FORECAST Industry
Source: Commission modelling inventory and knowledge management system (MIDAS)
Date of Report Generation: Thu Mar 06 2025
Dissemination: Public
© European Union, 2025
The Commission's reuse policy is implemented by the Commission Decision of 12 December 2011 on the reuse of Commission documents. Unless otherwise indicated (e.g. in individual copyright notices), content owned by the EU on this website is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. This means that reuse is allowed, provided appropriate credit is given and changes are indicated. You may be required to clear additional rights if a specific content depicts identifiable private individuals or includes third-party works. To use or reproduce content that is not owned by the EU, you may need to seek permission directly from the rightholders. Software or documents covered by industrial property rights, such as patents, trade marks, registered designs, logos and names, are excluded from the Commission's reuse policy and are not licensed to you.
Disclaimer: The Commission accepts no responsibility or liability whatsoever with regard to any and all information made available on or accessible through MIDAS website. The information, including but not limited to models, impact assessments, models’ input and output data, and metadata, modelling exercises and policy contributions, is of a general nature only and is not intended to address the specific circumstances of any particular individual or entity, and may not be regarded as comprehensive, complete, accurate or upto-date. The Commission furthermore does not assume any responsibility for content of any external websites to which links maybe provided on this website. Any and all information provided may not be regarded as professional or legal advice. Information available through the website may not be referenced as officially adopted text of European Union regulatory or policy documents or sources. Their authentic versions can only be accessed through the Official Journal of the European Union (the printed edition or, since 1 July 2013, the electronic edition on the EUR-Lex website).
Overview
Acronym
FORECAST Industry
Full title
Forecasting Energy Consumption Analysis and Simulation Tool (model part: industry)
Main purpose
FORECAST Industry is a bottom-up simulation model. It calculates scenarios of energy demand and GHG-emissions of the industry sector. It is mainly applied to scenarios addressing climate change and industry transformation.
Summary
The main purpose of the FORECAST Industry model is to calculate scenarios of industry transformation with the background of climate change mitigation. It covers the European Union, UK, Switzerland and Norway and is usually applied within the timeframe of European and national climate targets (up to 2050). Main calculations happen on national (NUTS0) level, with capabilities to disaggregate results downwards to NUTS3. The model includes all industrial subsectors (e.g. iron and steel, cement, pulp&paper…) relevant to Eurostat and national energy balances, adding details on individual processes (e.g. blast furnace operation) and technologies (e.g. heat pumps, hydrogen-based direct reduction).
FORECAST Industry is a bottom-up simulation model. Therefore, the model uses highly-disaggregated data ("bottom") on industrial processes (e.g. specific energy consumption of steel production) to explain observable high-level figures ("up", e.g. electricity use in industry). The main approach is thus the assumption that the sum of all individual industrial activities constitutes the entire industry sector. Simulation means that the model strives to reproduce important aspects of decision-making (e.g. investment in new technologies) close to the actual process – including inefficiencies, lack of information and imperfect decisions.
The bottom-up approach of FORECAST Industry is well suited for instrument-based analyses that investigate specific subsectors, energy carriers or technologies (e.g. EU-ETS, IPCEI, CCfDs, Ecodesign, circular economy actions). For example, it is used for ex-ante evaluation of the German policy mix as part of the documentation requirements of Regulation (EU) 2018/1999 of the European Parliament and of the Council of 11 December 2018 on the Governance of the Energy Union and Climate Action. In addition to instrument-based analyses, FORECAST Industry is often applied to exploratory scenarios and in combination with other sectoral- and energy-system models.
The FORECAST model family also includes models for buildings and appliances.
Model categories
ΟtherEnergy
Model keywords
SimulationIndustryDecarbonisation
Model homepage
Ownership and Licence
Ownership
Third-party ownership (commercial companies, Member States, other organisations, …)
Ownership details
Licence type
Non-Free Software licence
The license has one or more of the following restrictions: it prohibits creation of derivative works; it prohibits commercial use; it obliges to share the licensed or derivative works on the same conditions.
Details
Structure and approach
FORECAST Industry is based on European or national energy balances (e.g. Eurostat, AGEB (Germany)). In addition, it uses techno-economic data from literature and production statistics to define properties of around 80 industrial processes (e.g. energy intensity, deployed and potential future technologies). The combination of these techno-economic data and scenario-based assumptions on industrial activity (physical production of specific products) yield energy demands per product, process and subsector. This energy demand can be influenced by energy efficiency, fuel switch (driven by fuel prices or regulations), technology replacement (e.g. electric boilers replacing natural gas-fired ones) or complete process switch (e.g. hydrogen-based direct reduction instead of blast furnace operations) – all of which may be impacted by policies included in the scenarios.
In this calculation process, additional information are added to the statistical data with which the model started – thus, the process is called "disaggregation of energy balances". The disaggregated description of the industry sector is used to calculate possible futures in scenarios. In a final step, the model results are aggregated back towards the level of energy balances and calibrated to a given base year. The results thus represent a structurally compatible extension of the base statistic into the future along the scenarios defined in the project, with the main output of final energy demand, energy carrier shares and GHG-emissions by source (compatible with National Inventory Reports (NIR)).
Input and parametrization
- Energy balance (Eurostat, national balances)
- Various techno-economic data on industrial processes (e.g. temperature profile of heat demand, energy intensity, investment and operation costs of technologies,…)
- GHG-emissions (National Inventory Reports, common reporting tables)
- Scenario definitions (including expected development of all input data)
- Policy instrument description
- Past and current activity of industrial processes (physical production)
- Energy carrier prices
- CO2-pricing
- Gross domestic product
Main output
- Final energy demand by energy carrier, subsector, technology, temperature level, country
- Greenhouse gas emissions (GHG) by subsector, energy carrier, country
- Selected (not full) cost data (e.g. investment, energy, policy, CO2)
Spatial & Temporal extent
The output has the following spatial-temporal resolution and extent:
| Parameter | Description |
|---|---|
| Spatial extent / country coverage | EU Member states 27NorwaySwitzerlandUnited Kingdom |
| Spatial resolution | NationalSub-national (NUTS1)Sub-national (NUTS2)Sub-national (NUTS3) |
| Temporal extent | Long-term (more than 15 years) |
| Temporal resolution | Years |
Quality & Transparency
Quality
Model uncertainties
Models are by definition affected by uncertainties (in input data, input parameters, scenario definitions, etc.). Have the model uncertainties been quantified? Are uncertainties accounted for in your simulations?
- response
- no
- details
- Uncertainties are addressed with scenario variations. Multiple scenarios allow to narrow the solution space of "possible scenarios" and what they mean for the model output.
- url
Sensitivity analysis
Sensitivity analysis helps identifying the uncertain inputs mostly responsible for the uncertainty in the model responses. Has the model undergone sensitivity analysis?
- response
- yes
- details
- Sensitivity analysis is addressed with scenario variations. Multiple scenarios allow to narrow the solution space of "possible scenarios" and what they mean for the model output.
- url
Have model results been published in peer-reviewed articles?
- response
- yes
- details
- url
Has the model formally undergone scientific review by a panel of international experts?
Please note that this does not refer to the cases when model results were validated by stakeholders.
- response
- no
- details
- url
Model validation
Has model validation been done? Have model predictions been confronted with observed data (ex-post)?
- response
- no
- details
- url
Transparency
To what extent do input data come from publicly available sources?
This may include sources accessible upon subscription and/or payment
- response
- Based on both publicly available and restricted-access sources
Is the full model database as such available to external users?
Whether or not it implies a specific procedure or a fee
- response
- no
- details
- url
Have model results been presented in publicly available reports?
Note this excludes IA reports.
- response
- yes
- details
- documents
For details please refer to the 'peer review for model validation' documents in the bibliographic references
Have output datasets been made publicly available?
Note this could also imply a specific procedure or a fee.
- response
- yes
Is there any user friendly interface presenting model results that is accessible to the public?
For instance: Dashboard, interactive interfaces...
- response
- yes
Has the model been documented in a publicly available dedicated report or a manual?
Note this excludes IA reports.
- response
- yes
- details
Is there a dedicated public website where information about the model is provided?
- response
- yes
Is the model code open-source?
- response
- no
- details
Can the code be accessed upon request?
- response
- no
- details
The model’s policy relevance and intended role in the policy cycle
The model is designed to contribute to the following policy areas
- Business and industry
- Climate action
- Energy
The model is designed to contribute to the following phases of the policy cycle
- Anticipation – such as foresight and horizon scanning
- Formulation – such as ex-ante Impact Assessments
The model’s potential
FORECAST Industry may contribute to the assessment of potential impacts of new technologies on the industry sector and how policy instruments affect their performance. Examples include estimates of future hydrogen and electricity demand that result from different technology choices in the context of climate change mitigation.
Previous use of the model in ex-ante impact assessments of the European Commission
Use of the model in ex-ante impact assessments since July 2017.
2024SWD/2024/63 final
Impact Assessment Report Part 1 Accompanying the document Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions Securing our future Europe's 2040 climate target and path to climate neutrality by 2050 building a sustainable, just and prosperous society
- Lead by
- CLIMA
- Run by
- Fraunhofer Institute for Systems and Innovation Research
- Contribution role
- baseline and assessment of policy options
- Contribution details
The FORECAST model has been used independently to study the impact of selected circular economy actions on industrial decarbonisation pathways.