Energy conversion - MESSAGE-GLOBIOM - Revision history

Rineke Oostenrijk: Text replacement - "|QQQ " to ""

2020-06-23T15:15:07Z

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	Energy technologies are characterized by numerical model inputs describing their economic (e.g., investment costs, fixed and variable operation and maintenance costs), technical (e.g., conversion efficiencies), ecological (e.g., GHG and pollutant emissions), and sociopolitical characteristics. An example for the sociopolitical situation in a world region would be the decision by a country or world region to ban certain types of power plants (e.g., nuclear plants). Model input data reflecting this situation would be upper bounds of zero for these technologies or, equivalently, their omission from the data set for this region altogether.		Energy technologies are characterized by numerical model inputs describing their economic (e.g., investment costs, fixed and variable operation and maintenance costs), technical (e.g., conversion efficiencies), ecological (e.g., GHG and pollutant emissions), and sociopolitical characteristics. An example for the sociopolitical situation in a world region would be the decision by a country or world region to ban certain types of power plants (e.g., nuclear plants). Model input data reflecting this situation would be upper bounds of zero for these technologies or, equivalently, their omission from the data set for this region altogether.

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	Energy technologies are characterized by numerical model inputs describing their economic (e.g., investment costs, fixed and variable operation and maintenance costs), technical (e.g., conversion efficiencies), ecological (e.g., GHG and pollutant emissions), and sociopolitical characteristics. An example for the sociopolitical situation in a world region would be the decision by a country or world region to ban certain types of power plants (e.g., nuclear plants). Model input data reflecting this situation would be upper bounds of zero for these technologies or, equivalently, their omission from the data set for this region altogether.		Energy technologies are characterized by numerical model inputs describing their economic (e.g., investment costs, fixed and variable operation and maintenance costs), technical (e.g., conversion efficiencies), ecological (e.g., GHG and pollutant emissions), and sociopolitical characteristics. An example for the sociopolitical situation in a world region would be the decision by a country or world region to ban certain types of power plants (e.g., nuclear plants). Model input data reflecting this situation would be upper bounds of zero for these technologies or, equivalently, their omission from the data set for this region altogether.

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2020-06-23T15:02:02Z

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2020-06-23T14:55:47Z

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Johanna Zilliacus at 14:55, 30 August 2016

2016-08-30T14:55:52Z

Show changes

Johanna Zilliacus: /* Systems Integration and Reliability */

2016-08-24T13:33:15Z

Systems Integration and Reliability

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	<div style=" overflow: auto;">		<div style=" overflow: auto;">
	<figure id="fig:MESSAGE-GLOBIOM_windcap">		<figure id="fig:MESSAGE-GLOBIOM_windcap">
	[[File:~~wind_cv~~.png\|left\|600px\|thumb\|<caption>Parameterization of Wind Capacity Value</caption>]]		[[File:35815449.png\|left\|600px\|thumb\|<caption>Parameterization of Wind Capacity Value</caption>]]
	</figure>		</figure>
	</div>		</div>

Johanna Zilliacus at 12:27, 24 August 2016

2016-08-24T12:27:42Z

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	* Inconvenience costs which are specified only for end-use technologies (e.g. cook stoves)		* Inconvenience costs which are specified only for end-use technologies (e.g. cook stoves)

	The specific technologies represented in various parts of the energy conversion sector are discussed in the following sections on [[Energy_conversion_-_MESSAGE-GLOBIOM#Electricity\|Electricity]], [[Energy_conversion_-_MESSAGE-GLOBIOM#Heat\|Heat]], [[Energy_conversion_-_MESSAGE-GLOBIOM#Other_conversion\|Other conversion]], and ~~'''ref:`grid`'''~~ below.		The specific technologies represented in various parts of the energy conversion sector are discussed in the following sections on [[Energy_conversion_-_MESSAGE-GLOBIOM#Electricity\|Electricity]], [[Energy_conversion_-_MESSAGE-GLOBIOM#Heat\|Heat]], [[Energy_conversion_-_MESSAGE-GLOBIOM#Other_conversion\|Other conversion]], and [[Energy_conversion_-_MESSAGE-GLOBIOM#Grid.2C_Infrastructure_and_System_Reliability\|Grid, Infrastructure and System Reliability]] below.


	==Electricity==		==Electricity==
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	Most thermal power plants offer the option of coupled heat production (CHP, see <xr id="tab:MESSAGE-GLOBIOM_elec"/>). This option is modeled as a passout turbine via a penalty on the electricity generation efficiency. In addition to the main electricity generation technologies described in this section, also the co-generation of electricity in conversion technologies primarily devoted to producing non-electric energy carriers (e.g., synthetic liquid fuels) is included in MESSAGE (see section on ''':ref:other''').		Most thermal power plants offer the option of coupled heat production (CHP, see <xr id="tab:MESSAGE-GLOBIOM_elec"/>). This option is modeled as a passout turbine via a penalty on the electricity generation efficiency. In addition to the main electricity generation technologies described in this section, also the co-generation of electricity in conversion technologies primarily devoted to producing non-electric energy carriers (e.g., synthetic liquid fuels) is included in MESSAGE (see section on ''':ref:other''').


	<figtable id="tab:MESSAGE-GLOBIOM_elec">		<figtable id="tab:MESSAGE-GLOBIOM_elec">
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	</figure>		</figure>
	</div>		</div>


	In <xr id="fig:MESSAGE-GLOBIOM_ther"/>, the black ranges show historical cost ranges for 2005. Green, blue, and red ranges show cost ranges in 2100 for SSP1, SSP2, and SSP3, respectively (see descriptions of the SSP narratives in section ''':ref:narratives'''). Global values are represented by solid ranges. Values in the global South are represented by dashed ranges. The diamonds show the costs in the “North America” region. CCS – Carbon Capture and Storage; IGCC – Integrated gasification combined cycles; ST – Steam turbine; CT – Combustion turbine; CCGT – Combined cycle gas turbine (Fricko et al., 2016 [[CiteRef::MSG-GLB_fricko_marker_2016]]).		In <xr id="fig:MESSAGE-GLOBIOM_ther"/>, the black ranges show historical cost ranges for 2005. Green, blue, and red ranges show cost ranges in 2100 for SSP1, SSP2, and SSP3, respectively (see descriptions of the SSP narratives in section ''':ref:narratives'''). Global values are represented by solid ranges. Values in the global South are represented by dashed ranges. The diamonds show the costs in the “North America” region. CCS – Carbon Capture and Storage; IGCC – Integrated gasification combined cycles; ST – Steam turbine; CT – Combustion turbine; CCGT – Combined cycle gas turbine (Fricko et al., 2016 [[CiteRef::MSG-GLB_fricko_marker_2016]]).
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	</div>		</div>


	In <xr id="fig:MESSAGE-GLOBIOM_nonth"/>, the black ranges show historical cost ranges for 2005. Green, blue, and red ranges show cost ranges in 2100 for SSP1, SSP2, and SSP3, respectively. Global values are represented by solid ranges. Values in the global South are represented by dashed ranges. The diamonds show the costs in the “North America” region. PV – Photovoltaic (Fricko et al., 2016 [[CiteRef::MSG-GLB_fricko_marker_2016]]).		In <xr id="fig:MESSAGE-GLOBIOM_nonth"/>, the black ranges show historical cost ranges for 2005. Green, blue, and red ranges show cost ranges in 2100 for SSP1, SSP2, and SSP3, respectively. Global values are represented by solid ranges. Values in the global South are represented by dashed ranges. The diamonds show the costs in the “North America” region. PV – Photovoltaic (Fricko et al., 2016 [[CiteRef::MSG-GLB_fricko_marker_2016]]).


	==Heat==		==Heat==
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	\|}		\|}
	</figtable>		</figtable>


	===Hydrogen Production===		===Hydrogen Production===
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	can be traded in liquified form, i.e. liquified natural gas (LNG) and liquid hydrogen, where liquefaction and re-gasification infrastructure is represented in addition to the actual		can be traded in liquified form, i.e. liquified natural gas (LNG) and liquid hydrogen, where liquefaction and re-gasification infrastructure is represented in addition to the actual
	transport process.		transport process.


	===Systems Integration and Reliability===		===Systems Integration and Reliability===
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	generation from that technology that is considered to be flexible or (if negative) the additional flexible generation required for each unit of generation from that technology. Load also		generation from that technology that is considered to be flexible or (if negative) the additional flexible generation required for each unit of generation from that technology. Load also
	has a parameter (a negative one) representing the amount of flexible energy the system requires solely to meet changes and uncertainty in load. <xr id="tab:MESSAGE-GLOBIOM_flex"/> below displays the parameters that were estimated using a unit-commitment model that commits and dispatches a fixed generation system at hourly resolution to meet load an ancilliary service requirements while hewing to generator and transmission operation limitations (Sullivan et al., 2013 [[CiteRef::MSG-GLB_sullivan_electric_2013]]). Technologies that were not included in the unit-commitment model (nuclear, H2 electrolysis, solar PV) have estimated coefficients.		has a parameter (a negative one) representing the amount of flexible energy the system requires solely to meet changes and uncertainty in load. <xr id="tab:MESSAGE-GLOBIOM_flex"/> below displays the parameters that were estimated using a unit-commitment model that commits and dispatches a fixed generation system at hourly resolution to meet load an ancilliary service requirements while hewing to generator and transmission operation limitations (Sullivan et al., 2013 [[CiteRef::MSG-GLB_sullivan_electric_2013]]). Technologies that were not included in the unit-commitment model (nuclear, H2 electrolysis, solar PV) have estimated coefficients.


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

Johanna Zilliacus at 12:23, 24 August 2016

2016-08-24T12:23:11Z

← Older revision		Revision as of 14:23, 24 August 2016
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	Grid, Infrastructure and System Reliability		==Grid, Infrastructure and System Reliability==

	===Energy Transmission and Distribution Infrastructure===		===Energy Transmission and Distribution Infrastructure===
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	transport process.		transport process.

	~~.. _syst_integration:~~

	==Systems Integration and Reliability==		===Systems Integration and Reliability===

	The MESSAGE framework includes a single annual time period characterized by average annual load and 11 geographic regions that span the globe. Seasonal and diurnal load curves and spatial		The MESSAGE framework includes a single annual time period characterized by average annual load and 11 geographic regions that span the globe. Seasonal and diurnal load curves and spatial

Johanna Zilliacus: /* == */

2016-08-24T11:51:39Z

← Older revision		Revision as of 13:51, 24 August 2016
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	Grid, Infrastructure and System Reliability		Grid, Infrastructure and System Reliability
	===~~=======================================~~
	Energy Transmission and Distribution Infrastructure		===Energy Transmission and Distribution Infrastructure===
	~~---------------------------------------------------~~
	Energy transport and distribution infrastructure is included in MESSAGE at a level relevant to represent the associated costs. Within regions the capital stock of transmission and		Energy transport and distribution infrastructure is included in MESSAGE at a level relevant to represent the associated costs. Within regions the capital stock of transmission and
	distribution infrastructure and its turnover is modeled for the following set of energy carriers:		distribution infrastructure and its turnover is modeled for the following set of energy carriers:
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	.. _syst_integration:		.. _syst_integration:


	==Systems Integration and Reliability==		==Systems Integration and Reliability==

Johanna Zilliacus at 10:22, 24 August 2016

2016-08-24T10:22:12Z

← Older revision		Revision as of 12:22, 24 August 2016
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	In <xr id="fig:MESSAGE-GLOBIOM_costind"/>, the black ranges show historical cost ranges for 2005. Green, blue, and red ranges show cost ranges in 2100 for SSP1, SSP2, and SSP3, respectively. Global values are represented by solid ranges. Values in the global South are represented by dashed ranges. The diamonds show the costs in the “North America” region. CCS – Carbon capture and storage; CTL – Coal to liquids; GTL – Gas to liquids; BTL – Biomass to liquids (Fricko et al., 2016 [[CiteRef::MSG-GLB_fricko_marker_2016]]).		In <xr id="fig:MESSAGE-GLOBIOM_costind"/>, the black ranges show historical cost ranges for 2005. Green, blue, and red ranges show cost ranges in 2100 for SSP1, SSP2, and SSP3, respectively. Global values are represented by solid ranges. Values in the global South are represented by dashed ranges. The diamonds show the costs in the “North America” region. CCS – Carbon capture and storage; CTL – Coal to liquids; GTL – Gas to liquids; BTL – Biomass to liquids (Fricko et al., 2016 [[CiteRef::MSG-GLB_fricko_marker_2016]]).


			Grid, Infrastructure and System Reliability
			==========================================
			Energy Transmission and Distribution Infrastructure
			---------------------------------------------------
			Energy transport and distribution infrastructure is included in MESSAGE at a level relevant to represent the associated costs. Within regions the capital stock of transmission and
			distribution infrastructure and its turnover is modeled for the following set of energy carriers:

			* electricity
			* district heat
			* natural gas
			* hydrogen

			For all solid (coal, biomass) and liquid energy carriers (oil products, biofuels, fossil synfuels) a simpler approach is taken and only transmission and distribution losses and costs
			are taken into account.

			Inter-regional energy transmission infrastructure, such as natural gas pipelines and high voltage electricity grids, are also represented between geographically adjacent regions.
			Solid and liquid fuel trade is, similar to the transmission and distribution within regions, modeled by taking into account distribution losses and costs. A special case are gases that
			can be traded in liquified form, i.e. liquified natural gas (LNG) and liquid hydrogen, where liquefaction and re-gasification infrastructure is represented in addition to the actual
			transport process.

			.. _syst_integration:


			==Systems Integration and Reliability==

			The MESSAGE framework includes a single annual time period characterized by average annual load and 11 geographic regions that span the globe. Seasonal and diurnal load curves and spatial
			issues such as transmission constraints or renewable resource heterogeneity are treated in a stylized way in the model. The reliability extension described below elevates the stylization
			of temporal resolution by introducing two concepts, peak reserve capacity and general-timescale flexibility, to the model (Sullivan et al., 2013 [[CiteRef::MSG-GLB_sullivan_electric_2013]]). To represent capacity reserves in MESSAGE, a requirement is defined that each region build sufficient firm generating capacity to maintain reliability through reasonable load and contingency events. As a proxy for complex system reliability metrics, a reserve margin-based metric was used, setting the capacity requirement at a multiple of average load, based on electric-system parameters. While many of the same issues apply to both electricity from wind and solar energy, the description below focuses on wind.

			Toward meeting the firm capacity requirement, conventional generating technologies contribute their nameplate generation capacity while variable renewables contribute a capacity value
			that declines as the market share of the technology increases. This reflects the fact that wind and solar generators do not always generate when needed, and that their output is generally
			self-correlated. In order to adjust wind capacity values for different levels of penetration, it was necessary to introduce a stepwise-linear supply curve for wind power (shown in the
			<xr id="fig:MESSAGE-GLOBIOM_windcap"/> below). Each bin covers a range of wind penetration levels as fraction of load and has discrete coefficients for the two constraints. The bins are predefined, and therefore are not able to allow, for example, resource diversification to increase capacity value at a given level of wind penetration.

			<div style=" overflow: auto;">
			<figure id="fig:MESSAGE-GLOBIOM_windcap">
			[[File:wind_cv.png\|left\|600px\|thumb\|<caption>Parameterization of Wind Capacity Value</caption>]]
			</figure>
			</div>

			The capacity value bins are independent of the wind supply curve bins that already existed in MESSAGE, which are based on quality of the wind resource. That supply curve is defined by
			absolute wind capacity built, not fraction of load; and the bins differ based on their annual average capacity factor, not capacity value. Solar PV is treated in a similar way as wind with the parameters obviously being different ones. In contrast, concentrating solar power (CSP) is modeled very much like dispatchable power plants in MESSAGE, because it is assumed to come with
			several hours of thermal storage, making it almost capable of running in baseload mode.

			In order to ensure adequate reserve dispatch, dynamic shadow prices are placed on capacity investments of intermittent technologies (e.g., wind and solar). The prices are a function of the cumulative installed capacity of the intermittent technologies, the ability for the convential power supply to act as reserve dispatch, and the demand-side reliability requirements. For instance, a large amount of storage capacity should, all else being equal, lower the shadow price for additional wind. Conversely, an inflexible, coal- or nuclear-heavy generating base should increase the cost of investment in wind by demanding additional expenditures in the form of natural gas or storage or improved demand-side management to maintain system reliability.

			Starting from the energy metric used in MESSAGE (electricity is considered as annual average load; there are no time-slices or load-curves), the flexibility requirement uses MWh of
			generation as its unit of note. The metric is inherently limited because operating reserves are often characterized by energy not-generated: a natural gas combustion turbine (gas-CT) that
			is standing by, ready to start-up at a moment’s notice; a combined-cycle plant operating below its peak output to enable ramping in the event of a surge in demand. Nevertheless, because
			there is generally a portion of generation associated with providing operating reserves (e.g. that on-call gas-CT plant will be called some fraction of the time), it is posited that using
			generated energy to gauge flexibility is a reasonable metric considering the simplifications that need to be made. Furthermore, ancillary services associated with ramping and peaking
			often do involve real energy generation, and variable renewable technologies generally increase the need for ramping.

			Electric-sector flexibility in MESSAGE is represented as follows: each generating technology is assigned a coefficient between -1 and 1 representing (if positive) the fraction of
			generation from that technology that is considered to be flexible or (if negative) the additional flexible generation required for each unit of generation from that technology. Load also
			has a parameter (a negative one) representing the amount of flexible energy the system requires solely to meet changes and uncertainty in load. <xr id="tab:MESSAGE-GLOBIOM_flex"/> below displays the parameters that were estimated using a unit-commitment model that commits and dispatches a fixed generation system at hourly resolution to meet load an ancilliary service requirements while hewing to generator and transmission operation limitations (Sullivan et al., 2013 [[CiteRef::MSG-GLB_sullivan_electric_2013]]). Technologies that were not included in the unit-commitment model (nuclear, H2 electrolysis, solar PV) have estimated coefficients.


			<figtable id="tab:MESSAGE-GLOBIOM_flex">
			{\| class="wikitable"
			\|+<caption>Flexibility Coefficients by Technology (Sullivan et al., 2013 [[CiteRef::MSG-GLB_sullivan_electric_2013]])</caption>
			! Technology
			! Flexibility Parameter
			\|-
			\| Load
			\| -0.1
			\|-
			\| Wind
			\| -0.08
			\|-
			\| Solar PV
			\| -0.05
			\|-
			\| Geothermal
			\| 0
			\|-
			\| Nuclear
			\| 0
			\|-
			\| Coal
			\| 0.15
			\|-
			\| Biopower
			\| 0.3
			\|-
			\| Gas-CC
			\| 0.5
			\|-
			\| Hydropower
			\| 0.5
			\|-
			\| H2 Electrolysis
			\| 0.5
			\|-
			\| Oil/Gas Steam
			\| 1
			\|-
			\| Gas-CT
			\| 1
			\|-
			\| Electricity Storage
			\| 1
			\|}
			</figtable>

			Thus, a technology like a simple-cycle natural gas plant, used almost exclusively for ancillary services, has a flexibility coefficient of 1, while a coal plant, which provides mostly
			bulk power but can supply some ancillary services, has a small, positive coefficient. Electric storage systems (e.g. pumped hydropower, compressed air storage, flow batteries) and
			flexible demand-side technologies like hydrogen-production contribute as well. Meanwhile, wind power and solar PV, which require additional system flexibility to smooth out fluctuations,
			have negative flexibility coefficients.