At its core, energy system modelling is the use of software simulations and mathematical models to understand, analyse, and predict how energy systems function. It allows experts, policy- and decision-makers to explore different energy scenarios, identify potential challenges, and assess the impacts of various energy policies before they are implemented in the real world.
As countries around the world transition to cleaner energy sources, it’s essential to have tools that can predict how these changes will impact everything from energy production to consumption patterns. Energy system modelling can identify the most efficient ways to incorporate green technologies, such as wind farms and electric vehicles while ensuring that energy remains reliable and affordable.
For example, by using energy system models, experts can simulate how a shift from fossil fuels to renewable energy would affect the reliability of power grids. This helps avoid blackouts and ensures that energy is available when it’s needed most.
Energy system modelling will become more sophisticated as technologies continue to advance. From enhancing the use of artificial intelligence to simulating future scenarios, the possibilities for improving energy systems are endless. This ongoing innovation is critical as we strive to balance the demands for economic growth, environmental protection, and energy security.
Mopo tools for energy system modelling
More specifically, the Mopo project provides component and data tools as well as a set of tools for energy system modelling, called Spine tools.
The component tools use open-access data sources to create sectoral models at a user-chosen level of detail and scope. They include tools and data for variable renewable energy (wind), hydropower, networks, conversion, building stocks and end-use sectors.
Based on the component tools, the Spine Tools allow flexible management and visualisation of data, scenarios and workflows (Spine Toolbox) and enable the design of resilient integrated energy systems to be optimised, advancing the state-of-the-art in energy system modelling (SpineOpt).
In the end, energy system modelling is not just about creating smarter, more efficient energy systems – it’s about helping decision-makers, scientists, and communities to work together toward a cleaner, more sustainable future for all.
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