Regulations corroborate the importance of retrofitting existing building stocks or constructing new energy-efficient districts. There is, thus, a need for modeling tools to evaluate energy scenarios to better manage and design cities, and numerous methodologies and tools have been developed. Among them, Urban Building Energy Modelling (UBEM) tools allow the energy simulation of buildings at large scales. Choosing an appropriate UBEM tool, balancing the level of complexity, accuracy, usability, and computing needs, remains a challenge for users. The review focuses on the main bottom-up physics-based UBEM tools, comparing them from a user-oriented perspective. Five categories are used: (i) the required inputs, (ii) the reported outputs, (iii) the exploited workflow, (iv) the applicability of each tool, and (v) the potential users. Moreover, a critical discussion is proposed, focusing on interests and trends in research and development. The results highlighted major differences between UBEM tools that must be considered to choose the proper one for an application. Barriers of adoption of UBEM tools include the needs of a standardized ontology, a common threedimensional city model, a standard procedure to collect data, and a standard set of test cases. This feeds into future development of UBEM tools to support cities' sustainability goals.

In the last four decades several methods have been used to model occupants' presence and actions (OPA) in buildings according to different purposes, available computational power, and technical solutions. This study reviews approaches, methods and key findings related to OPA modeling in buildings. An extensive database of related research documents is systematically constructed, and, using bibliometric analysis techniques, the scientific production and landscape are described. The initial literature screening identified more than 750 studies, out of which 278 publications were selected. They provide an overarching view of the development of OPA modeling methods. The research field has evolved from longitudinal collaborative efforts since the late 1970s and, so far, covers diverse building typologies mostly concentrated in a few climate zones. The modeling approaches in the selected literature are grouped into three categories (rule-based models, stochastic OPA modeling, and data-driven methods) for modeling occupancy-related target functions and a set of occupants' actions (window, solar shading, electric lighting, thermostat adjustment, clothing adjustment and appliance use). The explanatory modeling is conventionally based on the model-based paradigm where occupant behavior is assumed to be stochastic, while the Revised Manuscript with No Changes MarkedClick here to view linked References data-driven paradigm has found wide applications for the predictive modeling of OPA, applicable to control systems. The lack of established standard evaluation protocols was identified as a scientifically important yet rarely addressed research question. In addition, machine learning and deep learning are emerging in recent years as promising methods to address OPA modeling in real-world applications.

Improving the reliability of energy simulation outputs is becoming a pressing task to reduce the performance gap between the design and the operation of buildings. Occupant behaviour modelling is one of the most relevant sources of uncertainty in building energy modelling and is typically modelled via a priori choices made by modellers. Thus, an improvement in the description of occupant behaviour is needed. To this regard, the availability of smart meter recordings might help to generate more reliable input data for building energy models. This paper discusses a novel data-driven procedure that enables to create yearly occupancy and occupantrelated electric load profiles to inform building energy modelling, using a typical uneven database made available by energy operators. The procedure is subdivided into three main tasks. The first has the intent to detect representative occupant-related electric load profiles from smart meters readings. The second task aims to generate yearly occupancy profiles from the same database. The last task assesses the impact of the generated occupancy and occupant-related electric load profiles on building energy simulation outputs. The procedure is applied to the case study of a multi-residential building in Milan, Italy and is meant to show the possibility to overcome deterministic inputs that might have little relation with the actual building operation. It showed a substantial improvement in the reliability of building energy simulation and that occupant related load profiles may account for about 8 % of the building's energy need for space heating.

Urban building energy modeling (UBEM) seeks to evaluate strategies to optimize building energy use at urban scale to support a city's building energy goals. Prototype building models are usually developed to represent typical urban building characteristics of a specific use type, construction year, and climate zone, as detailed characteristics of individual buildings at urban scale are difficult to obtain. This study investigated the Italian building stock, developing 46 building prototypes, based on construction year, for residential and office buildings. The study included 16 single-family buildings, 16 multi-family buildings, and 14 office buildings. Building envelope properties and heating, ventilation, and air conditioning system characteristics were defined according to existing building energy codes and standards for climatic zone E, which covers about half the Italian municipalities. Novel contributions of this study include (1) detailed specifications of prototype building energy models for Italian residential and office buildings that can be adopted by UBEM tools, and (2) a dataset in GeoJSON format of Italian urban buildings compiled from diverse data sources and national standards. The developed prototype building specifications, the building dataset, and the workflow can be applied to create other building prototypes and to support Italian national building energy efficiency and environmental goals.

• A novel physics-based bottom-up approach is developed to calculate heat emissions from buildings to ambient air. • Heat emissions are grouped into three components: envelope, zone exhaust/exfiltration, and HVAC system. • Heat emissions of 16 building types in 4 climates and 2 efficiency levels are simulated. • Daily and seasonal patterns of heat emissions and their variations by building type, climate and efficiency are analyzed. • Detailed hourly anthropogenic heat from buildings can improve urban microclimate modeling.

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The construction of energy-efficient buildings and the planning of suitable energy supply systems are fundamental undertakings to reach a more sustainable future. Decision-makers need evaluation criteria and possible scenarios to establish the best options to decrease cities' energy consumption. Thus, in the last decade, several tools for Urban Building Energy Modelling (UBEM) have been developed to achieve this result. The aim of this paper is to give a practical overview of the different methods and approaches used by UBEM. The work compares the available and most relevant UBEM tools, to assess their potential and limits. The characteristics of the main UBEM tools are compared with the intent to create a brief selection guide for new users.

Increasing concerns over climate change and energy poverty have triggered the transition toward a decentralized energy system through the widespread adoption of renewable energy technologies. Although this transition was led, over past decades, mainly by major investors and large industrial players, citizens and local authorities are increasingly playing an active role in delivering clean energy investments. In particular, the current European Renewable Energy Directive introduced Renewable Energy Communities (RECs), which allow citizens to collectively organize their participation in the energy market, leading to a more distributed renewable energy system and new forms of sustainable, collaborative, and democratic economies. RECs currently under implementation show differences among European countries due to the different national contexts. A literature review exploring the peculiar Italian regulatory framework on RECs and its recent evolution has been carried out to identify available national and regional financial support mechanisms, barriers, and emerging trends in the diffusion of RECs across the country. The paper reviews and describes three main approaches that emerged in the development of RECs in Italy, discussing their strengths, and limitations. In addition, it provides a brief comparison of the regulatory framework in different European countries, highlighting the distinctive features of the Italian experience. Although the development of RECs in Italy involved a combination of both public and private initiatives, the leading role of local authorities as promoters and aggregators of RECs is evident. This role helps preserve the social impact of RECs but might slow down their implementation due to bureaucratic issues often linked to public procedures and procurement processes, as well as the lack of sufficient expertise within local authorities.