Introduction¶
Somadutta Sahoo, Last update: 11 November 2023
The model description template was created to compare models under different categories. For this project, the focus is energy system models. The intention was to create a platform for model filtering when determining diverse energy system configuration analyses. The template provides a standard format for model description, including capabilities, important assumptions, data requirements, definitions, and scales.
The template is categorized into the first level, second level, questions to ask, answers, and additional comments. The first category was further subdivided into:
Within general information, further subcategories or the second level are basic information, model versions, type or token model, intended purpose, level of decision that the model aims to support, questions that the model can address, strengths, limitations, part usage of the model, model documentation, model accessibility, model type, model paradigms/formalisms, model implementation environment, and model license.
The model content targets the model structure. The categories are energy system integration, scope, scale, granularity/resolution, model assumptions, model inputs, parameters and output, data sources, verification, validation, test, and uncertainty description. The last category is the reference section.
Questions and the explanation of the question sections were formulated to ask questions and further explain those questions to different model owners if needed. The examples of answers section was created to facilitate model owners in answering some questions. The explanation of the question and the example of answers sections provided clarity to model owners in answering questions. Some question explanations are based on the Terminology document. This allowed for clarity among model owners regarding interpreting different meanings of the same terms. The answers section provides answers from the model owners regarding the questions asked. Some of the answers could be further explained in the additional comments section. The following paragraphs describe the model template in detail.
General model information¶
To start with general model information, basic questions were asked about the model name, owner, and developer. Similarly, questions were asked about the model’s latest versions, versions used for this project, and point of contact for posing any further questions.
Second level |
Questions to ask |
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Basic information |
Model name |
Model owner |
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Model Developer |
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Model version |
Latest model version/date |
The model version used in this project |
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Point of contact for questions |
Organization |
Individual |
Within general information regarding the model, questions were asked regarding whether the model is a token or a type model. Questions on the modeling’s intended purpose and level of decision support were asked. Some of the questions were further explained in the process of asking questions. Suitable references, wherever needed, were provided.
Second level |
Questions to ask |
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Type model or token model |
Whether the model is a token model? If so, give illustrations Explanation of the question: These models capture elements or individual properties of the system as opposed to universal property (ref: https://link.springer.com/article/10.1007/s10270-006-0017-9) |
Is the model a type model? If so, give illustrations Explanation of the question: These models capture the universal property of the system rather than emphasizing a particular property (ref: https://link.springer.com/article/10.1007/s10270-006-0017-9) |
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Intended purpose |
Briefly describe the intended purpose of the model. |
The level of decision that the model aims to support |
Strategic - long-term planning; what do we want? |
Tactical - medium-term; how do we approach this? |
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Operational - short-term; regular/day-to-day operations? |
Continuing with general model information, questions were asked related to what kind of typical questions can be answered by the model or what the strengths and limitations of the model are. Similarly, questions were asked regarding cases/examples where the model was used for the intended purpose or was not related to the past usage of the model.
Second level |
Questions to ask |
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Questions to address |
What are typical types of questions that can be asked to the model? Provide examples of such questions. Explanation of the question: The questions may relate to categories such as technologies, techno-economics, society, environment (also emission-related), and policies. |
Strengths |
What are the strengths of this model? What is unique? |
Limitations |
What are the important limitations of the model? |
Past usage of the model |
Cases/examples where the model was used for its intended purpose |
Cases/examples where the model was not used for its intended purpose; are there any examples of model abuse or misuse? |
Second-level categories of general model information included model documentation, accessibility, and types. Questions within the model documentation included whether the model documentation is complete, whether the documentation is accessible, and whether the documentation is in English. Model accessibility-related questions included asking the modeler whether the model has a Graphical User Interface (GUI) and the possibility to access the same. A similar question was whether the model has an application programming interface (API) and how one can access it. To understand the model type, questions were asked whether the model is static or dynamic, continuous or discrete, stochastic or deterministic, and optimization-based. To understand the type of optimization, a question was asked regarding what algorithm the model uses.
Second level |
Questions to ask |
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Model documentation |
Is the model documentation complete? |
Is the documentation accessible? If so, how? |
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Whether the documentation is in English? |
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Model accessibility |
Does the model have a GUI? If so, how to access it? |
Does the model have an API? If so, how to access it? |
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Model type |
Is the model static or dynamic? |
Is the model continuous or discrete? |
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Is the model stochastic or deterministic? |
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Is it an optimization model? If so, what type of algorithms does it use? Examples of answers: linear programming (LP), mixed integer (linear) programming (MIP), non-linear programming (NLP), or a combination of some of these |
Continuing with the general model information, the second-level categorization followed was modeling paradigms/formalisms, model implementation environment, and model license. A question was asked regarding what modeling paradigm or formalism the model uses. Examples of answers included discrete events, system dynamics, agent-based, etc. Questions related to the model implementation environment included if the model was implemented in a general-purpose programming language, such as Python or JAVA, what modeling package the model used, for example, off-the-shelf packages such as AIMMS or MATLAB, and whether the model is implemented in a spreadsheet. The model licensing question was whether any license is required to run the model.
Second level |
Questions to ask |
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Modeling paradigms/formalisms |
What modeling paradigm or formalism does the model use? Examples of answers: discrete event, systems dynamics, agent-based, regression, network model, math equations, etc. |
Model implementation environment |
Is it implemented in a General purpose programming language? Examples of answers: Python, JAVA, C++, etc. |
Does it use a modeling/Simulation environment/package? Examples of answers: off-the-shelf packages such as AIMMS, GAMS, MATLAB; or modeling packages such as Mesa, PyDevs |
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Is it implemented in a spreadsheet? Examples of answers: excel, googlesheets, etc. |
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Model license |
Is any license required for running the model? |
Model content¶
The next set of questions was related to the model content (first level). The first set of second-level categories within this are energy system integration and model scope. The integration question was whether the model represents an integrated energy system. Scope-related questions were what important elements and concepts are included in the model and what are not. To explain these questions further, the explanation was scope could include energy carriers, infrastructure, supply options, demanding sectors, etc. Examples of energy carriers could include heat, electricity, hydrogen, etc. Since flexibility is gaining attention within the context of energy system modeling, an explicit scope-related question was asked regarding what flexibility options were included in the model.
Second level |
Questions to ask |
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Energy System Integration |
Does the model represent an integrated energy system? |
Scope |
What important elements and concepts are included in the model? Explanation of the question: This can include energy carriers, infrastructure, supply options, demanding sectors, etc. Examples of answers: heat, electricity, hydrogen, etc. – for energy carriers. |
What elements and concepts are currently not included in the model, but in your opinion, those shall be included? |
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Specific attention to flexibility options: What type of flexibility options are included in the model? Examples of answers: seasonal storage, demand response, etc. |
Continuing with the model content, the next second-level category was scale and granularity or resolution. Within the scale category, questions were asked about the model’s spatial (or geospatial) and temporal (or time) categorization. Answers could include neighborhood, city, province, etc, for spatial scale and a year or multiple years for temporal scale. Granularity also included spatial and temporal categorization with similar possible answers.
Second level |
Questions to ask |
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Scale |
What spatial (or geospatial) scale does the model have? Examples of answers: neighborhood, district, town/city, province, country, continent, global, etc. |
What temporal (or time) scale does the model have? Examples of answers: annual, multiple years, etc. |
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Granularity/resolution |
Spatial Explanation of the question: This can be further classified into structural or information granularity. Structural granularity represents the level of disaggregation between model elements and the relationships between them. Information granularity represents the information content of the model elements and output. Examples of answers: individual buildings, neighborhood, district, town/city, province, country |
Temporal Examples of answers: seconds, minutes, hours, annual, time slices within a year, time slices over a time period, etc. |
Within the model-content context, the next set of second-level categories are model assumptions; model inputs, parameters, and outputs; and data sources of the model. Model assumption questions are what important assumptions the model has and what assumptions are likely to be contested by others. Questions related to model input, parameters, and output are: what is/are the model format for input and output, and what important inputs, parameters, and outputs does the model include? Data sources-related questions included the model’s data sources and whether any data can be shared.
Second level |
Questions to ask |
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Model assumptions |
What important assumptions does the model have? |
Which ones are likely to be contested by others? Why? |
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Model input, parameters, and output |
What is/are the model input format(s)? |
What is/are the model output format(s)? |
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What are the important model inputs? |
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What important parameters does the model have? |
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What are the important model outputs? |
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Data sources |
What are the data sources used by the model? |
Any data that can be shared? If so, what and how to access them? |
The next second-level categories within the model content are verification, validation, and test and uncertainty descriptions. Within the first category, questions included what the test coverage of the model is, what is verified, validated, and tested within the model, and what methods are deployed for model verification, validation, and testing. Examples of answers related to the test coverage are direct structure tests, parameter confirmation, structural boundary adequacy, etc. Examples of testing and validation methods include Monte Carlo simulations. Questions related to uncertainty descriptions were simplistic, for example, what could modelers comment on the uncertainties associated with model parameters, inputs, and structure? In the end, there is a description and application-related reference of the model.
Second level |
Questions to ask |
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Verification, validation, and test |
Can you comment on the test coverage of the model? Explanation of the question: The test could be on structure, behavior, policy implications, etc. Examples of answers: direct structure tests, parameter confirmation, extreme conditions, structural boundary adequacy, unit checks, sensitivity tests, reproduction/prediction tests, etc. |
What are being verified, validated, or tested in the model, if any? Explanation of the question: What type of methods are employed? It could be qualitative, quantitative, etc. Examples of answers: expert opinion, contemporary literature review, running the same model under different scenarios, etc. |
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What methods are used for model verification, validation, and testing, if any? Explanation of the question: Are there any inbuilt tools, such as Monte Carlo, or ways to perform sensitivity analyses on model inputs? |
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Uncertainty descriptions |
Can you comment on the uncertainty in model parameters? |
Can you comment on the uncertainty in model input? |
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Can you comment on the uncertainty in the model structure? |
In the following section, each of the models used in the project is described in detail.