Sommario
- 1 A Digital Tool for Complex Urban Decisions
- 2 Supporting the Design of Positive Energy Districts
- 3 How the Decision Support System Works
- 4 A Multi-Dimensional Set of Criteria
- 5 Flexibility and Contextual Adaptation
- 6 From Analysis to Action
- 7 Integration within the Making PEDs Platform
- 8 Driving the Transition to Sustainable and Climate-Neutral Cities
Planning climate-neutral cities requires informed, data-driven decisions. Public administrators, urban planners, and energy professionals must balance energy and environmental targets, financial constraints, and social priorities while navigating an increasing number of technological options.
To support this process, R2M Solution, within the Making PEDs project, has developed a Decision Support System (DSS) for urban energy planning. The tool is designed to guide decision makers in the design and implementation of Positive Energy Districts (PEDs) by identifying the most effective and sustainable scenario.
A Digital Tool for Complex Urban Decisions
A Decision Support System is a digital solution that enables users to analyse complex problems and compare multiple scenarios in a structured way. In the context of sustainable cities and energy efficiency, the DSS developed by R2M Solution within the Making PEDs project provides a comprehensive framework for evaluating district-level energy strategies.
In practice, the system supports decision makers in:
- comparing alternative scenarios at district level
- assessing environmental, economic, and social impacts simultaneously
- choosing strategies aligned with climate-neutrality objectives
This integrated perspective is essential when planning Positive Energy Districts, where trade-offs between cost, performance, and social inclusion are unavoidable.
Supporting the Design of Positive Energy Districts
Positive Energy Districts are a key enabler of climate-neutral cities, as they aim to produce more energy than they consume. However, their design requires the careful selection of technologies, services, and planning strategies.
Within the MakingPEDs platform, the DSS supports this process by generating and comparing alternative scenarios at district level. By aligning technical results with local priorities and policy objectives, the system reduces uncertainty and improves the overall quality of decision-making.
How the Decision Support System Works
The DSS is based on a Multi-Attribute Analysis integrating Analytic Hierarchy Process (AHP), a widely used methodology for complex decision-making.
The process is structured into three main phases:
- Problem structuring, where users define the goal, select evaluation criteria, and identify possible alternatives
- Comparison of alternatives, allowing users to assign relative importance to criteria and express preferences across multiple alternatives
- Synthesis of results, where the system aggregates inputs and produces a composite score with ranked list of scenarios
This structured approach breaks down complex decisions into manageable steps, making them easier to analyze and compare, helping users clearly understand trade-offs between different options.
A Multi-Dimensional Set of Criteria
One of the key strengths of the DSS lies in its ability to integrate multiple dimensions of sustainability into the decision-making process. The system evaluates scenarios through a comprehensive set of Key Performance Indicators (KPIs) transposed into evaluation criteria, ensuring that decisions reflect both technical and societal priorities.
The main categories include:
- Energy and environmental performance, such as energy efficiency, greenhouse gas emissions, and resource use
- Energy vulnerability, including income levels, vulnerable populations, and energy affordability
- Financial and economic factors, covering investment costs, operational costs, and job creation
- Environmental balance at district level, including impacts on transport, water, waste, and green areas
Users can assign different weights to these criteria, tailoring the analysis to their specific context and strategic objectives.
Flexibility and Contextual Adaptation
Urban energy planning is influenced by dynamic external factors. For this reason, the DSS is designed to be flexible and context-aware.
Thanks to the integration of the adapted Analytic Hierarchy Process within the DSS, users can contribute their contextual knowledge, such as funding opportunities, regulatory frameworks, or local constraints, to inform the analysis. This ensures that the results are both technically robust and grounded in realistic, context-specific conditions, making them implementable within specific urban contexts.
From Analysis to Action
The outcome of the DSS is a clear and transparent ranking of alternative PED scenarios. This enables decision makers to understand how each option performs across different criteria and how changes in priorities influence results.
For example, a scenario that performs best from a financial perspective may not achieve the highest environmental performance. By adjusting the weighting of criteria, users can explore different scenarios and identify solutions that provide a more balanced outcome.
In this way, the DSS does not replace human judgment but strengthens it, providing a structured and evidence-based foundation for decision-making.
Making PEDs platform developed and deployed by CICLICA, with the support of the project’s partners
Integration within the Making PEDs Platform
The DSS is fully integrated within the broader Making PEDs platform, which also includes Digital Twin models used to simulate district-level scenarios.
The platform has been tested in four European cities—Linz (AT), Bærum (NO), Sant Esteve de Palautordera (ES), and Civitavecchia (IT) —demonstrating its adaptability across diverse urban contexts. Although developed based on these case studies, the methodology is designed to be replicable in cities across Europe.
Driving the Transition to Sustainable and Climate-Neutral Cities
With the development of the Decision Support System, R2M Solution reinforces its commitment to supporting cities in their transition towards sustainability and climate neutrality. By combining digital innovation with expertise in energy efficiency, the DSS enables more transparent, informed, and impactful urban planning decisions.
To further strengthen its scientific foundation, R2M Solution has also published a scientific paper detailing the methodology behind the system and the application of the Analytic Hierarchy Process.
