Replacing transmission conductors, or transmission lines – known in the industry as reconductoring - is France’s apt electrical transmission line expansion solution that has already shown its proof of concept in several other countries. On average, France loses 8.5% of its electricity production from resistive, capacitive, and inductive line losses, usually in the form of heat.
Our lightning talk investigates the economic advantages of reconductoring the French transmission and distribution lines. We also explain the actionable steps to achieve these goals and how much can be saved as a result.
We present TransitionZero’s Future Energy Outlook: an open-access ecosystem of data services, systems modelling frameworks, and programmatic and graphical user interfaces. The expert modeller can access well-maintained data and scale run ensembles with our API and Python client. The non-technical analyst can access modelled results from the user community or dispatch their own via our web-based UI. This talk will present our progress and our roadmap, as well as the decisions and trade-offs we’ve made to productise systems modelling for non-technical users.
description: We present scengen – a scenario generator for the electricity market model AMIRIS – which enables light-weight multi-scenario analysis. In this overview, we outline the comprehensive features available for scenario creation, the easy execution of AMIRIS, and a basic yet insightful analysis of results. Furthermore, we show practical applications, illustrating how these new features can be effectively utilized.
optional link to the code repository: AMIRIS and scengen
description: We enhanced FAME-Io to support metadata fields for any FAME-based model class and inputs. These can be easily associated with, e.g., Open Energy Ontology entries or any other type of metadata. This simplifies creating and maintaining automated (inter-) model workflows, such as automated model couplings or automated result documentation. We provide a quick glimpse on how these new features can be put to use.
description: Deeply decarbonized power systems often rely on large shares of variable renewable energy and electrification of end-use consumption, such as heating, which make them highly dependent on weather variability and climate change. Weather exhibits fluctuations on temporal scales ranging from sub-hourly to yearly while climate variations occur on decadal scales. To investigate the intricate interplay between weather patterns, climate variations, and power systems, here we present a framework to generate time series of wind power generation, solar power generation, hydropower generation, heating demand, and cooling demand. The framework can generate time series at high temporal resolution for any country and for any period between 1940 and 2100. Our framework serves as a tool for understanding and addressing the challenges posed by the evolving energy landscape in the face of climate change.
description: The ATLAS model simulates the various stages of the electricity market chain in Europe, including the formulation of offers by different market actors, the coupling of European markets, strategic optimization of production portfolios and, finally, real-time system balancing processes. ATLAS was designed to simulate the various electricity markets and processes that occur from the day ahead timeframe to real-time with a high level of detail. Its main aim is to capture impacts from imperfect actor coordination, evolving forecast errors and a high-level of technical constraints—both regarding different production units and the different market constraints.
Unlike electricity production, which is centralised and mutualised throughout the territory, heating production is mainly decentralised and is specific to every dwelling.
The non-dilution question appears at two different levels: at the centralized-versus-individual level and between the individual heating solutions. First, dwellings connected to district heating networks are very unlikely to rely as well on individual heating devices. Secondly, we can ask ourselves if a dwelling investing in a particular individual heating solution (such as a gas boiler) is likely to add another heating equipment.
Taking into account, or not, this particularity will influence the MILP formulation (by adding non-dilution constraints) and therefore possibly influence the global results of the optimisation.
This lightning talk assesses the potential impact of non-dilution (on a simplified electricity-and-heat optimisation model) and addresses the following questions:
Does the non-dilution affect the optimisation results? To what extent?
Should the non-dilution be taken into account? In which context?
description: Drawing from our PhD research, we will present the methods, challenges and insights of coupling open-source energy planning tools with open-source stock-flow consistent macroeconomic models. We designed such a coupling (between EnergyScope and GEMMES) for studying the intertwined energy and economic dynamics of the low-carbon transition in the case of Colombia. Among others, we study how the energy system’s planning gets modified when modelled in a fluctuating macroeconomic environment.
description: Hubs.jl is a library built on top of JuMP.jl and is designed to optimize industrial symbiosis, encompassing both energy and mass flows. Unlike conventional approaches, it broadens the hub concept beyond energy to include industrial hubs, offering insights into resource utilization within complex industrial systems. Hubs.jl promotes synergies and circularity inside the hubs and between them through network connections, which minimize waste and maximize resource utilization. Hubs.jl is versatile and doesn’t require prior knowledge of the system’s architecture, making it an ideal tool for early-stage analysis of industrial and energy systems.
optional link to the code repository: will be available later
description : Several datasets pertaining to building energy consumption are made available by french public entities such as building simplified geometries, dwelling-level census, energy performance diagnosis, gas network routes and district-level energy consumption. By combining datasets at the building level, simplified energy models can be instantiated and simulated for various scenarii of occupant behavior and parameter uncertainties. District-level simulation results can then be compared to metered district-level energy consumption in order to select the most likely scenario. In this talk, we will present an overview of the methodology used, the most common pitfalls to avoid when leveraging these datasets, as well as an application to a local test case.
description: For the Energy Transition to be timely and feasible, functioning electricity markets are imperative. Yet, existing modeling approaches could be insufficient to appropriately assess future electricity market design. In this context, Reinforcement Learning appears as an alternative to further improve the existing modeling framework, by allowing policymakers to assess more intricate elements in the agent’s decision-making process. This presentation will explore some of the challenges, obstacles and opportunities for Multi-Agent Reinforcement Learning approaches with the Ray Libraries.
description: Traditionally, open research projects focus on delivering publishable findings, with software outputs taking a secondary role. Yet, robust and reusable software is crucial for replicating results, accelerating scientific progress, and fostering collaboration. This calls for a shift in mindset, moving beyond one-off coding efforts to embedding quality-driven processes throughout the research lifecycle.
What is the benefit of taking this approach?
How can we deliver open research projects by investing in sustainable quality practices?
optional link to the code repository: To be provided later
description:
Reproducibility of modelling results is a key criterion for clean scientific work and achieving this through open data, methods and models is one of the key aspirations of the openmod community. Within the SEDOS project we have further optimised our open data management and use our tools Open Energy Platform (OEP), Open Energy Ontology (OEO), DBpedia Databus together with oeomof.tabular and oemof.solph to create and optimise a sector-integrated energy system model. In this Lightning Talk I will give an insight into the status-quo of these developments within the SEDOS project.
description: Many energy system sizing tools are based on Mathematical Programming (MP) formulations that implicitly assume perfect foresight for the underlying system operation (also called energy management or unit commitment and energy dispatch). In contrast, sizing tools that rely on a system simulator embedding simple rule-based operation strategies are admittedly suboptimal, but are non-anticipative by default. Using the open-source simulator-based sizing tool Microgrids.jl and a MP-based variant, we study the risk of obtaining an ill-sized microgrid (i.e. one that cannot meet a prescribed Quality of Service level) when assuming perfect foresight.
description: CEA has developed a tool for studying optimal possible energy architectures involving RES, new technologies in the frame of decarbonization studies at several scales. PERSEE provides a graphical interface with smart connector functionalities that allows the user to model the system by assembling MILP model contributions from a model library in order to build a time-dependant optimization problem. The resulting problem is solved by one of the solvers available to PERSEE through a multi-MILP-solver interface that also allows the modeler to add or refine their desired constraints or contributions to the objective function. We are thinking about deploying the software under an open source license.
description: ehubX is an energy system modelling tool developed in the Urban Energy System Lab in Empa, Switzerland, with a platform-based design concept that has the flexibility to integrate with other modules and tools. This tool is used in various projects in Switzerland at different scales, from individual buildings to regional levels. The tool is planned to be open-source this summer.
NOTE: apologise for the late posting; I will remove it if it is too late.
description:
With the recent growth trend in open science, many open data lifecycles have been proposed. However, many of these lifecycles are not well adapted to energy datasets. In this talk, I’ll present some of the most popular lifecycles and highlight some of the peculiarities of datasets in the energy domain. In addition, I’ll present an open energy data life cycle that takes into consideration the management of the data, its re-use by external parties, and most importantly the importance of feedback loops in increasing the valorisation of datasets.
Description : The PAC 2.0 project is an ambitious project aiming at exploring the implications of a PAC (Paris accord compatible) scenario with 100% renewable energy sources (RES) by 2040 at the EU(+TYNDP) level. It involves a large increase of interconnection between countries and a strict policy against the expansion of fossil fuel capacity, with coal slated for phase-out by 2030 and gas/oil by 2035. Additionally, it relies on an ambitious energy demand reduction scenario, supported by a comprehensive energy demand modeling tool called the Pathways Explorer, for improved sector coupling.
description: Sector coupling has been introduced as an increasingly important goal in order to achieve decarbonisation via electrification and provision of flexibility. This talk will discuss which sectors (and vectors) we should focus on in our modelling efforts going forward to address climate change.