OPERA is a Dutch-based national energy system model focusing on total system cost minimization. Refer to https://multimodelling.readthedocs.io/en/latest/energy_models/OPERA/index.html for more overall information regarding the model.

General model information

General model information questions were asked regarding basic information, model versions, and point of contact for questions. The OPERA model is developed and maintained by the TNO-ETS group in Amsterdam.

Questions to ask


Model name

OPERA (Options Portfolio for Emission Reduction Assessment)

Model owner


Model Developer


The latest model version/date

The model version used in this project





Joost van Stralen

A second set of questions was asked regarding whether the model is type or token, the intended purpose of the model, and the level of decision that the model aims to support. We understand that the model can be categorized as type and token model. The model focuses on long-term decision-making with different policies, targets, and measures. Even though some policy measures are incorporated, the model does not emphasize significantly in the mid-term (2025-2045). The model allows the possibility to focus on the mid-term if needed. Energy balances are maintained between the demand and supply on a regular basis, i.e., short-term.

Questions to ask


Is the model a token model? If so,

give illustration(s).

Yes. For example, the model analyses the techno-

economical aspect of the energy system.

Is the model a type model? If so,

give illustration(s).

Yes. For example, the model reflects universal

characteristics of network infrastructure, i.e., energy flows.

Briefly describe the intended purpose of

the model

Total system cost minimization at the national level

(the Netherlands)

Strategic - long-term planning; what do

we want?

1. Long-term national and regional policy targets related

to emissions reductions, efficiency, renewable energy


2. Long-term targets of, for example, production for

industries, including subsectors, sectoral demands,

energy infrastructure capacity, if any

Tactical - medium-term; how do we approach


1. Not much emphasis in the medium term, except in the

dynamic run mode of the model

2. Model structure allows for the inclusion of medium-

term policies. Most of them are already included are already

in the model.

3. Certain input parameters are adjusted based on

upcoming policies, for example, energy labels of offices

Operational - short-term; regular/day-to-day


demand-supply energy balances, energy flows to address

mismatches, short-term flexibility options

Typical questions asked of the model include future capacities of different renewable resources and energy supply options. The model has many strengths, one of them being replicability. The model can readily apply to other European national energy system modeling contexts. An additional remark is that the model can simultaneously analyze greenhouse gases (GHG), non-energy-related emissions, and air pollutants at the regional and national levels. One of the critical limitations of the model is the assumption of perfect foresight. The model has been used to formulate strategic policy advice for the Dutch government on energy decarbonization and climate change mitigation. Refer to the table below for further discussion on these aspects.

Questions to ask


What are typical types of questions that

can be asked to the model? provide

examples of such questions

1. What are different renewable sources’ future capacities and

energy supplies

2. What is the energy flow between regions, and is the

network constrained to achieve that? Etc.

What are the strengths of this model?

What is unique?

1. Replicability: the structure can be readily applied to other

countries, particularly in Europe

2. System integration - an ideal tool for assessing the

implementation of the energy transition and the

establishment of a low-carbon economy

3. Linkage to the NEOMS model - this model uses data from

the NEOMS model, which is used for preparing the annual

Dutch national energy outlook.

Additional comments/remarks:

1. The model analyzes greenhouse gases (GHG), non-energy-

related emissions, and air pollutants.

2. The capacity limits (of at least essential technology options

or processes) are set by expert consultation.

What are the important limitations of the


  1. Perfect foresight assumption

2. Social interaction and impacts missing

Cases/examples where the model was

used for its intended purpose

1. Used for formulating strategic policy advice on energy

decarbonization and climate change mitigation for the Dutch


2. Performed exploratory studies on the role of specific low-

carbon energy technologies in the energy transition of the


Cases/examples where the model was

not used for its intended purpose; are

there any examples of model abuse or


The next set of questions is related to model documentation, accessibility, and type. The model content is documented in a journal paper that is open source. The graphical user interface (GUI) can be accessed with the owner’s permission. The model is static, deterministic, and linear programming (LP)-based.

Questions to ask


Is the model documentation


Content documentation is a journal paper

(see reference below). There is no public documentation on

the details of the model (for example, GUI, API, etc.). In

addition, not every update is documented.

Is the documentation accessible?

If so, how?

The journal paper is open source.

Is the documentation in English?


Does the model have a

GUI? If so, how to access


Yes, the GUI can be accessed with the whole model with

the owner’s permission.

Does the model have an Application

Programming Interface (API) ? If so,

how to access it?

In general, the model does not have an API.

Is the model static or dynamic?


Additional comments/remarks:

OPERA can consider 5/10-year time steps, projecting till 2050,

i.e., years are optimized individually. Previous year-cycle data

are not automatically fed to future years. Dynamic modeling is

in progress and will not be a part of this project.

Is the model continuous or discrete?


Is the model stochastic or



Is it an optimization model? If so, what

type of algorithms it uses?

Yes, LP

Additional comments/remarks:

Due to linear structure, discrete values (say, integers) are

not considered. However, limits (lower and upper) can be set

as discrete values.

The next set of questions are regarding the modeling paradigm, implementation environment, and license. The model applies multiple formalisms, such as mathematical equations and logical expressions. The model is implemented using a modeling package called AIMMS. An AIMMS license is needed, and the owner can share the model.

Questions to ask


What modeling paradigm or formalism

does the model use?

Mathematical equations, logical expressions, energy balances,

math equations, etc.

Is it implemented in a General

purpose programming language?


Does it use a modeling/Simulation



Is it implemented in a spreadsheet?

Is any license required to run the


AIMMS license is needed, except for educational and research


Model content

A preliminary set of model content questions were related to energy system integration and scope. The model represents an integrated energy system. Essential elements and concepts the model includes are all greenhouse gas emissions in the Netherlands. Similarly, content-wise, the model contains important energy infrastructure, such as electricity, heat, and hydrogen. Some flexibility options included in the model are salt caverns (spatially dependent), batteries, or hydrogen (spatially independent).

Questions to ask


Does the model represent an integrated

energy system?


What important elements and concepts are

included in the model?

1. Covers the entire energy system and all greenhouse gas emissions of the Netherlands

2. Content-wise coverage: Energy-demanding sectors

(built environment, industries, agriculture, and mobility),

energy supply options (for example, wind, solar, biomass,

geothermal, and non-renewable sources), and energy

infrastructure (electricity, heat, gas, hydrogen, and CO2)

What elements and concepts are currently

not included in the model, but in your

opinion, those shall be included?

Specific attention to flexibility options:

What type of flexibility options are included

in the model?

A few examples of flexibility options are salt caverns

(space-specific), batteries, hydrogen storage, and a

significant range of conversion techniques.

Additional comments/remarks:

Storage, in general, has zero costs. Only electricity and

hydrogen have storage costs.

The next set of content-related questions included scale and resolution. The spatial scale of the model is the national level, and the temporal scale is long-term (till 2050). The spatial resolution is at the city or municipality level, which has only been done for Groningen province in the northern Netherlands. Temporal resolution is time slices, with a maximum possible 80 slices for a year.

Questions to ask


What spatial (or geospatial) scale does the

model have?


What temporal (or time) scale does the

model have?

Long-term (till 2050)

Per run, the calculations are done on an annual basis in

the model.

Spatial resolution


Additional comments/remarks:

This has been done only for Groningen Province. The

structure allows us to perform similar analyses in other

regions within the Netherlands.

Temporal resolution

Time slices

Currently, the maximum possible is 80 slices/year.

The next set of questions is related to model assumptions, model inputs, parameters, and outputs, and data sources related to the model. One of the critical assumptions is the state in which the energy infrastructure is considered in the model. For some, the current state is the base; for others, every investment starts from 0. The model standard input is MS Access, and the output format is MS Excel. Some important model inputs are Technology inputs (supply options), costs (annualized investments, fixed, variable, and operation and maintenance costs), and industrial processes. Similarly, some important model outputs are primary energy supply, secondary energy demand-supply balances, energy flows, and system costs. Data can be shared with permission from model owners. Most of the data are from open sources.

Questions to ask


What critical assumptions does the

model have?

1. For some infrastructure, the current state of investment

is the base (or lower limit), for example, high voltage

electricity network, for others, all the investments start

from scratch, for instance, medium voltage electricity


2. Cost or capacity ranges are primarily based on literature or

expert suggestions.

Which ones are likely to be contested by

others? Why?

1. Price includes material costs and does not include social

or environmental costs

2. Every stakeholder has complete knowledge of the market

Behavior. Only the system operator perspective is


What is/are the model input format(s)?

MS Access

Additional comments/remarks:

There is a preprocessing of inputs within OPERA so that

to reduce the number of activities (solving variables) that

goes into the optimization process

What is/are the model output format(s)?

MS Excel

Additional comments/remarks:

There is postprocessing of outputs both in OPERA and in


What are the important model inputs?

Technology inputs (supply options), costs (annualized

investments, fixed, variable, and operation and

maintenance costs), industrial processes, emissions from

industries and other activities, future targets (for example,

renewable energy production, emission reduction, and

efficiency improvement)

What important parameters do the

model have?

technology- and process-related parameters (such as,

efficiency), demand and supply profiles, limits and ranges

on output, demand service units (for example, MT_steel)

What are the important model outputs?

primary energy supply, secondary energy demand-supply

balances, energy flows, system costs

What are the data sources used by the


Open sources, such as CBS, are mostly linked to other models

for specific inputs, etc.

Any data that can be shared? If so, what

and how to access them?

Databases (MS access format) can be accessed with

permission from model owners. Databases contain most

input-related data. The remaining data can be accessed by

accessing the model with permission from the model


Continuing with the model content, there were questions regarding verification, validation, and test, and uncertainty descriptions. The answer to test coverage of the model is that there is no formal testing possibility within the modeling framework. Verification, validation, and testing can be done on boundary conditions and input limits/ranges, generally done by sensitivity analyses, expert opinions, and comparisons with other models. Inputs related to the long term are more uncertain compared to the mid-term.

Questions to ask


Can you comment on the test coverage of

the model?

There is not much formal testing possibility within the

modeling framework. Input parameters can be tested by

sensitivity analyses, for example. Non-optimality or model

not converging conditions validate modeling


What is being verified, validated, or tested

in the model?

Verification, validation, and testing can be on the

boundary conditions, inputs, limits/ranges, etc.

What methods are used for the model

verification, validation, and testing, if any?

1. Qualitative method: stakeholder and expert opinions

and perspectives, literature, government reports, etc.

2. Quantitative method: comparison with other

contemporary national models, scenario comparisons, etc.

Can you comment on the uncertainty in

model parameters?

Important model parameters within the model operate

within ranges, depending upon scenarios, to handle


Can you comment on the uncertainty in

model input?

Input is more uncertain for long-term scenarios compared

to the mid-term.

Can you comment on the uncertainty in

the model structure?


Model Description:

Model application: