GCAM - Contact person for this activity: Dr S Lazarou [email protected]
An introduction of using the Global Change Assessment Model (GCAM) The European Energy Union [1] has recently pointed out the importance of EU leadership in the development of advanced zero-carbon emission electric production facilities. This policy is consistent with the recent Paris Agreement (COP21) [2] under the United Nations Convention on Climate Change, since they both contribute towards carbon emissions reduction. On the other hand, the One Belt-One Road/Silk Road initiative [3] creates complexities, but also opportunities for good practices exchange in creating sustainable energy transfer routes across Eurasia.
This work has as its objective to advance the knowledge of the technical challenges, in order to be able to propose the infrastructure that minimizes carbon emissions. This is to be achieved through energetic analysis. It needs to be carefully analyzed by using capable simulation tools and the appropriate data, whenever available. The tools have to able to foresee the effects of any potential further interconnections and propose feasible solutions.
Having mentioned the above, the researchers apply the energy module in the Global Change Assessment Model (GCAM), developed by the Pacific Northwest National Laboratory (PNNL) [4]. This platform provides the capabilities to translate objectives into the physical world. In this manner, the potential bottlenecks and practical challenges related to policies can be quantified.
Simulations
The existing information available in GCAM is adequate, to a certain degree, for performing the required simulations. The stored information includes complex knowledge on a variety of specially treated subjects of energy production, distribution, consumption, prices, resources availability etc., per region in global scale and technology.
However, to achieve the previously mentioned objectives, the researchers propose a variety of different scenarios based on the European policy expectations, as they are described in the European Energy Union and in the Paris Agreement. These scenarios can describe the challenges of the European Energy Union and provide a detailed analysis of the current and future situation, taking into consideration energy security policies and technical complications.
To quantify the input values, the researchers use the data available by default at the model and on a certain degree the ones available in the European Commission's Energy Technology Reference Indicator projections report [5]. These include the production costs and emissions for all available technologies, and the transmission and distribution losses for the electricity grid.
The scenarios could incorporate a variety of indicators including emission trajectories in time, and the CO2 concentration tracks for different technologies based on the representative concentration pathways (RCP) [6]. This is feasible due to the fact that GCAM is a Representative Concentration Pathway (RCP)-class model [4]
The proposed scenario is expressed in 10 years intervals and includes data up to 2050. An average global carbon emission trajectory the RCP4.5 [7] is taken into consideration. This represents the concentration of Greenhouse Gas concentration that leads to 4,5W/m2 radiative force. To the opinion of the authors, this simulation can be an initial step towards understanding the issues of the European Energy Strategy [8] that emphasizes to zero carbon emission facilities. GCAM, by default, includes this information at its running package [9].
Energy System and Climate Module of the Global Change Assessment Model (GCAM)
GCAM [9, 10] describes the interconnectivity between several sectors including energy and climate. It is able to provide informed estimations of the future situation based on the projection of the existing situation as it is adjusted to the policy requirements. It performs simulations of the requested data in 5 years intervals, using as initialization scenarios the real situation 1975 up to 2010 and then it projects it to 2100. As a market equilibrium model, for each distinctive part of the simulation the assigned prices to the commodities involved have to lead to a balanced situation. The results of the model remain under the scrutiny of its users. This research gives more attention to the energy module of the model.
For the energy system, the model takes into consideration the availability of primary energy, the transformation capabilities and the consumption requirements. The primary energy is comprised on the depleted and renewable sources. The depleted sources include the hydrocarbons, specifically oil and unconventional oil, natural gas, coal and nuclear power using uranium as the fuel. The renewable sources include wind, solar, hydropower, geothermal and biomass. Each of these sectors are assigned a selection of input parameters based on their special technical specifications such as the installation and operation costs, which is important for production facilities from depleted resources and the reserves cost for the intermittent renewables. The model uses specific pathways depicted to provide the results. It starts from the information provided at the left side of the picture assigning production costs for each specific depleted technology. The next step calculates the intermediate level to transform, refine and/or transfer the primary sources to the consumption sectors. The above are adequately represented for the time intervals of five years, however are not meant to simulate the electricity power system per se, which requires more detailed analysis as far as the intermittent renewables and the grid are concerned.
The above-mentioned primary sources are transformed to other forms of energy before they are consumed. For GCAM the customers of this exercise are the residential, industrial and transportation sectors. Their needs have to be met and the energy consumption produces carbon emissions that can be quantified. For GCAM, other sectors except from the energy sector are of importance. Among others the agricultural, land use and water sectors could indirectly or directly affect the energy production. As a matter of fact, land biomass used for energy production affects land and agricultural use. A separate function calculates the losses of the energy transformation per se.
As a general consideration the internal interconnections of GCAM appear to be linked to each other, creating a circle of inputs and outputs as abstractly depicted for the energy system in the figure below. In this reflection, it is assumed that the final objective eventually is the driving cause of the initial consideration. Therefore, the power system has consumption as its major requirement to be met. This consumption is on a variety of sectors, which specifically for GCAM are the industry, transportation and buildings. As a matter of fact, the aforementioned procedure leads to the carbon or greenhouse gases emissions that eventually lead to the phenomenon of global warming as it is accepted by the international organizations that study it. The next step of this exercise is to understand the requirements for the reduction of these emissions. This can be achieved through implementing limitations of the carbon emissions per se or by increasing the production from zero-emission sources. GCAM provides this capability in a variety of different ways, based on the policy requirement to be met. For example, the policy requirements of the European Union, as described at the Energy Union, lay on proposing the installation of zero-carbon emission sources. GCAM can accommodate this by predefining the existing installations. On the other hand, Paris agreement under the auspices of the United Nations and the Represented Concentration Pathways inspired by round tables chaired by the same organization, approach the same challenge in an alternative manner. In this case the emissions are to be capped. GCAM is able to simulate this requirement being able to provide a solution that meets this capping, incorporating to the simulation restrictive upper limits to greenhouse gas emissions.
The policies affect its results in a variety of ways, even on regional level given that climate change is global challenge. GCAM observes limitations, geographically expressed, that are of the interest of this research. The limitation towards carbon emissions is the principal factor under consideration but land use remains of paramount importance. All the above are analyzed in 32 geographical regions, where the input data, in this case, are open source provided by PNNL. Having mentioned the above, in the interests of this research are the geographical regions of the European Union, South East Asia and China but the model is run by default taking into consideration the global situation per se.
References
[1] A Framework Strategy for a Resilient Energy Union with a Forward-Looking Climate Change Policy, European Commission Communication, COM/2015/080.
[2] Adoption of the Paris Agreement. Proposal by the President, UNFCCC Secretariat, Conference of the Parties, FCCC/CP/2015/L.9/Rev.1.
[3] James A. Millward, The Silk Road, Oxford University Press 2013, ISBN 978-0-19-978286-4.
[4] http://www.globalchange.umd.edu/dev/models/gcam/, accessed November 2016.
[5] ETRI 2014 - Energy Technology Reference Indicator projections for 2010-2050, JRC92496.
[6] D. P. van Vuuren et al, The representative concentration pathways: an overview, Climatic Change (2011) 109:5–31
[7] IPCC Fifth Assessment Report of 2014: https://www.ipcc.ch/report/ar5/
[8] European Energy Security Strategy [COM(2014)330]
[9] http://jgcri.github.io/gcam-doc/, accessed November 2016.
[10] Kim, S.H., J. Edmonds, J. Lurz, S. J. Smith, and M. Wise (2006) The ObjECTS Framework for Integrated Assessment: Hybrid Modeling of Transportation Energy Journal (Special Issue #2) pp 51-80.
[11] http://jgcri.github.io/gcam-doc/energy.html, GCAM Energy Module documentation, accessed November 2016.
This work has as its objective to advance the knowledge of the technical challenges, in order to be able to propose the infrastructure that minimizes carbon emissions. This is to be achieved through energetic analysis. It needs to be carefully analyzed by using capable simulation tools and the appropriate data, whenever available. The tools have to able to foresee the effects of any potential further interconnections and propose feasible solutions.
Having mentioned the above, the researchers apply the energy module in the Global Change Assessment Model (GCAM), developed by the Pacific Northwest National Laboratory (PNNL) [4]. This platform provides the capabilities to translate objectives into the physical world. In this manner, the potential bottlenecks and practical challenges related to policies can be quantified.
Simulations
The existing information available in GCAM is adequate, to a certain degree, for performing the required simulations. The stored information includes complex knowledge on a variety of specially treated subjects of energy production, distribution, consumption, prices, resources availability etc., per region in global scale and technology.
However, to achieve the previously mentioned objectives, the researchers propose a variety of different scenarios based on the European policy expectations, as they are described in the European Energy Union and in the Paris Agreement. These scenarios can describe the challenges of the European Energy Union and provide a detailed analysis of the current and future situation, taking into consideration energy security policies and technical complications.
To quantify the input values, the researchers use the data available by default at the model and on a certain degree the ones available in the European Commission's Energy Technology Reference Indicator projections report [5]. These include the production costs and emissions for all available technologies, and the transmission and distribution losses for the electricity grid.
The scenarios could incorporate a variety of indicators including emission trajectories in time, and the CO2 concentration tracks for different technologies based on the representative concentration pathways (RCP) [6]. This is feasible due to the fact that GCAM is a Representative Concentration Pathway (RCP)-class model [4]
The proposed scenario is expressed in 10 years intervals and includes data up to 2050. An average global carbon emission trajectory the RCP4.5 [7] is taken into consideration. This represents the concentration of Greenhouse Gas concentration that leads to 4,5W/m2 radiative force. To the opinion of the authors, this simulation can be an initial step towards understanding the issues of the European Energy Strategy [8] that emphasizes to zero carbon emission facilities. GCAM, by default, includes this information at its running package [9].
Energy System and Climate Module of the Global Change Assessment Model (GCAM)
GCAM [9, 10] describes the interconnectivity between several sectors including energy and climate. It is able to provide informed estimations of the future situation based on the projection of the existing situation as it is adjusted to the policy requirements. It performs simulations of the requested data in 5 years intervals, using as initialization scenarios the real situation 1975 up to 2010 and then it projects it to 2100. As a market equilibrium model, for each distinctive part of the simulation the assigned prices to the commodities involved have to lead to a balanced situation. The results of the model remain under the scrutiny of its users. This research gives more attention to the energy module of the model.
For the energy system, the model takes into consideration the availability of primary energy, the transformation capabilities and the consumption requirements. The primary energy is comprised on the depleted and renewable sources. The depleted sources include the hydrocarbons, specifically oil and unconventional oil, natural gas, coal and nuclear power using uranium as the fuel. The renewable sources include wind, solar, hydropower, geothermal and biomass. Each of these sectors are assigned a selection of input parameters based on their special technical specifications such as the installation and operation costs, which is important for production facilities from depleted resources and the reserves cost for the intermittent renewables. The model uses specific pathways depicted to provide the results. It starts from the information provided at the left side of the picture assigning production costs for each specific depleted technology. The next step calculates the intermediate level to transform, refine and/or transfer the primary sources to the consumption sectors. The above are adequately represented for the time intervals of five years, however are not meant to simulate the electricity power system per se, which requires more detailed analysis as far as the intermittent renewables and the grid are concerned.
The above-mentioned primary sources are transformed to other forms of energy before they are consumed. For GCAM the customers of this exercise are the residential, industrial and transportation sectors. Their needs have to be met and the energy consumption produces carbon emissions that can be quantified. For GCAM, other sectors except from the energy sector are of importance. Among others the agricultural, land use and water sectors could indirectly or directly affect the energy production. As a matter of fact, land biomass used for energy production affects land and agricultural use. A separate function calculates the losses of the energy transformation per se.
As a general consideration the internal interconnections of GCAM appear to be linked to each other, creating a circle of inputs and outputs as abstractly depicted for the energy system in the figure below. In this reflection, it is assumed that the final objective eventually is the driving cause of the initial consideration. Therefore, the power system has consumption as its major requirement to be met. This consumption is on a variety of sectors, which specifically for GCAM are the industry, transportation and buildings. As a matter of fact, the aforementioned procedure leads to the carbon or greenhouse gases emissions that eventually lead to the phenomenon of global warming as it is accepted by the international organizations that study it. The next step of this exercise is to understand the requirements for the reduction of these emissions. This can be achieved through implementing limitations of the carbon emissions per se or by increasing the production from zero-emission sources. GCAM provides this capability in a variety of different ways, based on the policy requirement to be met. For example, the policy requirements of the European Union, as described at the Energy Union, lay on proposing the installation of zero-carbon emission sources. GCAM can accommodate this by predefining the existing installations. On the other hand, Paris agreement under the auspices of the United Nations and the Represented Concentration Pathways inspired by round tables chaired by the same organization, approach the same challenge in an alternative manner. In this case the emissions are to be capped. GCAM is able to simulate this requirement being able to provide a solution that meets this capping, incorporating to the simulation restrictive upper limits to greenhouse gas emissions.
The policies affect its results in a variety of ways, even on regional level given that climate change is global challenge. GCAM observes limitations, geographically expressed, that are of the interest of this research. The limitation towards carbon emissions is the principal factor under consideration but land use remains of paramount importance. All the above are analyzed in 32 geographical regions, where the input data, in this case, are open source provided by PNNL. Having mentioned the above, in the interests of this research are the geographical regions of the European Union, South East Asia and China but the model is run by default taking into consideration the global situation per se.
References
[1] A Framework Strategy for a Resilient Energy Union with a Forward-Looking Climate Change Policy, European Commission Communication, COM/2015/080.
[2] Adoption of the Paris Agreement. Proposal by the President, UNFCCC Secretariat, Conference of the Parties, FCCC/CP/2015/L.9/Rev.1.
[3] James A. Millward, The Silk Road, Oxford University Press 2013, ISBN 978-0-19-978286-4.
[4] http://www.globalchange.umd.edu/dev/models/gcam/, accessed November 2016.
[5] ETRI 2014 - Energy Technology Reference Indicator projections for 2010-2050, JRC92496.
[6] D. P. van Vuuren et al, The representative concentration pathways: an overview, Climatic Change (2011) 109:5–31
[7] IPCC Fifth Assessment Report of 2014: https://www.ipcc.ch/report/ar5/
[8] European Energy Security Strategy [COM(2014)330]
[9] http://jgcri.github.io/gcam-doc/, accessed November 2016.
[10] Kim, S.H., J. Edmonds, J. Lurz, S. J. Smith, and M. Wise (2006) The ObjECTS Framework for Integrated Assessment: Hybrid Modeling of Transportation Energy Journal (Special Issue #2) pp 51-80.
[11] http://jgcri.github.io/gcam-doc/energy.html, GCAM Energy Module documentation, accessed November 2016.