This topic is to collect posters for the Grenoble workshop scheduled for 26–28 March 2024. The grenoble-workshop-2024 tag lists all topics relevant to this event.
Some logistical issues with posters are yet to be resolved and details will advised in due course.
Role
Posters can be used to communicate information about your model, data, research, or a related project.
Posting
Please create a dedicated posting for each proposal by replying to this topic. And add the following template to the top of that posting by simply copy/pasting the markdown, noting that you will need to remove the triple apostrophes that get copied across too.
- genre: poster
- title:
- presenter: @handle
- description:
- optional link to the code repository:
description:
There is a range of energy system optimisation frameworks out there exploiting the power of linear programming. Yet, the analysis of fully sector-integrated energy systems covering a broad range of technologies and large geographical extent while keeping a high temporal and regional resolution is rather rare. REMix, which was originally started in 2006, was recently rewritten with this kind of large-scale (inter)continental energy systems in mind and made open-source in the process. Significant integrated features are, amongst others, parallel solving with PIPS-IPM++, multi-criteria and pathway optimisation as well as modelling to generate alternatives (MGA).
description: MicroGridsPy is a sophisticated and comprehensive analytical model which provides a solution to the problem of sizing and dispatch of energy in microgrids in isolated places at a village scale with a time resolution of 1 hour and time-evolving load demand. The model is based on two-stage stochastic optimization and it enables a detailed techno-economic characterization of renewable energy sources, storage and backup systems resulting in the lowest Net Present Cost (NPC) or lowest Operation and Maintenance expenses (O&M) during the project’s lifespan. Significant integrated features are, amongst others, Capacity Expansion, Mixed-Integer Linear Programming (MILP) formulation, Multi-objective Optimization, Main Grid Connectivity Simulation, Endogenous Renewables Production and Load Curve Time Series Estimation.
Documentation: microgridspy-documentation.rtfd.io
description: We want to introduce the work we are currently doing in the ELYAS project which aims at developing a hydrogen atlas for Europe. Particularily the work done in the development of regionalized location factors for the provision of green hydrogen in Europe.
We will present the methods we used for deriving power and gas grid datasets.
optional link to the code repository: SciGRID (the updated code will be soon made available, still ongoing the internal approval process)
description:
This work identifies and discusses key research gaps in the field of energy system modelling. The main challenge is to make these models more precise, robust, comprehensible. Precision is closely tied to the concept of resolution, which manifests in four dimensions: temporal, spatial, techno-economic detail, and sector coupling. Each dimension can be characterized by low, medium, and high levels of resolution, forming a matrix to map model capabilities. While numerous models excel in one or more dimensions, the overarching challenge lies in achieving high resolution simultaneously across all areas. This endeavor is further complicated by the need for refined temporal resolution, both intra-year (timesteps) and intra-horizon (periods). The precision of the results is also tightly related with the quality of the input data, that need to be reliable and coherent.
Robustness in energy system modeling hinges on effectively managing uncertainty. The field must evolve to enhance the comparison of frameworks, models, and scenario outcomes, thereby integrating uncertainty analysis as a core component. This progression is vital for ensuring that models remain reliable under diverse conditions and can adapt to varying scenarios.
Comprehensibility, particularly in the context of policymaking, is another crucial aspect. The complexity of models must be balanced with their accessibility to policymakers, also through a clear interpretation and communication of the results. This balance is essential to ensure that the insights derived are not only analytically profound but also actionable in real-world policy contexts.
Addressing these gaps is imperative for advancing energy system modeling. Doing so will enhance the ability of models to capture the intricacies of real-world energy systems and inform policy decisions, thereby contributing significantly to sustainable energy development. This pursuit of precision, robustness, and comprehensibility in energy system models is not just an academic endeavor but a practical necessity in navigating the complexities of modern energy landscapes.
description: NRGISE is a modular simulation framework for energy systems. The focus is on the precise simulation of energy storage systems, which act as a central component. However, NRGISE also makes it possible to model components from the fields of e-mobility, PV systems, loads and diesel generators. Thanks to the modular software architecture, the components can be flexibly combined to represent any energy system. A central paradigm in NRGISE is the clear separation between the modeling of the energy system and the implementation of the controller. Here, the basic and established approaches from the field of reinforcement learning and the application of Markov Decision Processes (MDP) were used as a strong orientation. This clear separation between the energy system and the controller, as well as the implementation as an MDP, make it possible to model complex energy systems and controllers as discrete-time decision processes and thus to explore different strategies for controlling energy systems.
description: In the field of energy systems, the energy transition is driving massive changes in system variability and uncertainty. To ensure the system’s adequacy and reliability, these changes need to be accounted for in the models. In particular, this means using higher spatio-temporal resolution, planning on a longer time scale, and considering interactions between energy vectors. However, when translated into energy system models, they give rise to large-scale (potentially non-convex) problems which in practice, are not tractable. The aim of my PhD is to solve this type of long-term, adequate multi-energy system planning problem by developing tractable heuristic optimization methods, based on model coupling. The general idea is to leverage the potential of investment planning models (e.g. OSeMOSYS) by linking them to high-resolution adequacy models (e.g. ANTARES), which can be regarded as a kind of dialogue between these models. The poster will presents a coupling framework and some early results associated to it.
description: POMMES is a framework developed at the centre PERSEE, inherited from the the SPHYDERS framework, to compute optimal pathways for energy systems with integrated operation simulation and investment optimisation (Jodry et al.). Within the PlaneTerr project, this framework is used to model the evolution of multi-energy system in industrial hubs. Results on the the industrial platform of Fos-sur-Mer in France will be presented in this poster with a refined description of the investments to enable the early decommissioning of conversion or storage technologies and the potential re-purposing of technologies (e.g. from SMR to SMR with carbon capture).
description: Numerous European countries have set national carbon targets with the aim of achieving climate neutrality by 2050. However, the strategies that follow these objectives often overlook the actual implications of defossilization, especially concerning carbonaceous vectors. Using the tool Energyscope TD enhanced with a carbon flow quantification. This poster presents the pathway toward a climate-neutral French energy system under the assumption of no import of green energy. The results show a significant increase in energy production compared to the French national strategy and other reference documents.
Hi @Lucie, thank you!
Yes indeed the scigrid webpage is down. It is just an admin matter dealing with paying the bill for the server service
I hope the site will be up before the end of this week and start of next week at the latest
description: Industrial consumption in prospective energy modelling is generally a fixed input point for energy system models. The aim of the IND-OPT model is to use a bottom-up approach to optimise the industrial investment trajectory in a scenario-based economic context in order to derive future industrial energy consumption based on the technological choices made by the model. It is then possible to study the different frameworks favourable to the deployment of certain technologies or the consumption of specific energies.
This poster will present the IND-OPT model, its associated database and the results of a paper currently undergoing peer review. In an earlier version, the model was used for a case study in a conference paper.
description: A study was carried out to quantify the impact of short-term uncertainties in RTE’s 2050 outlook scenarios. Using the ATLAS model, the day-ahead market and three gate closures for the intraday market (the expected evolution of European regulation) were simulated with rolling forecast horizons for renewables and consumption forecasts. The results of the study underline the importance of flexibility assets, especially storage, whose revenu in the energy system is greatly underestimated by common dispatch models such as ANTARES. In particular, it was found that storage units capture a significant part of their value in the intraday markets; however, this signal is not currently communicated to investors and actors in prospective work. Furthermore, the impact of poor coordination between actors with incomplete information (price forecasts, production forecasts, technical constraints) could be estimated with ATLAS and also found to be significant in future flexible energy systems.
Recent times have seen a proliferation of national and regional open-source energy system models, enabled in part by the growing number of freely available modelling frameworks. Yet, there remains a dearth of “out-of-the-box” global-scale planning models. Those tools that do exist have erroneous data pipelines, entail significant technical expertise to use and can be inflexible, in that spatial and temporal scales cannot be easily traversed. As such, barriers to entry are high for non-technical users, while even competent users spend much of their time debugging. Here, we show FEO-Global, a productionised energy planning model with near-global coverage. FEO-Global is portable, scalable and well-maintained, and with cloud computing capability. This means users can rapidly setup and deploy multi-scale planning models, minimising the time spent fixing errors. In addition to explaining to logic behind FEO-Global, we demonstrate its application in a recent case-study exploring the economic benefits of global reinforcement of high-voltage interconnector capacity. Our case-study shows a $USD 3 trillion saving in transition costs if interconnectors are bolstered, relative to a case where no further transmission is built-out.
description: Poland is currently in the process of updating its National Energy and Climate Plan and shaping its official energy policy until 2040. To inform the ongoing public debate regarding the feasible energy transition pace and the achievable emission reduction targets, we (Instrat Foundation) expanded our in-house power system model by incorporating heating, mobility, and hydrogen sectors. In my poster presentation, I will provide an overview of the methodology employed in our model, discuss the scenarios we have developed, and highlight the influence our results had on the public debate in Poland.
description: The tool presented here was created for teaching. It allows to solve a single horizon multi-energy investment problem with hourly energy balance constraints. It has a case for Europe with 7 nodes that allows to do prospective analysis for 2030 and 2050. It is not as complete as PyPSA but more focused, the interest for teaching is that all equations are written explicitly with Linopy and that new equations can easily be added. This last feature can also be interesting for research. A simple interface is made available to modify the main economic assumptions.
description: The Agent-based Market model for the Investigation of Renewable and Integrated energy Systems AMIRIS was significantly enhanced in the last year. We present the most important new features, e.g., a market coupling algorithm, two additional storage operation strategies, a new financial Contract for Difference support scheme, as well as electrolysis units and associated dispatch strategies.
• genre: poster
• presenter: @anaelle.jodry
• title: Simulating wind power generation in France from observational data, meteorological data and technical turbine information.
• Description: As the world embraces sustainable energy, predicting future wind power generation is crucial for shaping effective policies, optimizing grid integration, and planning infrastructure development. In France, where wind power is a key contributor, accurate simulations are vital for a sustainable and efficient energy transition. In this work, we propose a methodology to build a model capable of simulating wind power generation using turbine technical information and meteorological data. First, we compare the different databases used (The Wind Power, ORE agency, and the French TSO RTE) and establish a more comprehensive unique database. Then, using ERA5 reanalysis and the past 10 years observed generation data, we construct the statistical model. Finally, this model is employed to simulate wind power generation.
• bibliography: Y.-M. Saint-Drenan et al., “A parametric model for wind turbine power curves incorporating environmental conditions”, vol. 157, pp. 754–768, 2020, Redirecting.
González-Aparicio et al., “Simulating European wind power generation applying statistical downscaling to reanalysis data,” Appl. Energy, vol. 199, pp. 155–168, Aug. 2017, Redirecting.
J. P. Murcia et al., “Validation of European-scale simulated wind speed and wind generation time series,” Appl. Energy, vol. 305, p. 117794, Jan. 2022, Redirecting.
Description:
Hypatia is an energy system modeling framework built in Python, aiming to address the complex challenges associated with optimizing operational and long-term planning aspects of energy systems. This framework provides an advanced tool for decision-makers and researchers to explore different policy-driven scenarios for energy transitions, utilizing multi-objective optimization or near-optimal solutions to explore the entire spectrum of solutions based on optimizing net present cost or emissions. With its open-source nature, Hypatia offers a customizable solution for analyzing diverse energy transition possibilities, making it highly valuable for those interested in analyzing and shaping the future of energy systems. Hypatia leverages the versatility of the Python programming language, making it accessible and adaptable for users across different domains. The framework covers short-term and long-term time horizons, allowing users to gain insights into the dynamic behavior of energy systems over various planning horizons.
title: Geographical approach of congestions on the sub-transmission grid in France
presenter: @louise.petit1
description: Treating and analyzing geographical open data combined with grid data gives additional perspectives. With the objective of enhancing national or international power flow grid models, an explicit modeling of chosen local sub-transmission grids would give a better view on sub-transmission’ impact on Extra High Voltage (EHV) power flows.
To choose the sub-transmission grid parts to be modelled explicitly, a study of correlations between congestion data and geographical open data is performed. Indicators that are the most correlated with congestions can be used to spot where to apply an explicit modeling of sub-transmission.
The geographical correlation study, developped in the context of my PhD thesis, will be described in this poster.
