As the world transitions toward a sustainable energy future, the role of integrated assessment models has become increasingly crucial. These complex tools aim to capture the intricate relationships between energy systems, the economy, and the environment. However, traditional models often focus primarily on economic efficiency, overlooking the critical social and environmental dimensions of energy decisions.
This is where the WIMBY project steps in. Dr James Price, a researcher at UCL’s Energy Institute, and his team are at the forefront of incorporating social and environmental factors into high-resolution energy system models.
Harnessing high-resolution modelling for Europe’s energy future
At the heart of the WIMBY project is a high-resolution energy model known as “highRes,” which divides Europe into distinct areas based on NUTS-2 regions. The model integrates detailed data on the social and environmental aspects of wind power, much of it developed within WIMBY, and uses it to plan optimal European electricity systems that account for and trade-off these factors.
NUTS-2 areas that highRES models for wind deployment across Europe
“Normally, these models focus on designing the system in the cheapest way possible,” James explains. “What we’re doing is introducing constraints into the model—restrictions that shape where wind farms can and cannot be built. This includes excluding cities, national parks, and areas with high risks to birds and bats.”
The team uses a GIS-based mapping approach to layer various datasets, enabling them to identify suitable locations for wind energy development while respecting environmental and social concerns.
The power of layers in energy modelling
“Imagine a map of Europe, and we’re layering different filters,” he says. “One layer excludes cities, another excludes national parks, and another identifies areas critical to wildlife conservation. By combining these layers, we calculate the available land for wind farm development while optimising the overall energy system.”
“We examine the distribution of impacts within a country,” James explains. “In scenarios prioritising wildlife protection, we exclude larger areas. For less restrictive scenarios, we allow for more land to be used.” This flexibility enables the WIMBY team to explore a spectrum of future scenarios, balancing environmental, social, and economic priorities based on stakeholder preferences.
Balancing visual impact and renewable development
One of the more nuanced challenges the project addresses is public concern over the visual impact of wind turbines. He talked about a related study in Great Britain which used a crowd-sourced dataset called “ScenicOrNot” to rank the scenic quality of each one-square kilometre of the country.
Two maps of Great Britain illustrate the impact of different restrictions on onshore wind deployment in highRES. In the “Low” scenario, only highly scenic areas and technical constraints (e.g., cities) are excluded, while in the “High” scenario, all areas ranging from moderately scenic to highly scenic are restricted (along with technical constraints). The green areas on both maps represent locations where highRES permits wind development.
“We created scenarios with varying levels of sensitivity to visual impact,” James says. “In some cases, we restricted wind power development in highRES in only the most scenic areas, like Scotland’s Highlands. In others, we limited development in moderately scenic regions or even urban edges. These scenarios help us understand how wind farm placement and system costs shift depending on public sentiment around visual landscapes.”
A great tool that WIMBY is developing to interact with stakeholders, citizens and understand their sentiment regarding wind power, is the interactive map, which empowers stakeholders to explore different scenarios and trade-offs. While highRES requires significant computational effort and its results are precomputed, the scenarios it will elaborate will also users to adjust sliders for priorities like wildlife conservation and visual impact and to understand their impact on system cost.
“This is where the magic happens,” says James. “Users can see in real time how their choices affect wind placement, costs, and environmental and social outcomes. It’s about making the implications of their preferences tangible and accessible.”
The interactive map serves not just as a visualisation tool but also as a platform for public engagement. By enabling users to interact with scenarios, the WIMBY project fosters transparency and inclusivity in energy system design.
“We want to include people in the type of modelling we do,” James emphasises. “Otherwise, you’re not going to deliver the energy transition that people can truly support.”
Through tools like this, the team aims to democratise the design process, helping communities understand and influence how renewable energy infrastructure is developed.
Challenges and opportunities in holistic energy modelling
Incorporating social and environmental factors into high-resolution energy models is not without its challenges. Data availability and quality remain critical hurdles, as does the balance between model complexity and computational feasibility. “Quantifying and monetising these impacts in a meaningful way is often difficult,” James admits. “We also need to make these models interpretable for stakeholders.” It is also quite difficult to engage diverse stakeholders and integrating their priorities into the energy modelling process. During the interview, James underscored the importance of a co-production approach, where stakeholders actively contribute to model development.
“The hope is to create scenarios that resonate with people and spark meaningful discussions,” he says. “But striking a balance between technical optimisation and public alignment is key.”
By embracing a more holistic, participatory approach, the WIMBY project aims to create energy systems that balance economic, social, and environmental considerations. This work highlights the importance of transparent and inclusive processes in shaping Europe’s renewable energy landscape.
“In the end,” James concludes, “these models aren’t just about numbers, they’re about people. The energy systems we design today will define the landscapes and communities of tomorrow.”
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