A technology assessment of available and commercially mature power system technologies at 2050 is made. It is presented in the form of a techno-economic database displaying data (i.e. technical performances, costs, environmental impact, etc.) that characterizes the different technologies for the next four decades, i.e. from today to 2050.
The technology assessment reflects the common views of the e-Highway2050 experts regarding the most likely evolutions of the selected technologies mainly in terms of technical performances, maturity, and costs and provides the project partners with data to feed the different simulation tasks (e.g. scenario quantification, grid simulations, cost benefit analyses).
The main challenge relates to the technology assessment for the grid architecture of the pan-European transmission system at 2050:
- How to define a portfolio of technologies at the 2050 time horizon impacting the European transmission grid?
- How to characterize trajectories of performances and costs of each identified technology at that time horizon?
- How these trajectories are consistent with the defined e-Highway2050 scenarios?
Background and assumptions
The technology assessment for the grid architecture is included in the framework of the general e-Highway2050 process based on energy scenario projections of likely futures for the power system at 2050. More specifically it follows the power spatial localization (Generation/Demand/Exchanges) for each scenario, at country and cluster level, the general objective being to identify the possible weak points, the congestion points in the transmission grid, in case of absence of reinforcement.
In order to identify grid architectures in 2050 solving the congestions, it is needed to further investigate cost and performances of power system technologies likely to impact long-term grid planning issues. Deliverable 3.1 of e-Highway2050 deals with the assessment of the most impacting technologies for the power system in the EU28 at the 2050 time horizon.
The scope of power system technologies covers the whole electricity value chain from generation and storage, transmission (passive and active transmission technologies) to demand.
Description of the result
Building a technology characterization database
The definition of the future grid architectures in 2050 solving the congestions is based upon a technology assessment of available and commercially mature power system technologies at 2050.
Such assessment consists in the construction of a database displaying data (i.e. technical performances, costs, environmental impact, etc.) that characterizes the different technologies for the next four decades, i.e. from today to 2050. Key issues of the database building relate to the technologies that are expected to be widely used in a long-term horizon, to the type of data that will be needed, and to the intrinsic uncertainty at that remote time horizon. These three major issues have been addressed in parallel through three main axis of effort: the technology selection and related data gathering, the template of the data gathering according to data types and the modalities to manage uncertainty.
The techno-economic database consists therefore in three building blocks which could be represented by the three dimensions depicted in the figure below.
- The wideness of technology areas is illustrated in brown color for the four considered technology areas (generation, storage, transmission and demand-side technologies).
- The depth of the database is represented in blue color with examples of variables characterizing the selected technologies, including technical performances and costs at 2050.
- A degree of uncertainty represented by the vertical axis: each data or range of data at the intersection of the horizontal plane (one technology X one variable) is qualified by a qualitative degree of confidence resulting from its uncertainty. This degree is estimated in the context of the five scenarios of the e-Highway2050 project.
The technology database could be seen as composed by records for each intersection point “Technology area X characterization variable” including either:
- quantitative data, i.e. precise values or ranges of values according to the degree of uncertainty,
- and, in a separate document, a description of assumptions and models used by experts, or qualitative data, i.e. data relative to the maturity of an innovation for a technology.
Figure 1: The three dimensions of the e-Highway2050 technology characterization database
It should be noted that the technology portfolio identification and selection is detailed in the knowledge article related to e-Highway 2050: a methodology to define power technologies expected to impact grid architecture studies at 2050, and the management of data uncertainties and the contextualization according to scenarios is presented in the knowledge article related to e-Highway 2050: Management of uncertainties and data contextualization in the framework of the technology assessment of power system technologies expected to impact grid architecture studies at 2050. In the following, the focus is on the architecture of the database (including the characterization variables).
The whole construction of the techno-economic database is the result of a collective work under the management of TECHNOFI and involving key European stakeholders of the electricity value chain (manufacturers, TSOs, academia).
Architecture of the technology characterization database and characterization variables
The database architecture consists in the definition of a list of key variables to be considered in order to characterize a given technology. The database is organized per technology (variant) and sub-technology1, when relevant. For each technology, a set of variables is documented on costs, performances and other characteristics. These variables are organized according to a set of data types detailed in Table 1. For each variable a value is given for each decade: today (2013), 2020, 2030, 2040 and 2050.
This architecture is found in all data sheets (Excel files) supplementing the Technology Assessment Report (Word file). The set of Excel files constitutes the technology database.
Table 1: Architecture of database per data types
Within this general framework, the most impacting variables describing technologies in a given technology area are detailed in the following sections. The two data types - technology performance characteristics and costs2 - are the ones that have been detailed in-depth since of the highest interest for the power system simulations to be performed by the project.
Assessment of the methodology use and limitations
Beyond the values and records included in the techno-economic database, one key value of the result is in its methodological dimension, e.g. it provides statements and assumptions in a modular way to rerun the various methodological blocks, e.g.:
- to recalculate future costs of transmission technologies based on different archetypes or different breakdowns of cost or different laws of evolutions of indices
- to re-contextualize data according to new 2050 scenarios
- to add non considered technologies beyond the current e-Highway2050 technology portfolio.
Beyond the e-Highway2050 project time horizon and scope, such approach could thus be used in further grid planning studies at national or EU levels.
This article is connected to the following complementary knowledge articles:
The techno-economic database is available on the GridInnovation on-line platform HOME page and via the following link: http://www.gridinnovation-on-line.eu/Technology-Database/
Deliverable D3.1 e-Highway2050
Glossary used in the article
- Database A comprehensive set of data for each decade (from today to 2050) characterizing power system technologies (organized per technology and data type).
- Data type Classes of data such as technical performances, environmental impact and public acceptance, costs (there are eight data types).
- Datasheet Excel file including a set of data for one technology retained in the e-Highway2050 scope. It is related to a Technology Assessment Report (TAR).
- TAR Report detailing the assumptions and comments relative to the data displayed in the datasheet(s).
 For example, wind power (technology or variant) is divided into two sub-technologies, i.e. on-shore and off-shore.
 the construction of future cost trajectories for transmission equipment based on their today’s estimated cost which is detailed here.