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 March 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.
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 contributions added below
Proposed contributions (please add your talk below 
following the same template/style as the ones already posted)
title : Coupling energy system models with life-cycle assessment - a case study on Québec energy system
presenter : Matthieu Souttre (CIRAIG, Polytechnique Montréal)
description : Energy System Models (ESMs) optimize transition trajectories but typically overlook environmental trade-offs beyond CO₂ — such as resource use, toxicity, or ecosystem impacts. This presentation introduces mescal, a model-agnostic open-source Python package that bridges ESMs with Life-Cycle Assessment (LCA) to embed these broader sustainability metrics directly into energy planning. As a case study, we present its application to the Québec energy system using EnergyScope, illustrating how prospective and regionalized LCA metrics can reshape transition pathways.
code repository : mescal (GitHub - matthieu-str/mescal: Coupling Energy System Models with Life Cycle Assessment · GitHub), EnergyScope (EnergyScope / EnergyScope · GitLab)
documentation : mescal (In a nutshell — mescal), EnergyScope (EnergyScope - Energyscope)
license : mescal - MIT, EnergyScope - Apache 2.0
literature :
title : Advancing Renewable Integration through Demand Flexibility and Sector Coupling: a Systematic approach to unlock renewable energy’s full potential
presenter : Alebachew Mossie
description : Large-scale Renewable Energy (RE) integration faces significant challenges, particularly variability, intermittency, and grid stability issues which limit its full deployment. This presentation introduces a systematic approach to enhancing RE integration by leveraging demand flexibility through sector coupling. The concept focuses on linking electricity with flexible demand sectors, such as electric mobility and green hydrogen production, to better balance supply and demand, aiming to reduce RE curtailment, improve system efficiency, and enhance resilience. The work is based on an ongoing research proposal and outlines the proposed modelling framework, key research questions, and expected contributions to clean energy transitions, particularly in emerging energy systems.
code repository : work in progress
literature : flexible energy demands, Energy modeling tools, renewable energy
title: Beyond the numbers: Examining economic modeling tools for climate change policy analysis
presenter: Madanmohan Ghosh
description: Over the past few decades, several economic models have emerged to assess the impact of policies addressing climate change. These models fall into five main categories: the integrated energy system model (IESM), the computable general equilibrium (CGE) model, the macroeconomic model (MEM), the agent-based model (ABM), and the integrated assessment model (IAM). This presentation provides an overview of these models, discusses key insights, and explores how they complement each other in climate policy assessments.
code repository:
literature: Energy-emissions-economy modeling, climate change
title: Energy system implications of decarbonized truck electricity demand profiles
presenter: Lih Wei Yeow
description: The transition to low-GHG emission trucking and wider energy system decarbonization will reshape temporal energy demand and interact with variable wind and solar PV generation. Yet, comparisons between these truck decarbonization technologies seldom incorporate cross-sectoral interactions with the broader energy system at high temporal (e.g. hourly) resolution. Using year-long GPS data of 8000+ trucks in Ontario, Canada, and the Temoa open-source energy system model, we investigate how high-resolution, hourly energy demand profiles and cross-sectoral interactions influence cost-optimal technology deployment in a decarbonized energy system.
code repository: work in progress
literature: temporal demand profiles, heavy-duty trucks
title: Rethinking European Energy Planning: What Open-Source Models Reveal About Network Development and Flexibility Needs
presenter: Luciana Marques (Open Energy Transition)
description: Open-source energy models are moving from research into real planning contexts, challenging the dominance of established commercial tools. In Europe, where transparency and traceability are becoming central to energy decision-making, this shift raises a key question: can open models deliver results robust enough for network development planning and flexibility needs assessment—and be trusted by stakeholders such as TSOs and regulators? Focusing on applications with PyPSA, this talk highlights how open-source approaches enable fully transparent and reproducible planning workflows. Drawing on validation against real-world open data, such as the Pan-European Market Modelling Database, it explores both the progress achieved and the remaining gaps, providing a concrete perspective on the role of open models in future European planning practice.
code repository: OpenTYNDP, FlexStudy
documentation: OpenTYNDP
license: MIT
literature: Network Development Plan (NDP), Flexibility Needs Assessment (FNA)
title: Open Grid Data Matters: PyPSA Lessons from Colombia Using MapYourGrid data.
presenter: David Díaz (Open Energy Transition)
description: Open grid data quality can strongly affect energy system planning results. This lightning talk presents a PyPSA-based Colombia case studyusing transmission data improved through the MapYourGrid project.The study compares capacity expansion outcomes across three versions of the grid dataset (OSM 2020, OSM 2024, and latest OSM) under 2030 and 2050 scenarios with changing assumptions. The talk highlights the planning pitfalls that arise when grid data is incomplete, including distorted bottlenecks, misleading investment signals, and different expansion pathways.The session will also briefly show how the model was validated against external reference data and reflect on why collaborative open mapping should be treated as a core input to credible open-source power system modelling.
code repository: GitHub - pypsa-meets-earth/pypsa-earth-osm: PyPSA-Earth-OSM: Exploring Synergies between OSM data and energy planning · GitHub
documentation: Colombia Grid Impact Study
license: MIT
title: Uncertainty Management in Capacity Expansion and Resource Adequacy Studies
presenter: Dheepak Krishnamurthy (EPRI Canada)
description: Resource planners often need a model that is simpler and faster than a full production-cost or market simulation, but still rich enough to test capacity expansion decisions against resource adequacy outcomes. The talk focuses on a sandbox model for capacity expansion planning and resource adequacy studies, where this kind of model is most useful: rapid scenario screening, stress-testing planning assumptions, and connecting long-term portfolio choices to reliability outcomes.
code repository:
literature: Stochastic modelling, uncertainty management, energy modeling tools
title : Enabling multi- and many-objective energy system optimization with Osier.
presenter : Samuel Dotson (University of Illinois)
description : Conventional energy system optimization models (ESOMs) optimize a single objective function that typically represents an aggregated cost metric. However, stakeholders have and express preferences over many dimensions simultaneously and decisions are rarely made on the basis of cost alone. Osier fills this gap by offering three critical advancements.
- Osier can optimize an arbitrary number of user-defined objectives.
- An n-dimensional extension for modeling-to-generate-alternatives.
- Two dispatch algorithm formulations (logic-based and linear program).
Together, these advancements allow users of Osier to address structural and the lesser known, normative uncertainties present in all modeling exercises. These features are demonstrated on an example system and discussed.
code repository : Osier (github - arfc/osier: Justice oriented energy system optimization framework)
documentation : Osier (osier — osier 0.4.1 documentation)
license : BSD-3
literature :
- Dotson, Samuel G., and Madicken Munk. 2024. “Osier: A Python Package for Multi-Objective Energy System Optimization.” Journal of Open Source Software 9 (104): 6919. https://doi.org/10.21105/joss.06919.
- Dotson, Samuel Gant, Madicken Munk, and Kathryn Dorsey Huff. 2026. “Demonstrating the Osier Framework for Energy System and Nuclear Fuel Cycle Optimization.” Annals of Nuclear Energy 230 (June): 112151. https://doi.org/10.1016/j.anucene.2026.112151.
title : Simple models, real change: Using a PyPSA analysis to drive policy in Illinois.
presenter : Samuel Dotson (Union of Concerned Scientists)
description : Commonly, policy makers will propose specific targets for energy investment and subsequently direct relevant agencies to study the impacts of this proposed policy. This backwards approach leads to slower and less precise policy development. Instead, we find that energy system models should drive policy recommendations. This talk covers a case study in Illinois where a state-level energy system analysis by the Union of Concerned Scientists motivated specific policy guidance that was eventually adopted under the 2025 Clean and Reliable Grid Affordability Act (CRGA).
code repository : pypsa-illinois (github ucsusa/pypsa-illinois: A model of the Illinois electricity system built with PyPSA.)
license : BSD-3
literature :
- Dotson, Samuel, Lee Shaver, and James Gignac. 2024. Storing the Future: A Modeling Analysis of Illinois Energy Storage Needs. Cambridge, MA: Union of Concerned Scientists. https://doi.org/10.7910/DVN/7QRME4
title : PyPSA-Canada framework and national model (Lightning Talk and Technical Demonstration)
presenter : Nathan de Matos, Michel Bui, Adrien Prigent (Natural Resources Canada, CanmetENERGY)
description : The lightning talk will introduce the soon-to-be-released PyPSA-Canada framework and national electricity model. This is a model of Canada’s interconnected electricity system, representing major generation and supply centres and the transmission corridors connecting them. Together, the model and framework allow exploring strategies to decarbonize Canada’s electricity system, such as expanding renewables, strengthening interprovincial transmission, or electrifying transportation and heating. They also support identifying the most cost-effective pathways to meet future electricity demand given environmental, technical and policy constraints. The technical demonstration will offer a guided walkthrough of the model’s features and scenario example showcasing how the tool can be used for analysis and decision-support.
code repository : NRCan github (repo not yet available)
documentation: Available in future repo
license : MIT
title : Assessing the Spatiotemporal Generalizability of Power Outage Prediction Models using GeoAI Foundation Models
presenter : Yamil Essus
description : Machine-learning based power outage prediction models are increasingly proposed as decision-support tools for disaster preparedness and response, yet their ability to generalize across regions and events remains poorly understood. We evaluate the spatiotemporal generalizability of power outage prediction models using publicly available data for the U.S. East Coast. Specifically, we assess model performance under multiple test selection strategies, including unfiltered random splits, leave-one-state-out, and leave-one-event-out designs, which increasingly approximate real-world deployment conditions. We conduct a series of experiments to test common assumptions in power outage prediction. We focus on three methodological decisions that we find have a large impact on generalizability of power outage prediction models. First, the strategy to select an out-of-sample test set from the available data, specifically regarding potential data leakage due to spatial and temporal correlation in covariates. Second, the selection of target variable, which is often an absolute measure of outage magnitude and is inherently linked to population size. Lastly, the use of static features that could potentially lead to the model not being applicable to new areas due to overfitting or memorization of location specific patterns. We also present evidence that inconsistency of chosen performance metrics, study areas and time periods makes it difficult to assess the performance of literature models as a whole, and the heavy use of proprietary and region specific data significantly hurts the reproducibility and generalizability of the results. Additionally, in order to address the high dimensionality of weather features, we applied transfer learning to build a machine learning model based on a recent Geospatial Artificial Intelligence (GeoAI) foundation model (Prithvi WxC) specifically built for generalizability of weather features.
code repository : TBD (geospatial processing + ML pipeline)
literature : Power Outage Prediction with ML, GeoAI, Generalizability of ML models
- Kapoor S, Narayanan A, Leakage and the reproducibility crisis in machine-learning-based science, Patterns, 2023; 4
title: Analyzing Industrial Decarbonization Pathways in Canada using Canadian Open Energy Model (CANOE)
presenter: Manish Mosalpuri (Postdoc, University of Calgary)
contributors: Sylvia Sleep and David Turnbull (University of Calgary)
description: Canada has committed to achieving net-zero greenhouse gas emissions by 2050- an ambitious goal that demands clear, data-driven decisions. The industrial sector accounts for more than half of Canada’s end-use energy demand, and fossil fuels dominate its energy use, with natural gas accounting for 49% of total consumption. This study models decarbonization strategies for the industrial sector in the Canadian Open Energy Model (CANOE). Built on the Tools for Energy Model Optimization and Analysis (TEMOA) framework, CANOE examines how various technological and policy choices could shape Canada’s energy future and support the transition to net-zero emissions. Our focus is on analyzing the intersectoral interactions and implications of these decarbonization strategies, and on estimating their costs and emissions-reduction potential.
code repository: work in progress
literature: industrial decarbonization, electrification.
title: Impacts of various energy efficiency options on the power system in Québec
presenter: Florian Mitjana (Professional researcher, HEC Montréal)
description: Decarbonization and electrification will increase the demand for electricity. This will put a lot of pressure on the power system, with significant cost impacts. Energy efficiency can alleviate these impacts. There are however many different energy efficiency options, such as reducing heating energy intensity through retrofits, installing heat pumps, or structurally reducing the growth of residential space. In the transportation sector, promoting electric cars instead of SUVs can also save energy. We assess the power system benefits of 12 (?) energy efficiency options through a load profile generator coupled with a capacity expansion and dispatch model (PITHOS). Results show cost reductions up to 55% when an ambitious energy efficiency policy is adopted. However, not all energy efficiency options contribute equally: the reduction of space heating intensity, the deployment of ground-source heat pump and the reduction of the vehicle fleet are the most impactful levers. Our analysis contributes to prioritizing the best energy efficiency options from the perspective of the power system.
code repository: work in progress
literature: decarbonization, electrification.
title : Cross-Border Renewable Integration: The Role of Québec Hydropower in the Decarbonization of New York City
presenter : Soroosh Sabaei (HEC Montréal)
description : Large-scale wind integration is expanding rapidly as power systems pursue decarbonization, but its variability and intermittency create major challenges for balancing supply and demand across hours and days. One common approach is to rely on local flexibility, especially utility-scale battery storage, although the cost and scale of very large battery systems remain important concerns. Another possibility is to collaborate with hydro-dominated neighboring regions whose reservoirs can provide temporal flexibility to support systems with high wind penetration. Considering New York City’s decarbonization plan, together with the CHPE transmission line currently under construction between NYC and Québec, this work investigates how cross-border coordination with Québec could support deeper decarbonization of NYC’s electricity supply. The presentation is based on an ongoing research project using a multistage stochastic operational model with detailed hydropower representation and compares a self-reliant pathway based on additional offshore wind and battery storage with a regional collaboration pathway based on expanded transmission access to Québec’s reservoir hydropower and additional wind resources.
code repository : work in progress
literature : hydro-wind integration, stochastic energy modeling, cross-border collaboration, decarbonization
title: Integrated assessment of the nexus among energy transitions, climate impacts, and adaptation responses with AD-MERGE 2.0
presenter: Kamyar Amirmoeini (GERAD/HEC Montreal)
description: AD-MERGE 2.0 is an integrated assessment model developed to examine the interactions among energy system transitions, climate damages, mitigation, and adaptation across global regions. This presentation will provide a brief overview of the model framework and illustrate how integrated assessment modeling can be used to study long-term climate and energy policy challenges, including regional differences in climate impacts, response capacities, and policy outcomes. The talk aims to highlight the value of linking energy, economy, and climate dimensions within a single analytical framework to support a more comprehensive assessment of climate strategies.
code repository : GitHub AD-MERGE 2.0 Integrated Assessment model
license : GPL-3.0 license
Literature :
- Amirmoeini, K., Bahn, O., de Bruin, K., Everett, K., Kouchaki-Penchah, H., & Pineau, P. O. (2026). AD-MERGE 2.0: An integrated assessment of the nexus among energy transitions, climate impacts, and adaptation responses. EGUsphere, 2026, 1-40.
- Bahn, O., Bruin, K. D., & Fertel, C. (2019). Will adaptation delay the transition to clean energy systems? An analysis with AD-MERGE. The Energy Journal, 40(4), 207-234.
title: Assessing Electrofuels Supply Potential in the United States using PyPSA-Earth
presenter: Daniele Lerede (Open Energy Transition)
description: Electrofuels could play an important role in decarbonizing hard-to-electrify sectors, but large-scale production will significantly interact with power systems. This lightning talk presents a modelling approach that combines renewable resource availability with power system expansion modelling to assess the impact of the uptake of e-kerosene as aviation fuel on the US electricity system under several policy scenarios. The talk highlights how grid constraints, renewable potential, and competing electricity demand shape the feasible supply of electrofuels and what this means for future energy planning.
license: AGPL-3.0 license
documentation: To be published
code repository: GitHub - open-energy-transition/efuels-supply-potentials · GitHub
literature:
- Riepin, I., Brown, T., System-level impacts of 24/7 carbon-free electricity procurement in Europe, System-level impacts of 24/7 carbon-free electricity procurement in Europe .
- Abdel-Khalek H., Schumm L., Jalbout E., Parzen M., Schauß C., Fioriti D., PyPSA-Earth sector-coupled: A global open-source multi-energy system model showcased for hydrogen applications in countries of the Global South, Redirecting , Applied Energy, 2025, vol. 383, 125316
- Pavlenko, N., 45V Hydrogen Guidance Quick Reactions, 45V Hydrogen Guidance Quick Reactions .
title: Hydrogen Pathways for Metropolitan Energy Transition: An Energy System Optimization Framework Applied to the Montréal Metropolitan Community
presenter: Sara Ghaboulian Zare (GERAD / Université de Montréal)
description: ETEM-H₂-CMM is an extended version of the open-source Energy Technology Environment Model (ETEM), a bottom-up energy system optimization model belonging to the MARKAL–TIMES family, developed to assess hydrogen deployment pathways within metropolitan energy systems. I will provide a brief overview of the modeling framework and illustrate how energy system optimization can be used to evaluate hydrogen integration under multi-level climate governance, including interactions between production, storage, distribution, and end-use technologies across sectors. The presentation highlights the role of hydrogen as a complementary decarbonization option in highly electrified metropolitan regions, with the Montréal Metropolitan Community as a case study, and demonstrates the transferability of the framework to other C40 cities facing similar long-term energy transition challenges.
code repository: Work in progress
literature:
- Ghaboulian Zare, S., Babonneau, F., Bahn, O., Haurie, A., Mousseau, N., Neshat, N., & Trépanier, M. (2025). A review of hydrogen supply chains in energy system optimization models. Energy, 315, 115544. Redirecting
- Aliakbari Sani, S., Maroufmashat, A., Babonneau, F., Bahn, O., Delage, E., Haurie, A., Mousseau, N., & Vaillancourt, K. (2022). Energy transition pathways for deep decarbonization of the Greater Montreal region: An energy optimization framework. Energies, 15(10), 3760. https://doi.org/10.3390/en15103760
title: Diagnostic Modelling: A Framework of Principles for Responsible Energy Systems Modelling
presenter: Davey Elder (University of Toronto)
contributors: Juan Moreno-Cruz, Cameron Wade, Sylvia Sleep, Sara Hastings-Simon, Heather MacLean, I. Daniel Posen
description: We present a framework of principles for the responsible usage of energy systems optimisation models (ESOMs). ESOMs suffer from an immense degree of complexity and uncertainty. We briefly explore the types of uncertainties ESOMs face and how this impacts their ability to inform policy decisions, and make the argument that tackling some of these uncertainties requires a different approach from traditional uncertainty methods. Building on past work on best practices, we present three simple principles to guide justifiable and actionable energy modelling studies.
title: Assessing the System Value of Emerging Technologies in A Multi-Sector Energy Model
presenter: Davey Elder (University of Toronto)
contributors: Juan Moreno-Cruz, Cameron Wade, Heather MacLean, Daniel Posen
description: In this work, we demonstrate the power of System Value Assessment (SVA) for assessing emerging energy technologies. Rapid decarbonisation requires decisive policy action, which is impeded by risk and uncertainty. A major source of uncertainty in the coming energy transition is the role of emerging technologies like batteries, hydrogen, and direct air carbon capture and storage (DACCS). These technologies feature heavily in plans to reach net zero emissions but there remains deep uncertainty in the projections of their at-scale cost and performance parameters, which are the basis of energy system modelling. This uncertainty is exacerbated by the opacity of large energy systems models, where the interpretation of results can be difficult and often subjective.
Using the Canadian Open Energy model (CANOE), we present an applied example with electrolytic hydrogen production to demonstrate the use of SVA. Rather than attempting to optimize around highly uncertain projections for future technology cost and performance, SVA focuses on the breakeven value the technology may provide to the energy system across the space of its uncertain parameters – identifying thresholds of price and performance and optimal deployment strategies to achieve and maximise economic viability. We break down the source of system value as a diagnostic tool to investigate model behaviour, uncovering generalizable insights into the cross-sectoral systemic effects of technology adoption.
title: Modeling Multisectoral Interactions in the Temoa Canadian Open Energy Model
presenter: Daniel Posen (University of Toronto)
contributors: Davey Elder, Sylvia Sleep, Sean McCoy, Juan Moreno-Cruz, Heather L. MacLean, Sara Hastings-Simon, Andrew Leach, Cameron Wade
description: Energy system models provide a critical foundation for assessing technology pathways for a low-carbon future. Despite substantial progress in advancing sector-coupling in previously electricity-focused models, many continue to struggle at capturing the sector-specific constraints and multisectoral interactions – particularly in relation to the physical realities such as fuel supply chains, critical mineral and bulk material flows or infrastructure requirements of the energy transition. This talk will present an overview of ongoing activities to construct and advance a novel energy system optimization model for Canada – the Canadian Open Energy Model (CANOE). Built on the Temoa linear-programming framework, CANOE is a multi-sector capacity expansion model. It is being constructed in a highly modular format that allows for flexible choice in technological, spatiotemporal and sectoral resolution.
The development team is a multi-university consortium with primary background in the tools of industrial ecology (life-cycle assessment, techno-economic assessment, material flow analysis and energy transitions) – enabling us to bring an uncommon perspective to the world of energy modeling. We have developed capabilities to track physical materials (e.g., critical minerals for battery cathodes and electrolyzers) through the energy system; assess the role of embodied carbon in the energy transition; analyze constraints imposed by the available fuel mix from petroleum refineries; incorporate empirical growth-rate constraints on new technologies; and embed results from detailed sectoral models such as transport sector traffic flows and infrastructure needs.
code repository: https://github.com/CANOE-main
documentation: https://canoe-main.github.io/CANOE/
license: GPL-3.0 (transitioning to MIT)
title: Mapping Energy Modelling Tools: openmod-tracker & Feature Inventory
presenter: David Diaz (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.
web app: https://openmod-features-prototype.streamlit.app/Deep_Dive_-_Tool_Feature_list
code repository: GitHub - open-energy-transition/openmod-features: Open Energy Modelling Tool Feature Inventory · GitHub
documentation:https://docs.google.com/document/d/1B_zWdniTYnGa10smAcLjtelu83JRjER1E0c6l9VGGYA/edit?tab=t.0
title: Unlocking FERC EQR
presenter: Ella Belfer (Catalyst Cooperative)
description: Efforts to design cost-effective decarbonization pathways are hindered by limited visibility into the financial flows and market structures that shape the electricity sector. FERC Electric Quarterly Reports (EQR) offers an enormous amount of data describing transaction-level data on prices, quantities, and contractual terms between power producers, utilities and financial intermediaries. Yet the dataset has remained largely underutilized due to accessibility and quality barriers. This talk will introduce the Public Utility Data Liberation’s efforts to make FERC EQR data accessible to the energy research community, demonstrating potential applications through an exploration of cross-border electricity sales to Canadian utilities.
code repository: PUDL
documentation:
license: MIT
title: Bridging the gap between long-term planning and grid physics: coupling capacity expansion model with PowSyBl Metrix,an open-source security-constrained optimal power flow solution.
presenter: Tengxiang Ren (Artelys)
description: To ensure computational tractability while maintaining robust results, long-term planning models often rely on aggregation methods, using a zonal representation of the energy system. However, this level of granularity may prove insufficient when moving from a long-term perspective to project-level investment decisions, particularly for transmission reinforcements.
The presented methodology couples a zonal planning model with a nodal security constrained optimal power flow solution, PowSyBl Metrix. A typical use case in Europe relies on ENTSO-E ‘s zonal model, TYNPD and an European nodal model, PyPSA-Eur.
This coupling allows to (1) verify that network security and reliability are respected along a given development trajectory, and (2) improve decision support by refining cost–benefit assessments of individual projects.
code repository: https://github.com/powsybl/powsybl-metrix
documentation:https://powsybl.readthedocs.io/projects/powsybl-metrix/en/stable/
license: MPL-2.0 license
title: Geospatial Optimization of Power-to-X Fuels and CCUS Supply Chains for Canadian Net-Zero Pathways
presenter: Andrew Vigars (University of Toronto - Canadian Open Energy Model)
contributors: Thiago A. Rodrigues, Ali Abdelshafy, I. David Elder, David Turnbull, Joule Bergerson, Sylvia Sleep, I. Daniel Posen
description: Canada’s Carbon Management Strategy calls for the large-scale deployment of carbon capture, utilization, and storage (CCUS) infrastructure to meet net-zero CO2 emission commitments by 2050. This includes the deployment of power-to-X fuel systems to serve hard-to-electrify sectors such as cement, aviation, and high-temperature industrial heating. Currently, most large-scale energy system optimization models operate at limited spatial resolution. This limits their ability to represent the supporting infrastructure constraints and supply chain clustering necessary for evaluating the costs associated of specific chain configurations. This study introduces a geospatial extension of the Temoa-based Canadian Open Energy Model (CANOE) for the least-cost optimization of CCUS and Power-to-X supply chains across a spatial network at different resolutions. Work to date has focused on a proof-of-concept framework for using Temoa to optimize geospatial networks (e.g., pipelines). In future work, this project aims to include existing modes of transportation infrastructure including road, rail, marine, and the potential for refurbished natural gas pipeline networks for the transportation of intermediate and end-use fuels such as green hydrogen, e-methanol, e-gasoline, e-diesel, and e-sustainable aviation fuel (e-SAF). The geospatial framework will also explore the modelling of constraints on infrastructure deployments such as terrain, land use restrictions, wind and solar variability, and economies of scale associated with the manufacturing of electricity and CO2-based Power-to-X fuels.
code repository: GitHub - ThiagoRodrigues/temoa_geospace · GitHub
documentation: CANOE Documentation ; Temoa Project Documentation — Tools for Energy Model Optimization and Analysis (Temoa) 4.0.0a1.dev20251201 documentation
Register here: 
Event Registration 
Lightning Talks: present a project, workflow, or tool development in a concise format
Technical demonstrations: live code walkthroughs and implementation case studies
Breakout Sessions: collaborate with experts in interactive sessions on diverse energy topics
Networking: engage with practitioners, developers, regulators, and system operators
If you are interested in contributing, please indicate your preferred format and topic in the staging area. The organising team will curate the final programme.
We look forward to welcoming the Canadian and international open energy modelling community in Montréal 