In this paper, we provide a view of the ongoing PEDRERA project, whose main scope is to design a district simulation model able to set and analyze a reliable prediction of potential business scenarios on large scale retrofitting actions, and to evaluate the overall co-benefits resulting from the renovation process of a cluster of buildings. According to this purpose and to a Positive Energy Districts (PEDs) approach, the model combines systemized data—at both building and district scale—from multiple sources and domains. A sensitive analysis of 200 scenarios provided a quick perception on how results will change once inputs are defined, and how attended results will answer to stakeholders’ requirements. In order to enable a clever input analysis and to appraise wide-ranging ranks of Key Performance Indicators (KPIs) suited to each stakeholder and design phase targets, the model is currently under the implementation in the urbanZEB tool’s web platform.

In accordance with the new recovery plan, Next Generation EU (NGEU), and the need to speed up the transition of cities towards a new sustainable model, this paper provides an overview of the outcomes of the PEDRERA project, which is focused on the development of a novel tool able to calculate multiple key performance indicators that can support renovation actions at the district level, according to a Positive Energy District (PED) concept. The new tool is programmed in Python programming language and is useful to evaluate several strategies for the renovation of existing building stock. It moves from a quick list of input according to several Public Private Partnership (PPP) models, in addition to other potential business models. Furthermore, the design of the model is supported by a step-by-step methodology in order to deal with a “financial appraisal” that is interactive in each context, customizable for each stakeholder, and user-friendly. The paper describes this innovative tool and reports on the stronger potential that this model can offer when it runs in a QGIS software environment and interacts with a PostgreSQL database, as demonstrated in two case studies located in Spain.

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