1,721,012 research outputs found
Scenario attuale e prospettive della climatizzazione a bassa "exergia" verso un mondo radiante
No full textRivista UponorPi
Solar Technologies as a Driver to Limit Energy Poverty in the Rocinha Favela
No full textIn developing countries, the constant conditions of economic and social crises resulted in a continuous expansion of non-regulated solutions to access energy services, especially in low-income settlements of urban areas such as Brazilian favelas, where people rely on illegal connections to the power grid, called gato, to fulfil their energy needs. An appropriate exploitation of renewable energy could reduce these energy thefts, contributing to urban sustainability and creating employment opportunities for locals. This section presents the results of a study developed for a pilot area within the favela of Rocinha, meant to establish ways to limit energy poverty, by spreading access to renewable energy. Both the favela’s energy uses, the potential of local climate and of photovoltaic (PV) panel’s production, have been assessed, leading to the proposal of a solar district based on the use of PV and of battery storage systems. In addition to it, the deployment of an urban management system (UMS), able to manage data coming from different urban facilities, will contribute to outline a new sustainable culture on the use of energy and urban services through the active participation of consumers
Environmental impact assessment of renewable energy communities: the analysis of an Italian neighbourhood
Full text linkIn recent years, research in renewable energy community (REC) schemes, coupling renewable energy sources and building energy efficiency, is gaining momentum. In this context, Urban Building Energy Modelling tools (UBEMs) have proved to comply with the design requirements of such schemes. However, a clear methodology exploiting UBEMs to support the design of RECs is still missing, especially for assessing the greenhouse gas (GHG) emissions associated with their specific technical configuration. Here, the REC is modelled in “urban modeling interface” (umi), one of the main bottom-up physics-based UBEMs. A building archetype approach is exploited to model the scenarios and assess embodied GHG emissions. The proposed methdology gives the possibility to investigate both the embodied and operational emissions for different REC configuration. A residential neighbourhood in Italy is selected as case study. The results demonstrate the importance of considering building characteristics when analysing emissions reductions in energy-sharing schemes, underlining the necessity of coupling the REC design with energy retrofit interventions
Technical and economic assessment of a battery storage system for a nZEB in the Mediterranean climate
Full text linkIn recent years, the promotion of nearly-Zero Energy Buildings (nZEB), has become a priority for European member states. In order to get this label, typically, a monthly or yearly energy balance of energy use through the exploitation of renewable energy sources (RES) is required, but not a hourly balance. This approach may determine a low exploitation of the RES on site in the case of solar and wind energy, because they are intermittent by nature. Moreover, energy production and energy use peaks are often in mismatch during the day. Battery energy storage systems (BESS) offer a solution to better integrate RES into buildings as well as into the grid, increasing its reliability and minimizing interactions. The cost of these systems is rapidly decreasing, opening new economic opportunities for investors. However, for many applications they do not yet represent the optimal cost-effective solution due to the lifespan of their short-lived components. The paper investigates the technical and economic feasibility of integrating a BESS into a high-performance residential building in the Mediterranean climate based on the outcomes of an original case study based research. The existing photovoltaic system combined with the BESS may substantially optimize the energy use, maximizing the self-consumption and minimizing grid interactions; nevertheless, the pay-back time may become fully-attractive for the analysed building, only if BESS costs will halve by 2030
From nearly zero energy to carbon‐neutral: Case study of a hospitality building
Full text linkIn recent years, many cities around the world have pledged to upgrade their building stocks to carbon‐neutral. However, the literature does not yet provide a shared definition of carbon-neutral building (CNB), and the assessment objectives and methodological approaches are vague and fragmented. Starting from the available standards and scientific literature on life cycle assessment (LCA), this paper advances an operational definition for CNB on the basis of an explicit calculation approach. It then applies the definition to an urban case study, comparing it against a state-of‐the‐art nearly Zero Energy Building (nZEB) scenario, with the intent of highlighting the major practical limitations connected to the application of a methodologically sound carbon neutrality cal-culation. The case study shows that carbon neutral objectives can hardly be achieved by single urban buildings because of the lack of spaces that can provide onsite carbon offsetting actions. Carbon neutrality may be better approached at the city, regional, or national scales, where overarching policies may be defined
Effects of COVID-19 confinement on the simulation of energy needs and uses of residential buildings in Milan
Full text linkThis paper examines the impact of COVID-19 confinement on the simulation of energy needs and uses of residential buildings in Milan. Data-driven schedules for electricity use before and during lockdown, derived from smart metering data, are applied to an urban building energy model to analyze their effects on energy needs for heating and cooling and the energy use for lighting and for other services. Electricity uses, heating and cooling needs, and total primary energy (TOE) are compared for pre-COVID and during-COVID cases. Electricity increases by 8%, while heating decreases by 10%, and cooling increases by 26%. The 5% decrease in TOE is mainly due to the decrease in heating. The study uses heat maps to display the coefficient of variation of root mean square error (CVRMSE) at different temporal and spatial aggregations, indicating significant differences between pre- and during-COVID cases. The CVRMSE for electricity consumption is highest at the hourly level for single buildings, reaching a maximum of 44, and decreases at higher levels of aggregation. The CVRMSE for TOE is highest at the hourly level for single buildings, reaching a maximum of 230. A scenario is created by combining during-COVID and pre-COVID schedules for a hybrid work model, called post-COVID. The post-COVID scenario results indicate a significant impact of remote work on energy consumption patterns
Building stock simulation to support the development of a district multi-energy grid
Full text linkThe urbanization process is constantly increasing worldwide. Today over 50 % of the population resides in urban areas and this value is expected to grow up to 68 % by 2050. In this scenario, the development of district scale energy grids and management systems has become crucial to optimize energy use and to balance energy flows within the cities, encouraging the use of renewable sources and self-consumption. This study focusses on a district under development in the city of Milan, involving an urban area of about 920 000 m2, which, once completed, will count for about 4 500 apartments, a school and a few other commercial uses. The existing energy systems consist of an electric grid, including a small photovoltaic field, a district heating system and a local district cooling system exploiting groundwater via heat pumps. They serve, at present, seven residential tower buildings (400 apartments). The overarching aim of the research is to evolve the existing grid into a smart energy grid able to guarantee an intelligent management of the district, empowering eventually people to apply for demand-response schemes, electric mobility and other innovative services. In order to perform such an improvement and extension of the exiting grid, it is necessary to evaluate and simulate the profiles and dynamics of the final energy uses for the residential buildings, that will represent the major load on site. Since monitoring data are not yet available for the district, the evaluation of the energy performance of the existing buildings has been developed through dynamic energy simulations via the definition of profile loads of the most frequent apartment typologies, that allow, moreover, to simulate further developments in the districts. Besides, a monitoring plan for the existing systems has been developed and implemented. Monitoring data will be used at first for validating the developed load profiles; then, they will be analysed to develop optimisation algorithms for the management of the upgraded energy grid. In this paper, the case study is presented and the results of the analysis, via energy simulation, on the existing building stock are reported
A data-driven procedure to model occupancy and occupant-related electric load profiles in residential buildings for energy simulation
Full text linkImproving 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 occupant-related 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
Coloured BIPV technologies: Methodological and experimental assessment for architecturally sensitive areas
Full text linkEnergy flexibility in buildings is gaining momentum with the introduction of new European directives that enable buildings to manage their own energy demand and production, by storing, consuming or selling electricity according to their need. The transition towards a low-carbon energy system, through the promotion of on-site energy production and enhancement of self-consumption, can be supported by building-integrated photovoltaics (BIPV) technologies. This paper investigates the aesthetic and technological integration of hidden coloured PV modules in architecturally sensitive areas that seem to be the best possibility to favour a balance between conservation and energy issues. First, a multidisciplinary methodology for evaluating the aesthetic and technical integration of PV systems in architecturally sensitive area is proposed, referring to the technologies available on the market. Second, the experimental characterisation of the technical performance specific BIPV modules and their comparison with standard modules under standard weather condition are analysed, with the aim of acquiring useful data for comparing the modules' integration properties and performance. For this purpose, new testbeds have been set up to investigate the aesthetic integration and the energy performances of innovative BIPV products. The paper describes the analyses carried out to define the final configuration of these experimental testbeds. Finally, the experimental characterisation at standard test conditions of two coloured BIPV modules is presented and the experimental design for the outdoor testing is outlined
Towards an AI-Based Framework for Autonomous Design and Construction: Learning from Reinforcement Learning Success in RTS Games
No full textThe present study summarizes the state-of-the-art research in deep reinforcement learning (DRL) techniques in the architecture, engineering and construction industry and it formulates a general framework for autonomous design and construction. The framework is inspired by the noticeable success of DRL and imitation learning algorithms in real time strategy (RTS) games, which normally require efficient resource planning and long-term strategic coordination.
The objective of the proposed framework is to reduce data segregation and loss of project information. The prevention of data leakage is achieved by replacing the linear process with an iterative one where the consequences of design decisions on the construction process (and vice versa) are understood in a virtual environment simultaneously. The proposed framework also exploits recent advances in simulated physics-based environments, like game engines. Designers and builders can therefore simulate on-site scenarios and exchange views on the required design and construction goals early in the project. The multi-objective optimization problem is then passed to artificial agents. These agents train on achieving the project goals under the supervision of a team of humans. The tacit knowledge transferred to the brain of the agents can later be deployed on-site through execution robots. The proposed approach is demonstrated by a proof-of-concept software application, showcasing a brick pavilion project. Design and construction constraints are first imposed by the user. Agents are then trained using a DRL algorithm
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