBIOM GHGs - MESSAGE-GLOBIOM Pollutants and non-GHG forcing agents - MESSAGE-GLOBIOM Climate - MESSAGE-GLOBIOM Modelling of climate indicators - MESSAGE-GLOBIOM Non-climate sustainability dimension - MESSAGE-GLOBIOM Air pollution and health - MESSAGE-GLOBIOM Water - MESSAGE-GLOBIOM Other sustainability dimensions - MESSAGE-GLOBIOM Appendices - MESSAGE-GLOBIOM References - MESSAGE-GLOBIOM
Corresponding documentation
AIM-Hub BLUES C3IAM COFFEE-TEA DNE21+ GCAM GRACE IFs MESSAGE-GLOBIOM POLES PROMETHEUS REMIND-MAgPIE TIAM-UCL
Previous versions
Archive of MESSAGE-GLOBIOM version 1.0
Model information
Model link	https://docs.messageix.org http://data.ene.iiasa.ac.at/message-globiom/ https://github.com/iiasa/message ix https://github.com/iiasa/ixmp
Institution	International Institute for Applied Systems Analysis (IIASA), Austria, http://data.ene.iiasa.ac.at.
Solution concept	General equilibrium (closed economy)
Solution method	Optimization
Anticipation

<xr id="tab:MESSAGE-GLOBIOM_depl"/> shows the assumed total potentials of non-biomass renewable energy deployment (by resource type) in the MESSAGE model. In addition, the assumptions are compared with technical potential estimates from the Global Energy Assessment (Rogner et al., 2012 MSG-GLB_rogner_chapter_2012). In this context, it is important to note that typical MESSAGE scenarios do not consider the full technical potential of renewable energy resources, but rather only a subset of those potentials, owing to additional constraints (e.g., sustainability criteria, technology diffusion and systems integration issues, and other economic considerations) that may not be fully captured within the model. These constraints may lead to a significant reduction of the technical potential.

<figtable id="tab:MESSAGE-GLOBIOM_depl">

Assumed global non-biomass renewable energy deployment potentials in the MESSAGE-GLOBIOM model. Estimates from the Global Energy Assessment (Rogner et al., 2012 MSG-GLB_rogner_chapter_2012) also added for comparison

Source	MESSAGE	Rogner et al., 2012 MSG-GLB_rogner_chapter_2012
	Deployment Potential [EJ/yr]	Technical Potential [EJ/yr]
Hydro	38	50 - 60
Wind (on-/offshore)	689/287	1250 - 2250
Solar PV	6064	62,000 - 280,000
CSP	2132	same as Solar PV above
Geothermal	23	810 - 1400

</figtable>

Notes: MESSAGE-GLOBIOM renewable energy potentials are based on Pietzcker et al. (2014) MSG-GLB_pietzcker_solar_2014, Eurek et al. (in review) MSG-GLB_eurek_wind_2016, Christiansson (1995) MSG-GLB_christiansson_diffusion_1995, and Rogner et al (2012) MSG-GLB_rogner_chapter_2012. The potentials for non-combustible renewable energy sources are specified in terms of the electricity or heat that can be produced by specific technologies (i.e., from a secondary energy perspective). By contrast, the technical potentials from Rogner et al (2012) MSG-GLB_rogner_chapter_2012 refer to the flows of energy that could become available as inputs for technology conversion. So for example, the technical potential for wind is given as the kinetic energy available for wind power generation, whereas the deployment potential would only be the electricity that could be generated by the wind turbines.

Regional resource potentials for solar and wind are classified according to resource quality (annual capacity factor) based on Pietzcker et al. (2014 MSG-GLB_pietzcker_solar_2014) and Eurek et al. (in review MSG-GLB_eurek_wind_2016). Regional resource potentials as implemented into MESSAGE-GLOBIOM are provided by region and capacity factor for solar PV, concentrating solar power (CSP), and onshore/offshore wind in Johnson et al. (in review MSG-GLB_johnson_vre_2016). The physical potential of these sources is assumed to be the same across all SSPs. <xr id="tab:MESSAGE-GLOBIOM_pv"/>, <xr id="tab:MESSAGE-GLOBIOM_csp"/>, <xr id="tab:MESSAGE-GLOBIOM_onshorewind"/>, <xr id="tab:MESSAGE-GLOBIOM_offshorewind"/> show the resource potential for solar PV, CSP, on- and offshore wind respectively. For wind, <xr id="tab:MESSAGE-GLOBIOM_capfactonshore"/> and <xr id="tab:MESSAGE-GLOBIOM_capfactoffshore"/> list the capacity factors corresponding to the wind classes used in the resource tables. It is important to note that part of the resource that is useable at economically competitive costs is assumed to differ widely (see Section Energy Conversion of MESSAGE-GLOBIOM).

<figtable id="tab:MESSAGE-GLOBIOM_pv">

Resource potential (EJ) by region and capacity factor for solar photovoltaic (PV) technology (Johnson et al. in review MSG-GLB_johnson_vre_2016). For a description of each of the regions represented in the table, see Spatial dimension of MESSAGE-GLOBIOM

	Capacity Factor (fraction per year)
	0.28	0.21	0.20	0.19	0.18	0.17	0.15	0.14
AFR	0.0	1.1	46.5	176.6	233.4	218.2	169.9	61.9
CPA	0.0	0.0	0.0	10.3	194.3	315.5	159.4	41.9
EEU	0.0	0.0	0.0	0.0	0.0	0.0	0.1	1.0
FSU	0.0	0.0	0.0	0.2	2.8	23.6	94.9	116.6
LAM	0.1	4.9	49.4	165.6	157.5	167.4	81.4	48.5
MEA	0.2	3.1	100.8	533.6	621.8	310.1	75.3	14.5
NAM	0.0	0.3	24.3	140.4	131.0	116.3	155.7	106.4
PAO	0.0	0.0	0.1	2.2	53.1	226.4	311.2	158.9
PAS	0.0	0.0	0.0	0.2	0.8	17.0	31.2	12.8
SAS	0.0	0.0	6.1	42.7	67.2	82.3	23.7	4.1
WEU	0.0	0.1	0.2	3.0	12.8	39.4	58.3	33.3
Global	0.3	9.6	227.4	1074.7	1474.6	1516.3	1160.9	600.0

</figtable>

<figtable id="tab:MESSAGE-GLOBIOM_csp">

Resource potential (EJ) by region and capacity factor for concentrating solar power (CSP) technologies with solar multiples (SM) of 1 and 3 (Johnson et al. in review MSG-GLB_johnson_vre_2016)

	Capacity Factor (fraction of year)
SM1	0.27	0.25	0.23	0.22	0.20	0.18	0.17	0.15
SM3	0.75	0.68	0.64	0.59	0.55	0.50	0.46	0.41
AFR	0.0	3.6	19.0	81.6	106.7	62.8	59.6	37.8
CPA	0.0	0.0	0.0	0.0	0.0	0.3	11.5	53.0
EEU	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
FSU	0.0	0.0	0.0	0.0	0.0	0.1	0.4	6.1
LAM	0.0	2.0	7.0	11.8	29.3	57.1	56.8	53.5
MEA	0.1	3.7	24.8	122.4	155.3	144.5	68.4	34.0
NAM	0.0	0.0	0.0	6.3	19.7	20.2	29.6	43.2
PAO	0.0	3.0	75.1	326.9	158.3	140.4	40.2	10.2
PAS	0.0	0.0	0.0	0.0	0.0	0.0	0.1	0.6
SAS	0.0	0.0	0.0	0.1	3.9	8.7	16.1	9.8
WEU	0.0	0.0	0.0	0.0	0.2	0.7	2.4	3.0
Global	0.1	12.3	126.0	549.2	473.3	434.8	285.0	251.3

</figtable>

<figtable id="tab:MESSAGE-GLOBIOM_onshorewind">

Resource potential (EJ) by region and wind class for onshore wind (Johnson et al. in review MSG-GLB_johnson_vre_2016)

	Wind Class
	3	4	5	6	7	8+
AFR	38.2	21.3	13.4	6.8	2.6	2.1
CPA	24.7	11.4	5.4	2.6	0.3	0.0
EEU	6.1	5.7	0.3	0.0	0.0	0.0
FSU	52.3	83.8	5.8	0.8	0.0	0.0
LAM	33.5	15.9	9.6	5.7	3.9	3.7
MEA	56.1	22.2	6.0	2.1	0.9	0.3
NAM	28.6	66.4	23.7	1.5	0.4	0.0
PAO	18.9	18.8	3.6	1.4	1.8	0.5
PAS	5.2	2.9	0.8	0.2	0.0	0.0
SAS	12.3	7.9	2.4	1.6	0.9	0.3
WEU	16.1	10.5	6.6	8.2	3.7	0.6
World	292.1	266.8	77.5	30.9	14.3	7.5

</figtable>

<figtable id="tab:MESSAGE-GLOBIOM_capfactonshore">

Capacity factor by region and wind class for onshore wind (Johnson et al. in review MSG-GLB_johnson_vre_2016)

	Wind Class
	3	4	5	6	7	8+
AFR	0.24	0.28	0.32	0.36	0.40	0.45
CPA	0.24	0.28	0.32	0.36	0.38	0.45
EEU	0.24	0.27	0.31	0.36	0.38	0.45
FSU	0.24	0.28	0.31	0.35	0.38	0.45
LAM	0.24	0.28	0.32	0.36	0.39	0.46
MEA	0.24	0.27	0.32	0.35	0.39	0.45
NAM	0.24	0.28	0.31	0.36	0.39	0.45
PAO	0.24	0.28	0.32	0.36	0.40	0.43
PAS	0.24	0.27	0.32	0.35	0.40	0.45
SAS	0.24	0.27	0.32	0.36	0.39	0.42
WEU	0.24	0.28	0.32	0.36	0.39	0.43

</figtable>

<figtable id="tab:MESSAGE-GLOBIOM_offshorewind">

Resource potential (EJ) by region and wind class for offshore wind (Johnson et al. in review MSG-GLB_johnson_vre_2016)

	Wind Class
	3	4	5	6	7	8+
AFR	3.1	2.4	2.0	2.0	1.1	1.7
CPA	3.5	4.3	2.6	0.9	1.3	0.1
EEU	0.7	0.6	1.0	0.0	0.0	0.0
FSU	1.8	4.6	14.2	13.3	4.3	0.7
LAM	7.1	7.3	5.3	2.7	2.6	5.9
MEA	3.2	0.9	0.8	0.9	0.6	0.9
NAM	4.5	18.2	24.0	16.0	7.3	2.1
PAO	5.8	11.2	15.3	9.8	2.6	2.5
PAS	5.3	6.6	4.7	1.5	0.1	0.0
SAS	1.9	0.9	0.6	0.5	0.0	0.0
WEU	3.5	4.7	8.8	12.9	10.3	0.9
World	40.4	61.5	79.4	60.5	30.3	14.8

</figtable>

<figtable id="tab:MESSAGE-GLOBIOM_capfactoffshore">

Capacity factor by region and wind class for offshore wind (Johnson et al. in review MSG-GLB_johnson_vre_2016)

	Wind Class
	3	4	5	6	7	8+
AFR	0.24	0.28	0.32	0.36	0.41	0.47
CPA	0.24	0.28	0.32	0.36	0.40	0.42
EEU	0.24	0.29	0.32	0.34	0.40	0.42
FSU	0.25	0.28	0.32	0.35	0.39	0.43
LAM	0.24	0.28	0.32	0.36	0.40	0.49
MEA	0.24	0.28	0.32	0.36	0.40	0.45
NAM	0.25	0.28	0.32	0.36	0.40	0.43
PAO	0.24	0.28	0.32	0.36	0.40	0.47
PAS	0.24	0.28	0.32	0.35	0.39	0.42
SAS	0.24	0.27	0.32	0.36	0.40	0.42
WEU	0.24	0.28	0.32	0.36	0.40	0.42

</figtable>