The definition, characterization and implementation of Positive Energy Districts is crucial in the path towards urban decarbonization and energy transition. However, several issues still must be addressed: the need for a clear and comprehensive definition, and the settlement of a consistent design approach for Positive Energy Districts. As emerged throughout the workshop held during the fourth edition of Smart and Sustainable Planning for Cities and Regions Conference (SSPCR 2022) in Bolzano (Italy), further critical points are also linked to the planning, modeling and assessment steps, besides sustainability aspects and stakeholders’ involvement. The “World Café” methodology adopted during the workshop allowed for simple—but also effective and flexible—group discussions focused on the detection of key PED characteristics, such as morphologic, socio-economic, demographic, technological, quality-of-life and feasibility factors. Four main work groups were defined in order to allow them to share, compare and discuss around five main PED-related topics: energy efficiency, energy flexibility, e-mobility, soft mobility, and low-carbon generation. Indeed, to properly deal with PED challenges and crucial aspects, it is necessary to combine and balance these technologies with enabler factors like financing instruments, social innovation and involvement, innovative governance and far-sighted policies. This paper proposes, in a structured form, the main outcomes of the co-creation approach developed during the workshop. The importance of implementing a holistic approach was highlighted: it requires a systematic and consistent integration of economic, environmental and social aspects directly connected to an interdisciplinary cross-sectorial collaboration between researchers, policymakers, industries, municipalities, and citizens. Furthermore, it was reaffirmed that, to make informed and reasoned decisions throughout an effective PED design and planning process, social, ecological, and cultural factors (besides merely technical aspects) play a crucial role. Thanks to the valuable insights and recommendations gathered from the workshop participants, a conscious awareness of key issues in PED design and implementation emerged, and the fundamental role of stakeholders in the PED development path was confirmed.

Thermal comfort and energy saving have become a priority for construction industry professionals. An important parameter of the comfort is the mean radiant temperature and its dependence on the building envelope. In the present research, a dynamic physical model has been studied in a climatic chamber, linked to the specific heat (C), density () and thermal conductivity (). The heat capacity is usually quantifiable in small, homogeneous and uniform samples by the application of calorimetric methods. Consequently, the building energy consumption assessed through calorimetric methods, is often quite different from the energy consumption measured in situ. In this work an experimental model for the assessment of specific heat of real-size building components is proposed. Such a parameter was determined by measuring the heat flow through a building wall. The model has been validated by comparing the evaluated properties of known materials for different thermal gaps.

The home automation system to control the climatic health in confined environments is the subject of this article. The standard UNI EN ISO 7730:2006 classifies the conditions of moderate confined environments by three categories according to the PMV index. The comfort sensation is mainly affected by four variables: air temperature, mean radiant temperature, air velocity, relative humidity. They are all mechanical and thermal quantities therefore they are measured through the same measurement method. In evaluating the PMV index two more variables are taken into account: metabolism and clothing insulation. They can be evaluated by different accuracy levels. Their indirect measure is subjected to more uncertainty than the above four measuring parameters and the distribution is typically non-Gaussian. The paper analyses the uncertainty in PMV measuring through the Monte Carlo simulation. The proposed study identifies the different weight of independent variables showing as their uncertainty, particularly those referred to metabolism and clothing insulation, affects considerably the final values for classifying the moderate environments.