Modelling Social Aspects

Modelling social apsects

Following the openmod Workshop in Berlin in January 2020, and especially the session “E.4 Let’s connect: how to model social aspects?“, it was decided a thread on the forum regarding the modelling of social aspects would be of great interest. You can find elements of context hereunder, based on collaborative notes of what was discussed during this session. Feel free to add any comment or contribution, this is thought as an item opening.

Presentation by Diana Süsser (IASS Potsdam)

Presentation as an introduction to the session, (see nextcloud: E4_How to model social aspects_download-version.pdf)
While Social sciences are crucial in the research around climate change mitigation, they get way less fundings than technical sciences (see sources).
QTDIAN is a model library for social scenarios and qualitative storylines. It is based on:

  • Socio-technical transition literature (multi-level, acceptance)
  • Collection and ranking of users’ needs (interviews, workshops)
    And uses the agent based model ATOM from the SENTINEL project.

Topics of general discussion

Processes of adoption of new technologies are not well understood. Various elements can greatly influence decision-making and acceptance:

  • “Windows of opportunity” and “change agents” (Zugpferde) are very important for decision making and acceptance ; strong narratives can be helpful for technology shifts in windows of opportunities (e. g. when different infrastructures like grids reach their lifetime simultaneously).
  • Constellation of strong leaders and existence of opponents have essential influence on adoptions rates.
  • A critical mass of people is often necessary for a perception change.
  • Lifecycle Assessment (LCA) models deal with resource impacts; they in turn can have influence on acceptance of technologies (e.g. critical resources in the production of e-mobility batteries); misinformation of the public often plays a role for acceptance. Other resource availabilities are also important, like scarcity of craftsman
  • Visibility of technologies (e. g. electric car versus building retrofit or heating system) makes a difference in adoption as social comparison is an important factor of end-user demand

Different models with social aspects like acceptance have been developed, but they all lack a reliable database from what we know so far, and therefore are of small use (without reliable data social models can be considered as “dummy” models). That´s one of the central reason why they did not find their way into mainstream so far. Good databases are required.

There can actually be different ways to include social aspects in (transformative) research:

  • A) including social aspects in the modelling, as discussed hereinabove
  • B) including models into society (societal processes)
    • Civil society should be involved in defining the scenarios; they should also be involved in the analysis. The output of models has to be prepared to make it manageable and that is already the first step of analyses. Iteration cycle of model results - reflection of results through civil society - new modeling/results would be desirable. Therefore, models must be easy to understand, transparent in their assumptions (what is based on empirical findings and what are just assumptions) and simple to use.
    • There could be a local use of energy models to make decisions with society and empower it. Once again, some guidance for the users as well as making assumptions and wording very clear in models is essential in order to make sure everyone mean the same thing, for being transparent and reproducible.
    • Something to keep in mind: on local level discussions the “big picture” is often missing (population explosion, other developments, …)
    • also see “STEmp-Tool” & “en-roads” in the sources below, as well as the openmod forum thread An open energy system analysis community

Pending questions:

  • How to model effects such as the ones of misinformation; the citizen empowerment leading to sufficiency?
  • Are linear optimization models suitable for modeling social feedbacks and interactions? Are non-linear models better options and which model types are out there? Logics of interaction and target conflicts may better be seen in simulation models than in optimization models; easier to discuss with decision-makers (politicians, etc.) ; relevant for transformative research. “System Dynamics” models could be of use.
  • How do you obtain reliable social databases? Surveys?
  • Problem of calibration for social models is critical, how to deal with it?
  • IPCC Socioeconomic Pathways include many social parameters; they are not that much used in energy models as the climate modeling and energy modeling communities (Integrated Assessment Models, IAMs) share only few overlap so far - how could this be changed?

First ideas, food for thoughts:

  • Influence could be modelled via scenario-/storyline-based social diffusion curves with different phases/levels of acceptance.
  • Different user groups / social dynamics / drivers / barriers should be reflected
  • Critical mass for acceptance change: modeling with thresholds?
  • Useful theories/concepts for social modeling:
  • Behavioural Economics
  • Social network theories (concept of trust)
    • Theory of bounded rationality
    • Theory of planned behaviour
  • Hybrid agent-based models for decision-making
    • Often misuse of models in policy; we need to reflect what are interpreted as results of a model

Sources, collection of existing research / models

  • On social sciences : socio-political-technical features are excluded in current models (Koppelaar et al., 2016); more work need to integrate social aspects in quantitative modelling (Pfenninger et al., 2014)
  • ZNES (Europa-Universität) Flensburg (Marion Wingenbach, Öko-Institut e.V. Freiburg): 3 years project, collecting data; developing acceptance factors for wind-energy using oemof framework … (PhD thesis). The developed “burden-level” in the ZNES-project could be developed further by including more factors based on a broader analysis of acceptance issues in German society (better understanding of regional distribution of acceptance: role of democratic and financial participation, influence of local natural landscape) [1]
  • en-roads: getting people involved in the global transition [2]
  • After the projekt the developed burden level for wind energy and delay times for grid expansion projects have been integrated in oeko-institute model “powerflex” [3] ; [4]
  • Analysis how a distribution of wind energy on the basis of an equal burden level influence costs of energy transition in PhD thesis [5]
  • Reiner Lemoine Institute: StEmp-Tools: Stakeholder Empowerment tools are made to discuss transformation on a local level [6]
  • Projekt name: “VerNetzen”: Sozial-ökologische und technisch-ökonomische Modellierung von Entwicklungspfaden der Energiewende [7]
  • Diana Süsser developed an ABM on wind energy diffusion (including influence of strong leaders in her PhD thesis)
  • WS on the human in the energy model in 2018: “Was ist die Energiewende ohne uns? Die Menschen im Energiesystemmodell” [8]
  • NIWA: New Zealand Project with Maori about hydrology / indigenous science on acceptance of water extraction from rivers
  • Eco-SESA: Cross Discplinary Program on local renewable energy production & consumption and the involvement of citizen [9]
  • OMEGAlpes : Open Energy Model Generation Tool for MILP Optimization [10]. Social scientists included in the development Lou Morriet PhD thesis [11]
  • Concept of Social energy nodes Gilles Debizet [12]
  • IÖW: model relation between RE-job creation, wealth distribution and acceptance, included through market acceptance factor
  • Anthropology of energy, in rural areas of Germany, Laure Dobigny (in french) [13] ; (Another article in english) [14]
  • German Sociological society and German Physical Society has a modelling team with social focus; organize a yearly conference on social modeling topics
  • Alex Pentland: social physics [15]
  • Cambridge Analytics and Facebook conducted empirical science on acceptance and delivered a reliable empirical data base
  • Atom model (part of SENTINEL project) is an agent based model on decision making regarding energy technologies in households
  • MIDAS - collection of knowledge including models which are used by European Commission and European Parliament; restricted use for other parties (to check) [16] --> could be interesting to look for open access models in the social context there
  • Center for Research in Social Simulation (CRESS) [17]
  • PAC-scenarios of RGI-network could be a good starting point, as they should be compatible with 1.5° climate target [18]
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The Fraunhofer ISE REMod study from February 2020 embeds societal aspects via four scenario definitions, two of which attempt to variously capture resistance to change in the private realm and resistance to new infrastructure. The study is reviewed elsewhere on this forum under the title: REMod pathways study from Fraunhofer ISE, Germany.

The impact of restricting the solution space as indicated may lead to zero‑carbon energy systems several times more expensive than one in which society is fully engaged. The results are specific to Germany and the study mostly examines 95% not 100% decarbonization. Notwithstanding, broadly similar outcomes can be expected to apply under full decarbonization.

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Dear @sacha.hodencq, Thanks a lot for setting up this thread!

Dear all, It was great meeting you all at the openmod. It was great to see that there is so much interest in how to integrate social aspects in energy (system) models.

One observation: while there seems to an growing number of bottom-up models which deals with questions of acceptance and conflicts on mirco-level, there still seems to be only a view approaches how to integrate social aspect in top-down models - espcially that it goes beyond adapting “only” the storyline/scenarios. Thus, we would like to keep up the discussion on that topic.

Some current ideas that have been stated a lot to be integrated in energy models:

  • social acceptance; e.g. in term of effectiveness (denstity, distance)
  • community participation
  • rebound effects
  • path dependence and deferral/delate action ; e.g. aspects of delays in expansion
  • energy poverty
  • policy preferences
  • socio-economic implications, such as jobs

It would be great to keep up posting new studies here that address modelling social aspects.

In order to keep up the discussion, we would like to form a group of people actively working on that topic and who would like to exchange further. Drop me a message if you like (diana.suesser[at]iass-potsdam.de)! I’m thinking of an online meeting in summer.

Thanks for sharing thoughts and suggestions.
Best, Diana

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Dear Sascha, dear all,

Thanks also from my side for continuing this work, @sacha.hodencq! One addition to @dianasuesser posting: I presented our QTDIAN concept also at a DLR-workshop in Oldenburg some days ago. We conducted the same Mentimeter poll that was included in Diana´s kick-off presentation (but this time in German): “Which neglected social aspects should be integrated into energy models?” A lot of the answers were similar but maybe there are new ideas for some of you. I have attached the additional Word Cloud to the post.

.

Kind regards,
Hannes

PS: If someone is interested, the etherpad/minutes of our initial E4-workshop at the OpenMod conference can be found here.

PPS: Another important, but probably for most of us long-forgotten model that has had much impact on the environmental movement and reflected different social aspects from a system dynamics perspective is World3 of the “limits to growth”-report. See, e. g., here.

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Just posting as a site moderator. There are several advantages if people use @‑handles rather than plain text names: clickable, notifications sent, and later machine anonymizable.  R.

Dear all interested in modelling social aspects of the energy transition!

I’m glad to inform you that the first version of our QTDIAN modelling toolbox has just been published: The QTDIAN modelling toolbox–Quantification of social drivers and constraints of the diffusion of energy technologies. Deliverable 2.3. Sustainable Energy Transitions Laboratory (SENTINEL) project | Institute for Advanced Sustainability Studies

QTDIAN is a toolbox of qualitative and quantitative descriptions of socio-technical and political aspects of the energy transition that influence the overall potential, the rate of energy-related technology and service diffusion and the design of the future energy system. In this report, we (i) develop qualitative social storylines of the energy transition that specifically consider the social developments and dynamics of the energy transition; and (ii) provide quantifications for six thematic elements of the social storylines, in formats allowing these data to be directly used in energy models. We develop QTDIAN based on the needs of both modellers and users of the models, which we identified in SENTINEL WP1 and WP7. We develop the social storylines based on transition theory and on empirical observations of actual drivers and barriers. The output of QTIDIAN is empirically founded datasets of social and political drivers and barriers of the transition, both in the form of raw data describing past and current developments and manipulated to constitute consistent quantifications of the storylines.

Please get in touch with me in case of any questions! We look forward to the applications of QTDIAN in the context of the SENTINEL energy projects and beyond.

Best, Diana

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Just to note that other interesting work from the Europe‑based SENTINEL project includes this look at the interrelationships between modeling efforts and policy development:

Süsser, Diana, Andrzej Ceglarz, Hannes Gaschnig, Vassilis Stavrakas, Alexandros Flamos, George Giannakidis, and Johan Lilliestam (1 May 2021). “Model-based policymaking or policy-based modelling? How energy models and energy policy interact”. Energy Research and Social Science. 75: 101984. ISSN 2214-6296. doi:10.1016/j.erss.2021.101984. Creative Commons CC‑BY‑4.0 license.

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Hi,

It is very good to see an interest in the challenge of modelling social aspects of energy systems in this forum. I recently started my PhD on the topic and look forward to discussions on how this can be achieved and improved!

I hope it is fine to share an invitation to a workshop I am hosting on a similar topic in September 2021.

Online research workshop on the inclusion of justice perspectives in energy systems modelling
Drawing from previous interdisciplinary workshops between meteorologists/climate scientists and energy modellers, we want to try something similar with social scientists/energy justice scholars.

Target participants
Energy system modellers (with curiosity about inclusion of social aspects) and social scientists open to explore links between their work on energy issues and energy system modelling.

If someone is interested in more information there is the Workshop website and the sign-up form.

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Social attitudes and influences

A mid‑2021 study on climate‑related social attributes and influences based on sampling in the United States:

Andre, Peter, Teodora Boneva, Felix Chopra, and Armin Falk (30 June 2021). Fighting climate change: the role of norms, preferences, and moral values — ECONtribute Discussion Paper No 101. Germany: ECONtribute. JEL‑Codes: D64, D83, D91, Q51, Z13.

And one quote from the abstract:

Respondents vastly underestimate the prevalence of climate-friendly behaviors and norms among their fellow citizens.

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What is the current representation of social factors in energy models?

In our ENERGY paper we analysed energy model studies to map the current integration and identify perspectives for future research. We asked: Which model types are particularly good at integrating social aspects? What social aspects are represented in energy models? How are these social aspects integrated?

We find:

  • Models represent social aspects mainly as exogenous assumptions or output discussion.

  • Some approaches exist that go beyond pure cost optimisation/simulation.

  • But the techno-economic model design remains, except for agent-based models.

  • Thus, more interdisciplinary research is need to enhance linking of energy modelling and social science.

You can find the paper here: Modelling social aspects of the energy transition: What is the current representation of social factors in energy models? - ScienceDirect
PM for private fulltext!

Please reach out for questions and feedback!

An enlightening article (in my opinion), on the notions of justice in energy modelling. I find the introduction of the various concepts of justice very accessible, even for an energy modeller as myself :wink:

  • Vågerö, Oskar, et Marianne Zeyringer. 2023. « Can We Optimise for Justice? Reviewing the Inclusion of Energy Justice in Energy System Optimisation Models ». Energy Research & Social Science 95 (janvier): 102913. https://doi.org/10.1016/j.erss.2022.102913.
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