A New Integrated Multi-Criteria Spatial Decision Support System for urban energy planning in the built environment

Sustainability contests represent a fundamental challenge to traditional urban development practices and concepts. Reducing energy consumption and greenhouse gas emissions from urban infrastructure and building stock, towards low-carbon cities requires a supportive planning process. In this regard, the use of appropriate tools and methods for addressing complex interactions of Urban Energy Planning (UEP) processes is needed. In particular, the problem of building stock energy consumption in the urban environment is crucial. A major aim of this research is to model energy consumption patterns based on bottom-up statistical-engineering combination methods. These methods evaluate the current status of energy consumption and different future energy saving scenarios to promote sustainable urban planning. However, the choice among urban energy planning scenarios is extensively based on multi-actors and multi-criteria aspects. Therefore, to anchor such a sustainable urban planning, a wider societal consensus building with an earnest and active engagement of relevant stakeholders in the city is essential. For this purpose, stakeholder-oriented approach plays a key role in implementing the effective strategies for urban and regional adaptation. The research, therefore, is also dealing with the integration of participative decisional processes of urban energy planning by organizing different focus groups involving real stakeholders. This fact can help to assess, over a short/long term period, the mix of measures by analyzing meaningful scenarios focused on energy consumptions, environmental impacts, economic and social aspects. The result is the development of a new Multi-Criteria Spatial Decision Support System (MC-SDSS), which is an interactive energetic plug-in in GIS environment using CommunityViz. This tool has been applied to a demonstrator case-study, related to a medium-sized city of the metropolitan area of Turin. However, the methodology used for delivering the tool can be applied to other contexts due to its flexibility. The new MC-SDSS is intended to facilitate the decisional process for stakeholders who can ask “what-if” questions and visualize “if-then” scenarios in a real-time. Moreover, it can explore a range of possible futures for assisting urban planners, policymakers and built environment stakeholders in their efforts to plan, design and manage low-carbon cities. This thesis is part of a national Smart City & Communities project, named “EEB-Zero Energy Buildings in Smart Urban Districts” (www.smartcommunitiestech.it).