Staging area 1
This staging area is intended for potential contributors. Please feel free to edit and update the description of your intended in person contribution as your ideas evolve. Some of the entries listed here may still be at an early stage of development. Not all suggestions will necessarily be selected or developed into lightning talks or presentations.
The deadline for submitting your potential contribution is May 31st 2026. After this deadline passes, the organizing group will screen the suggestions and develop the final program.
This is a wikipost that anyone registered with the forum can edit. You are encouraged to add your potential contributions directly here therefore. The order given is chronological downwards.
Note also that the topics and postings on this forum related to this event will be reorganized as the content builds. So just be aware that some URLs will break going forward. But the cape-town-workshop-2026 tag will persist.
Lightning talks:
Each lightening talk consists of a 6 minutes presentation followed by 4 minutes of Q&A. Profile your favorite project, tool, data, research findings, etc
When adding your lightening talk contribution, it should look something similiar to the following example post
Example
title : Using a global energy system model for a detailed country study
presenter : Martha Frysztacki (Open Energy Transition)
description : This presentation introduces a case study applying PyPSA-Earth for an energy transition study in Kazakhstan. We will show how we tailored a global open energy system model with high spatial and temporal resolution data to the specific country’s requirements. The novel approach avoids the time-consuming creation of models for every country and fosters collaboration, addressing the challenges of the energy transition together. Extended from this paper in Applied Energy .
code repository : GitHub - pypsa-meets-earth/pypsa-earth: PyPSA-Earth: A flexible Python-based open optimisation model to study energy system futures around the world. · GitHub
literature : Based on “PyPSA-Earth. A new global open energy system optimization model demonstrated in Africa”. Applied Energy . 341 : 121096. ISSN 0306-2619. doi:10.1016/j.apenergy.2023.121096
Proposed contributions (please add your talk below 
following the above template/style)
title : Using a global energy system model for a detailed country study
presenter : Hazem Abdel-Khalek @Hazemakhalek, Martha Frysztacki (Open Energy Transition)
description : This presentation introduces a case study applying PyPSA-Earth for an energy
transition study in Kazakhstan. We will show how we tailored a global open energy
system model with high spatial and temporal resolution data to the specific country’s
requirements. The novel approach avoids the time-consuming creation of models for
every country and fosters collaboration, addressing the challenges of the energy
transition together.
code repository :
literature :
title : Supporting Open Energy Planning in African Power Systems
presenter : Albert Chitandula, Mwiche Simpemba (Open Energy Transition)
description : This initiative supports African utilities and system operators in strengthening their capacity to plan and operate climate-resilient, modern power systems using open-source energy modelling tools. By working with utilities and regional partners, the project explores how open tools can improve transparency, collaboration, and power system planning. Starting with pilot activities in Zambia, the initiative seeks to demonstrate practical use cases and support broader
adoption of open approaches to energy planning across the region.
code repository : GitHub - open-energy-transition/pypsa-zambia: PyPSA-Zambia: A flexible Python-based open optimisation model to study energy system futures for Zambia · GitHub
literature :
title : Mapping Energy Modelling Tools: openmod-tracker & Feature Inventory
presenter : Hazem Abdel-Khalek, Bryn Pickering (Open Energy Transition)
description : Open energy modelling tools are growing rapidly, but it is often unclear which tools exist, what
they can do, and where key functionality gaps remain. The openmod-tracker and Feature
Inventory map tools and their capabilities to improve transparency and coordination. This
lightning talk introduces these resources and invites contributions to expand coverage and
highlight gaps compared to proprietary software.
code repository :
literature :
title : Benchmarking Energy System Solvers: Insights from HiGHS and Open
Energy Benchmark
presenter : Sid Krishna, Daniele Lerede, Enrico Antonini (Open Energy Transition)
description : Efficient solvers are critical for large-scale energy system modelling. Recent benchmarking efforts, including developments around HiGHS, are helping the community better understand solver performance across different modelling problems. This lightning talk highlights the Open Energy Benchmark platform (openenergybenchmark.org) and ongoing benchmarking
activities that compare solvers in a transparent and reproducible way. The goal is to raise
awareness of these efforts and encourage broader participation in benchmarking and
performance testing across energy modelling tools.
code repository :
literature :
title: Developing a PyPSA-SAPP Model
presenter: Meridian Economics
description : This presentation introduces the development of a PyPSA-Earth based model for the Southern African Power Pool (SAPP). It outlines how the model has been adapted to better reflect the region, including transmission representation and improvements to coal fleet modelling. There are additionally key data updates, such as revised demand profiles, improved technology assumptions for South Africa and a custom renewable energy development zone raster for the region. Additionally, we will present some key insights that have emerged from the model.
title: Collaborating on Open Energy Modelling for the SAPP
presenter: Meridian Economics
description : This breakout session aims to explore opportunities for collaboration around the PyPSA-SAPP model. We will discuss how open energy system models can benefit from broader engagement with contributions to data, methodology and scenario design. Participants are encouraged to share their needs, ideas and potential contributions.
Code repository:
title: Modelling and Improving Electricity Reliability in South Africa Using Satellite Nightlights and PyPSA-Earth
presenter: Nylan Ramnauth, Ravi van Os, Barcelona School of Economics
description : This presentation introduces a novel remote sensing methodology to model electricity unreliability in hourly power system models. By using daily observations of satellite night-light, we derive a proxy of electricity reliability at the settlement level. In parallel, we validate a customised PyPSA-Earth model of South Africa against historical ESKOM data. Our aim is to integrate this reliability measure, aggregated at the official supply/local area level, into the model to help improve investment decisions for unreliable grids in data-scarce countries. The model is designed to be data-agnostic, depending on the availability of granular data on outages. We welcome any collaboration on the methodology or its implications for South Africa and countries beyond.
Code repository
title: Grid Builder: An Open-Source Bridge Between Geospatial Communities and Energy Modelers
presenter: Emmanuel Bolarinwa, Open Energy Transition
The effectiveness of open-source energy modeling tools is often hampered by “siloed” data cleaning workflows. Researchers frequently duplicate efforts to fix the same recurring errors in regional grid datasets. Grid Builder proposes a unified, collaborative pipeline that acts as a bridge between three specific groups: the OpenStreetMap community, the “Map Your Grid” initiative, and the broader energy modeling ecosystem.
We introduce the modular architecture of Grid Builder, focusing on its ability to process diverse data streams into standardized GeoJSON and data packages compatible with multiple modeling frameworks. We highlight the integration of empirical insights specifically addressing the lack of localized line-type catalogs that were identified during recent grid impact assessments.
title: From Silos to Systems: Meet the M3 Modelling Platform
presenter: Madeleine McPherson, University of Victoria Canada
The M3 (Multi-Model Mapping and Modelling) Platform is an integrated energy systems modelling framework developed to support complex decision-making in Canada’s energy transition. Rather than relying on a single model, M3 links a suite of complementary tools that operate across different scales, sectors, and methodological approaches. Core components include capacity expansion modelling, macro-economic modelling, energy demand modelling, and high-resolution operational simulation, alongside input data infrastructure and output visualization tools.
What makes M3 novel is its integrated but modular architecture. Models exchange outputs—such as electricity prices, demand profiles, and system configurations—until results converge, enabling consistent representation of interactions between supply, demand, infrastructure, and policy. This allows the platform to capture feedbacks that are typically missed in siloed modelling approaches, such as how electricity prices influence end-use demand, or how demand shifts affect optimal generation and transmission investments.
The platform is particularly valuable for evaluating multi-dimensional outcomes, including system costs, emissions, reliability, and economic impacts. By integrating diverse modelling paradigms into a unified workflow, M3 provides policymakers with a robust, transparent, and flexible tool to assess pathways toward a net-zero, integrated energy system.
code repository: https://m3.cme-emh.ca
title: OpenGridTwin-Africa: An Open-Source AI Digital Twin Framework for Climate-Resilient Power System Planning in African Grids
presenter: Kwabena Addo, Kumasi Technical University (KsTU), Ghana
African power systems are increasingly facing complex planning challenges driven by rapid demand growth, renewable energy integration, ageing infrastructure, weak-grid conditions, and climate-related disturbances such as heatwaves, storms, droughts, and renewable-resource variability. This talk proposes OpenGridTwin-Africa, an open-source AI-enabled digital twin framework designed to support climate-resilient and intelligent power system planning in African grids. The framework integrates open-source energy modelling tools, grid simulation engines, climate data, and artificial intelligence methods to create a transparent platform for testing future grid scenarios, evaluating climate-related vulnerabilities, and supporting data-driven planning decisions. It is intended to help researchers, utilities, system planners, and policymakers assess how African power networks respond to renewable variability, extreme weather events, demand growth, and infrastructure constraints. The talk will present the motivation for the framework, its proposed architecture, possible open-source toolchain, African grid use cases, and opportunities for collaboration with the OpenMod community. The goal is to encourage the development of open, reproducible, and climate-aware modelling approaches that can strengthen power system planning and resilience across Africa.
Code Repository:
The code repository is currently under preparation and will be made available once the initial framework structure is finalized.
title: Modelling bioenergy: Accounting for carbon stock changes from foregone carbon storage
presenter: Timon Renzelmann, Chalmers University of Technology, Sweden
Bioenergy is often modelled as carbon neutral even though its production causes changes in land carbon stocks. In this talk and discussion, I will make the case for integrating these effects into energy system models while providing examples from a European case study. I will also introduce a new welfare-grounded methodology of weighting emissions over time. This approach allows for collapsing complex time series of carbon stock changes induced by biomass harvest and regrowth into practical emission factors.
literature: in preparation for submission
title: SPLICE: Soft-linked Planning for Integrated eLectrification and Capacity Expansion — a PyPSA-Earth and OnSSET framework for Uganda
presenter: Corrado Maria Caminiti (Politecnico di Milano, Department of Energy), Davide Fioriti ( Università di Pisa)
This presentation introduces SPLICE (Soft-linked Planning for integrated eLectrification and capacity Expansion), an open-source iterative framework connecting PyPSA-Earth and OnSSET to produce nationally consistent, geospatially explicit integrated energy and electrification plans for low and middle income countries, with Uganda as the primary case study. The name SPLICE reflects the methodological ambition of the framework: to join two planning layers that the existing literature has consistently treated as separate, stitching the supply-side network optimization of PyPSA-Earth to the community-level access planning of OnSSET into a single coherent workflow.
PyPSA-Earth serves as the core component of SPLICE, providing network-feasible generation expansion, transmission planning, and hourly dispatch analysis within a physically grounded network structure. Its ability to represent transmission constraints, renewable integration, and ramping limitations makes it particularly suited to Sub-Saharan African contexts where grid bottlenecks materially influence planning outcomes. OnSSET provides the geospatially explicit electrification masterplan, allocating technology across communities based on a least-cost backcasting logic. The two tools are coupled through an iterative workflow: PyPSA-Earth produces the nodal cost-of-electricity signal that drives technology allocation in OnSSET; the resulting grid-connected demand is aggregated and fed back into PyPSA-Earth to update the generation portfolio; the process iterates until convergence. SPLICE also introduces a methodological extension to PyPSA-Earth enabling the explicit representation of transmission lines under construction, allowing the framework to incorporate national development plans and evaluate investment sizing, timing, and prioritization within the optimization. Applied to Uganda under three scenario narratives, SPLICE demonstrates that the carbon constraint and network topology jointly determine both the long-term generation mix and the spatial distribution of electrification technology, and that endogenous investment decisions recover Uganda’s planned transmission corridors through cost-driven optimization alone.
Code Repository: GitHub - CorradoMariaCaminiti/SPLICE: Soft-linked Planning for integrated eLectrification and capacity Expansion · GitHub
literature: in preparation for submission
title: Identification of Offgrid areas for solar expansion energy markets in Ethiopia using EAE
presenter: Tesfu Kidane Aregawi (Ministry of Water and Energy Ethiopia)
This contribution presents a geospatial analysis of Ethiopia’s off-grid regions to identify where solar energy expansion is most viable. Using the Energy Access Explorer (EAE), the analysis evaluates areas with sufficient population density, ability to pay, distance from existing grids and strong solar irradiation levels.
The analysis identifies 13,274 km² and 4.1 million people with medium-to-high energy access potential, concentrated primarily in the Oromia, Amhara and Sidama regions. This contribution offers a practical framework for directing solar investments and shaping enabling policies to accelerate equitable electrification.
Code Repository: Identification of Off-grid areas for Expansion of solar energy markets in Ethiopia using energy access explorer
literature: in preparation for submission
title: Optimal Resource Mix for Indian Power Sector Decarbonization by 2070
presenter:Aravinda De Chinnu Arul Babu (Indian Institute of Technology Bombay)
The presentation argues for incorporating the impacts of climate change on the capacity factors of solar PV and wind, given their weather-dependent power generation. It also considers the corresponding impacts on electricity demand and explains the need to incorporate emerging demand drivers, such as increased cooling needs under a warming climate, while estimating future resource mixes. Finally, the presentation motivates exploring alternative near-optimal resource mixes, since strictly cost-optimal solutions are often highly extreme; moving slightly away from them can reveal fundamentally different yet cost-comparable resource configurations.
Model: Capacity expansion model developed using the formulations of the open-source GenX model in Python.
title: Waste-to-Energy Pathways from Agricultural Biomass in Ethiopia
Presenter: Desta Mulu Gebeyehu (Stellenbosch University, South Africa)
This presentation highlights ongoing research on the conversion of agricultural and invasive biomass resources to sustainable bioenergy products in Ethiopia. Focus on the production of bioethanol from water hyacinth, biochar applications, and broader waste valorization approaches for climate change mitigation and circular bioeconomy development.
The talk will also discuss the contribution of locally available biomass resources to renewable energy access, environmental sustainability and low-carbon development pathways in African contexts. Additionally, it will identify opportunities to integrate open-source energy modelling approaches for biomass resource assessment and sustainable energy planning.
Code repository: Not applicable (research-based presentation; tools and datasets are under development)
Literature: Relevant studies on biomass conversion technologies, bioethanol production from invasive aquatic plants, biochar applications, and sustainable bioenergy systems in sub-Saharan Africa.
title: Macro-Med: Extending European Energy System Modelling to the Southern Mediterranean
presenter: Alice Di Bella (EIEE - CMCC, Milan)
description: This lightning talk presents Macro-Med, a macro-energy modelling framework that extends the geographic scope of European energy system models to the southern shore of the Mediterranean Sea. Built on MacroEnergy.jl, the model investigates cross-regional energy interdependencies and transition pathways across both shores of the Mediterranean. Data pipelines are sourced from PyPSA-Eur and PyPSA-Earth, enabling consistent and reproducible integration of European and North African energy system data.
code repository: MacroEnergy.jl
literature: MacroEnergy.jl – arXiv:2510.21943
title: From Data to Decisions: Structuring Value for Sustainable Energy Planning
Presenter: Meng Yuan/Frederik Dahl (Aalborg University, Denmark)
Description: Energy system modelling and planning are increasingly data-driven, but more data does not automatically lead to better decisions. This presentation focuses on translating data, regardless of its availability and accessibility, into effective decision-making tools for sustainable energy planning. We will present three cases across different data and geographic contexts: the Strategic Heating Plan for Mongolia, representing a data-scarce environment; Heat Roadmap Europe 5, representing a data-rich context; and a local carbon storage case in Denmark, illustrating how data and models create value when embedded in decision-making processes. These cases use GIS to organise and analyse spatial energy data, while the energy system simulation tool EnergyPLAN is applied to develop scenarios and assess their implications for planning. Across these cases, the presentation shows that data value depends not only on availability or resolution, but on its ability to inform real planning choices. It argues that the question is not simply whether we have enough data, but whether we are using it in ways that support modelling for better decisions.
title: From passive loads to active buildings: Bottom-up dynamic modelling of demand-side flexibility and decarbonisation pathways with DREEM
Presenters: Vassilis Stavrakas, Alexandros Flamos {Technoeconomics of Energy Systems laboratory (TEESlab), University of Piraeus Research Center (UPRC)}
Description: Buildings are often treated in energy-system models as fixed demand curves. But in the transition to net zero, buildings are becoming much more than passive consumers. Renovation, heat pumps, cooling demand, rooftop photovoltaics, storage, electric vehicles, behavioural patterns, comfort needs, and demand response can all reshape when, where, and how energy is consumed. This lightning talk presents the Dynamic high-Resolution dEmand-sidE Management (DREEM) model, an open-source bottom-up simulation framework developed to analyse energy transition pathways in the buildings sector. DREEM is able to represent heterogeneous building stocks, end-use technologies, energy efficiency measures, heating and cooling systems, distributed energy resources, and flexible demand strategies at high temporal and technological resolution.
Rather than relying on static or aggregated demand projections, DREEM captures how building characteristics, technology choices, behavioural assumptions, and policy interventions interact to shape future hourly electricity and thermal demand profiles. These outputs can feed into power-system, capacity-expansion, operational, integrated energy-system, and agent-based models, helping improve the representation of demand dynamics, peak loads, flexibility potential, and wider system impacts. All the model’s modules have been developed using the “Buildings” library, an open-source, freely available Modelica library for building energy and control systems. Alongside the Modelica models, Python scripts have been developed to model parts of the model’s components and to enable the interface with the Dymola simulation environment. The model is open access under the “GNU Affero General Public License”.
DREEM has already been applied in policy-relevant contexts, including the development of building-sector decarbonisation pathways for the Peloponnese Region in Greece, the assessment of transition strategies supporting the revision of the Greek National Energy and Climate Plan (NECP)’s targets in the residential sector, and the development of the recent Greek Long-Term Renovation Strategy (as of recently National Building Renovation Plan - NBRP). Its modular architecture also makes it suitable for open, interoperable, multi-model workflows aimed at evaluating net-zero transitions across different spatial and governance scales. This contribution aims to open a discussion with the Openmod community on how bottom-up demand-side models can better connect with open energy-system modelling frameworks, so that buildings are no longer treated as background demand, but as active, flexible, and policy-relevant components of future energy systems.
Code repository: GitHub, IAM PARIS platform.
Literature: “A modular high-resolution demand-side management model to quantify benefits of demand-flexibility in the residential sector”. Energy Conversion and Management. 205 : 112339. ISSN 0196-8904. doi:10.1016/j.enconman.2019.112339.
“Towards decarbonisation or lock-in to natural gas? A bottom-up modelling analysis of the energy transition ambiguity in the residential sector by 2050”. Energy Conversion and Management. 324 : 119235. ISSN 0196-8904. doi:10.1016/j.enconman.2024.119235.
“Expanding natural gas infrastructure in Greece: Good practice or missed opportunity of a green and inclusive transition?”. Energy. 326 : 136314. ISSN 0360-5442. doi:10.1016/j.energy.2025.136314.
“Modelling in support of community-empowered energy transitions: Transforming a coal- and carbon-intensive region into a municipality of energy citizens”. Environmental Innovation and Societal Transitions. 59 : 101079. ISSN 2210-4224. doi:10.1016/j.eist.2025.101079.
title:Beyond “most likely” futures: Navigating deep uncertainty and designing adaptive policy pathways for robust decision-making with AIM
Presenters: Nikos Kleanthis, Vassilis Stavrakas, Alexandros Flamos {Technoeconomics of Energy Systems laboratory (TEESlab), University of Piraeus Research Center (UPRC)}
Description: Energy and climate policies are often designed around a limited set of scenarios, or even worse, around a single “most likely” future. But real transitions rarely unfold as expected. Technology costs change, social behaviour shifts, economic conditions evolve, climate impacts intensify, political priorities move, and policies that once appeared optimal may become fragile, ineffective, or even counterproductive. This lightning talk presents the Adaptive polIcymaking Model (AIM), a decision-support framework developed in Python to help policymakers move from static scenario-based planning towards dynamic adaptive policy pathways (DAPPs). Rather than producing new scenarios itself, AIM translates outputs from integrated assessment models, energy-system models, macroeconomic models, sectoral models, and other simulation tools into policy pathways that can be stress-tested under deep uncertainty.
AIM evaluates alternative policy and strategy packages across large ensembles of future contextual conditions, identifying where they succeed, where they fail, and under which combinations of uncertainties they remain robust. In doing so, it helps users move beyond the question “Which policy works best in one future?” towards the more policy-relevant question “Which policy pathways remain effective across many plausible futures, and when should they adapt?” A key feature of AIM is its ability to connect model-based assessment with adaptive policymaking through signposts, triggers, monitoring indicators, and policy adaptation points. This allows users to explore not only what should be implemented now, but also what should be monitored over time, when a policy change may be needed, and which alternative pathway to follow next. Through interactive and stakeholder-friendly visualisations, AIM supports transparent discussion of trade-offs, vulnerabilities, opportunities, and dead ends in long-term transition planning.
The framework has already been applied in energy-transition research, including work on dynamic adaptive policy pathways for small-scale photovoltaic deployment in Greece and recent soft-linking with the JRC-EU-TIMES model to explore long-term zero-emission transition pathways by 2050 in Switzerland. This contribution aims to open a discussion with the Openmod community on how open modelling workflows can better support robust, adaptive, and decision-relevant policymaking under deep uncertainty.
Code repository: GitHub.
Literature: “A transdisciplinary modeling framework for the participatory design of dynamic adaptive policy pathways”. Energy Policy. 139 : 111350. ISSN 0301-4215. doi:10.1016/j.enpol.2020.111350.
- Incorporating Local Grid Infrastructure Costs into Renewable Energy LCOE: A South African Case Study
Presenters: Johannes de Bruyn - Centre for Renewable and Sustainable Energy Studies (CRSES) - Stellenbosch University
Abstract: Long-term power system planning relies on techno-economic optimisation models to determine the necessary generation capacity expansions. These models typically use generic economic data for generators, with limited representation of location-specific transmission and distribution network and grid connection costs required to deliver energy from resource areas to the transmission grid. This may lead to overly optimistic levilised cost of energy (LCOE) values for geographically dependent renewable energy resources in grids like South Africa, where access varies drastically by region. This talk addresses this gap by integrating local grid infrastructure costs into the LCOE and showing how the LCOE evolves as more renewable power plants are connected in a region. The modelling framework uses high-spatial-resolution DIgSILENT PowerFactory load-flow models to simulate increasing penetrations of renewable energy sources and to cost the infrastructure required to host them. Integrating these localised LCOE curves into long-term planning frameworks significantly enhances the optimisation of future renewable energy deployment.
Data Repository: The data repository is currently under preparation and will be made available once the initial framework structure is finalised.
Title: Standardizing South Africa’s Electricity Modelling Landscape: An Open-Source, Collaborative Data Repository and Reference Dataset for Capacity Expansion and Unit Commitment Modelling
Presenter: Tiaan Vivier, Centre for Renewable and Sustainable Energy Studies (CRSES) - Stellenbosch University
Abstract: Energy system modelling is vital for navigating South Africa’s energy transition, yet researchers frequently face data bottlenecks, leading to siloed assumptions regarding critical parameters like thermal generator ramp rates and heat rate curves. To resolve this, a standardized, open-source energy dataset for South Africa is proposed, utilizing transparent approximation methodologies to reliably infer missing technical parameters where public data is restricted. This initiative will be launched on a public data repository hosted by Stellenbosch University as a multi-university collaboration, creating a space where stakeholders can critique and suggest revisions. Drawing on international benchmarks, this presentation will examine the challenges and opportunities of such open-source frameworks and discuss how global best practices can be adapted to the South African context. To support evolving system needs, the repository will feature ongoing version updates; major consensus baselines will be published as citable, peer-reviewed journal articles (e.g., Elsevier), establishing a transparent, authoritative, and living foundation for national energy modelling.
Code Repository: The code repository is currently under preparation and will be made available once the initial framework structure is finalized.
Contribution Format: Lightning Talk
Title: PyPSA-CMP: a dispatch model for Africa’s Continental Master Plan
Presenter: Tinne Mast (Vrije Universiteit Brussel, VITO/Energyville)
Description: This presentation introduces PyPSA-CMP, an open-source power system dispatch model of the African continent implemented within PyPSA framework. The model is developed in the context of the African Union’s Continental Master Plan (CMP), a long-term roadmap under AU Agenda 2063 for the development of Africa’s electricity infrastructure connecting the five regional power pools. PyPSA-CMP complements the existing SPLAT-CMP capacity expansion model, outlining the conception of the CMP, by simulating hourly system operation and capturing variability from diurnal to seasonal timescales including four decades of weather data. The model allows to investigate renewable synergies and complementarities across the continent’s power system under scenarios of increasing grid integration.
Code repository: In preparation for submission.
title: Carbon Taxes and Revenue Recycling in South Africa’s Power Sector – Insights from PyPSA-RSA
Presenter: Agatha Majcher (Europa-Universität Flensburg, Reiner Lemoine PhD Group)
Abstract: South Africa’s carbon tax is gradually expanding its reach in the energy sector, yet the distributional consequences of different revenue recycling mechanisms remain underexplored. This lightning talk presents ongoing modelling work using PyPSA-RSA to assess how carbon pricing interacts with electricity system investment and dispatch, and how revenue recycling schemes affect system costs and distributional outcomes. I will share first results and open questions and welcome feedback from the community.
title: A Monitoring, Evaluation and Learning (MEL) Framework for Energy and Resource Modelling Capacity Development
Presenter: Carolina Rodrigues Poupinha (KTH Royal Institute of Technology)
Description: Energy and resource planning models are increasingly important for sustainable development policy, yet capacity-building efforts for these tools are rarely evaluated systematically. This talk introduces a MEL framework tailored to energy and resource modelling training, integrating established evaluation approaches with modelling practice across planning, monitoring, evaluation, and learning stages. The framework is piloted through a post-training survey distributed at a CLEWs training in Lusaka, Zambia (n=18). We discuss what we learned and how the framework can help improve energy and resource modelling technical assistance programmes for sustainable development.
Code repository: Not applicable (datasets under development)
Literature: under preparation for submission.
title: Can LLMs Make Energy System Models Usable by Non-Specialists?
Presenter : Fabrizio Fattori (University of Insubria)
Description : The complexity of energy-system models often limits their direct use by non-specialist stakeholders. This lightning talk, based on ongoing research, explores the use of a large language model as a conversational interface for an existing energy-system model. The proposed workflow translates policy-relevant questions into model operations and provides accessible explanations of the results. The talk aims to stimulate discussion on whether LLMs can help democratise access to energy models, enabling public administrations and local authorities with limited resources to integrate modelling tools more directly into their planning processes. At the same time, it raises the question of whether such tools may complement the work of energy modellers or instead challenge existing consultancy-based roles in energy planning.
code repository : not yet available
literature : not yet available
title: Systems Modelling for Sustainable Mining: Addressing electricity demand and supply for Copper and Cobalt extraction in the DRC
Presenter: Mashaka Audry Lubenga (University of CapeTown)
Short description: As a leading producer of critical minerals, including copper and cobalt, the Democratic Republic of Congo (DRC) must reconcile rising mining-sector electricity demand with severe domestic power shortages. This study fills a critical gap in national energy planning by coupling the Geologic Resource Supply-Demand Model (GeRs-DeMo) with the Open-Source Energy Modelling System (OSeMOSYS) to forecast electricity demand for copper and cobalt extraction and optimize the regional power mix through 2050.
Mining electricity demand is projected to peak between 2.8 GW (2033) and 3.5 GW (2043), requiring national grid capacity to expand from 2.2 GW to up to 15.7 GW. Although hydropower remains central, solar PV with storage emerges as the most economically viable and rapidly deployable option to displace carbon-intensive diesel self-generation, which caused 44% of greenhouse gas (GHG) emissions from copper and cobalt production in 2024. However, dominant mining-sector investments risk entrenching uneven domestic energy access. Integrating industrial power demand into broader infrastructure planning is vital to align mining-sector development with national climate and social electrification goals.
code repository :
literature :
title: Integrating Capacity Expansion, Flexibility and Network Planning Tools for Renewable Energy Pathway Analysis in the Southern African Power Pool
Presenter: Keith Katyora (University of CapeTown)
Description: This presentation will explore an integrated open-source modelling workflow developed as part of an MSc Electrical Engineering research study at the University of Cape Town, focused on renewable energy integration pathways within the Southern African Power Pool (SAPP).
The session will discuss how different modelling approaches and tools can be combined to support more holistic power system planning under high renewable penetration scenarios. In particular, the presentation will reflect on the integration of:
- OSeMOSYS for long-term capacity expansion planning,
- FlexTool for operational flexibility assessment, and
- network and transmission planning considerations to better understand system feasibility and regional interconnection requirements.
The presentation will further reflect on some of the practical challenges associated with linking long-term planning outputs with operational and transmission-level constraints in the context of emerging African power systems. The intention is not only to present modelling results, but also to contribute to broader discussions around transparency, interoperability, and integrated open-source energy modelling frameworks for developing power systems.
The work is positioned within ongoing research on renewable integration, flexibility requirements, and transmission expansion pathways in the SAPP region.
title: OPTIMISING THE ENERGY MIX FOR ECO-INDUSTRIAL PARKS IN DEVELOPING COUNTRIES: A LEAST-COST ANALYSIS USING PYPSA
Presenter: Stefan Karamanski (CSIR)
Description/abstract: As a result of persistent loadshedding since 2008, numerous industries have increased their efforts to adopt alternative energy technologies to lessen their reliance on the national grid. Industrial spaces are no exception, particularly with the emergence of eco-industrial parks - a group of manufacturing and service businesses situated on a shared property. Questions arise regarding how much an industrial park can decrease its reliance on the national grid and how much emissions can be reduced by utilizing an optimal combination of available energy technologies. These questions are addressed through a least-cost optimisation case study of a medium-sized eco-industrial park. A customised capacity expansion planning tool built on the open-source platform Python for Power System Analysis (PyPSA) is employed in the study. Renewable energy is sourced from rooftop solar PV and an offsite wind installation.
Energy storage is provided by commercially available LiFePO4 containerised lithium-ion batteries. The model assumes a multiyear simulation horizon, with learning rate assumptions for the
renewables based on the NREL Annual Technology Baseline report. Several scenarios are modelled, and the outcomes are compared to a “business as usual” case, where reliance is solely
on the national grid and no embedded renewable energy is employed. The study shows that the employment of currently available renewable energy solutions offers industrial spaces a significant cost saving and a reduced carbon footprint while simultaneously reducing their dependence on the grid.
Literature: Grobler, JH., Karamanski, S., Zandamela, F. (2026). Optimising the Energy Mix for Eco-industrial Parks in Developing Countries: A Least-Cost Analysis Using PyPSA. In: Trois, C., Kaseke, R., Sempiira, J.E. (eds) Proceedings of the 2024 Southern African Sustainable Energy Conference. SASEC 2024. Springer Proceedings in Energy. Springer, Cham. Optimising the Energy Mix for Eco-industrial Parks in Developing Countries: A Least-Cost Analysis Using PyPSA | Springer Nature Link
title:The modeller’s dilemma: honesty, influence, and responsibility in energy-transition planning
Presenter/facilitator: Gregory Ireland, Principal Research Analyst, University of Cape Town Energy Systems Research Group
Contribution format: Breakout session / facilitated discussion
Description: Open energy modelling is often presented as a technical project: sharper tools, better data, standardized workflows, end-to-end reproducibility. These are all essential. But in real planning processes, models do not operate in a neutral space. They sit at the boundary between science, evidence, institutions, political economy, public trust, investment decisions, emotional narratives, and contested futures.
This session asks a deliberately uncomfortable but practical question: how honest should energy modellers be when the future is on the line?
How do we communicate uncertainty without becoming timid?
How do we avoid turning models into sophisticated justification machines for decisions already made elsewhere?
When should modellers remain neutral analysts, and when do they have a responsibility to challenge misleading assumptions, opaque processes, or politically convenient narratives?
The discussion will use energy-transition planning examples from South Africa and invite those from other contexts to explore common tensions: transparency versus diplomacy, technical rigour versus real-world influence, open models versus closed decision processes, and the risk that modelling communities produce increasingly fancy tools without changing the quality or direction of actual decisions.
The session is intended as an open, reflective, and constructive discussion rather than a conventional presentation. It is aimed at researchers, modellers, planners, policymakers, utilities, consultants, and civil-society actors who want open energy modelling to matter in practice, not only as a technical exercise but as part of better public decision-making.
Possible guiding questions:
- What does “honesty” mean in applied energy modelling: publishing assumptions, showing uncertainty, naming trade-offs, or challenging misleading narratives?
- How should modellers handle cases where technically sophisticated modelling is used to legitimise weak, opaque, or politically predetermined decisions?
- Where is the line between being policy-relevant and becoming politically captured?
- What responsibilities come with open-source tools when the surrounding planning process is not open?
- How can modelling communities build credibility without becoming naïve about power, incentives, and institutional constraints?
Code repository:
Not applicable.
Literature:
Not a literature-driven technical presentation. The session draws on applied experience in energy-system modelling, energy planning, climate-policy support, and science-policy engagement. Relevant themes include science-policy boundary work, transparency in modelling, open energy modelling, uncertainty communication, and political economy of energy transitions.