Energy use in Urban Transport sector within the Sustainable Energy Action Plans (SEAPs) of three Italian Big Cities

Promising Renewable Energy solutions could be installed in cities, but they require specific morphological conditions as well as architectural integration. Transport sector is still neglected from a strong policy initiative. A first attempt along with a defined framework to attract economic resources as well as interested stakeholders is the Covenant of Mayors (CoM). Within this agreement, the Municipality has to design a plan, the so-called Sustainable Energy Action Plan (SEAP). The plan must contain a clear outline of the strategy and relative actions to be taken by the local authority to reach its commitments in 2020, in terms of sustainability goals set by EU 20-20-20. The aim of this paper is to discuss and evaluate the differences of fuel usage and transport sector interaction in Italian urban scenarios, taking into account geographical and morphological constraints, and to compare the forecasts for 2020 and 2030scenarios, in accordance with European and National laws in force

Local Energy Efficiency Interventions by the Prioritization of Thermal Zones in an Historical University Building

Architectural constraints are a crucial aspect in energy retrofitting of historic buildings. Usual global interventions are often not allowed since preserving historical values of the building stock is mandatory. In this paper, the authors provide an alternative procedure by identifying the most profitable local interventions in order to maintain the architectural values during the restoration and energy retrofitting operations. So, thermal zones prioritization is the key element considered in this study. Its aim is to analyse which energy efficiency measures could be applied to a listed building, but at certain technological elements rather than a unique choice for the entire building envelope. Thus it will prove that you can work with individual elements of the building without compromising the protection of architectural good. The attention was placed in promoting single measures and improving the quality of the built environment. The case study is an historical building in Rome, currently used for university purposes. The analysis was carried out through a building simulation model so that to assess the building energy performance before and after the selected interventions. The chosen software is TRNSYS. This approach shows how interventions, usually not applicable at the building scale, would be beneficial if applied at local scale such as a single thermal zone or a single technological unit. The authors built a reference scenario and, for each identified thermal zone, tested the energy efficiency improvement in terms of heating demand reduction coming from the hypothesized local intervention

Power Management Techniques for Data Centers: A Survey

With growing use of internet and exponential growth in amount of data to be stored and processed (known as 'big data'), the size of data centers has greatly increased. This, however, has resulted in significant increase in the power consumption of the data centers. For this reason, managing power consumption of data centers has become essential. In this paper, we highlight the need of achieving energy efficiency in data centers and survey several recent architectural techniques designed for power management of data centers. We also present a classification of these techniques based on their characteristics. This paper aims to provide insights into the techniques for improving energy efficiency of data centers and encourage the designers to invent novel solutions for managing the large power dissipation of data centers.Comment: Keywords: Data Centers, Power Management, Low-power Design, Energy Efficiency, Green Computing, DVFS, Server Consolidatio

Small-Scale Compressed Air Energy Storage Application for Renewable Energy Integration in a Listed Building

In the European Union (EU), where architectural heritage is significant, enhancing the energy performance of historical buildings is of great interest. Constraints such as the lack of space, especially within the historical centers and architectural peculiarities, make the application of technologies for renewable energy production and storage a challenging issue. This study presents a prototype system consisting of using the renewable energy from a photovoltaic (PV) array to compress air for a later expansion to produce electricity when needed. The PV-integrated small-scale compressed air energy storage system is designed to address the architectural constraints. It is located in the unoccupied basement of the building. An energy analysis was carried out for assessing the performance of the proposed system. The novelty of this study is to introduce experimental data of a CAES (compressed air energy storage) prototype that is suitable for dwelling applications as well as integration accounting for architectural constraints. The simulation, which was carried out for an average summer day, shows that the compression phase absorbs 32% of the PV energy excess in a vessel of 1.7 m(3), and the expansion phase covers 21.9% of the dwelling energy demand. The electrical efficiency of a daily cycle is equal to 11.6%. If air is compressed at 225 bar instead of 30 bar, 96.0% of PV energy excess is stored in a volume of 0.25 m3, with a production of 1.273 kWh, which is 26.0% of the demand

Scalable Approach to Uncertainty Quantification and Robust Design of Interconnected Dynamical Systems

Development of robust dynamical systems and networks such as autonomous aircraft systems capable of accomplishing complex missions faces challenges due to the dynamically evolving uncertainties coming from model uncertainties, necessity to operate in a hostile cluttered urban environment, and the distributed and dynamic nature of the communication and computation resources. Model-based robust design is difficult because of the complexity of the hybrid dynamic models including continuous vehicle dynamics, the discrete models of computations and communications, and the size of the problem. We will overview recent advances in methodology and tools to model, analyze, and design robust autonomous aerospace systems operating in uncertain environment, with stress on efficient uncertainty quantification and robust design using the case studies of the mission including model-based target tracking and search, and trajectory planning in uncertain urban environment. To show that the methodology is generally applicable to uncertain dynamical systems, we will also show examples of application of the new methods to efficient uncertainty quantification of energy usage in buildings, and stability assessment of interconnected power networks

Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects

While monolithic satellite missions still pose significant advantages in terms of accuracy and operations, novel distributed architectures are promising improved flexibility, responsiveness, and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance satellites are becoming feasible and advantageous alternatives requiring the adoption of new operation paradigms that enhance their autonomy. While autonomy is a notion that is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy is also presented as a necessary feature to bring new distributed Earth observation functions (which require coordination and collaboration mechanisms) and to allow for novel structural functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission Planning and Scheduling (MPS) frameworks are then presented as a key component to implement autonomous operations in satellite missions. An exhaustive knowledge classification explores the design aspects of MPS for DSS, and conceptually groups them into: components and organizational paradigms; problem modeling and representation; optimization techniques and metaheuristics; execution and runtime characteristics and the notions of tasks, resources, and constraints. This paper concludes by proposing future strands of work devoted to study the trade-offs of autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that consider some of the limitations of small spacecraft technologies.Postprint (author's final draft

Intelligent energy buildings based on RES and Nanotechnology

The paper presents the design features, the energy modelling and optical performance details of two pilot Intelligent Energy Buildings, (IEB). Both are evolution of the Zero Energy Building (ZEB) concept. RES innovations backed up by signal processing, simulation models and ICT tools were embedded into the building structures in order to implement a new predictive energy management concept. In addition, nano-coatings, produced by TiO2 and ITO nano-particles, were deposited on the IEB structural elements and especially on the window panes and the PV glass covers. They exhibited promising SSP values which lowered the cooling loads and increased the PV modules yield. Both pilot IEB units were equipped with an on-line dynamic hourly solar radiation prediction model, implemented by sensors and the related software to manage effectively the energy source, the loads and the storage or the backup system. The IEB energy sources covered the thermal loads via a south façade embedded in the wall and a solar roof which consists of a specially designed solar collector type, while a PV generator is part of the solar roof, like a compact BIPV in hybrid configuration to a small wind turbine

Microservices and Machine Learning Algorithms for Adaptive Green Buildings

In recent years, the use of services for Open Systems development has consolidated and strengthened. Advances in the Service Science and Engineering (SSE) community, promoted by the reinforcement of Web Services and Semantic Web technologies and the presence of new Cloud computing techniques, such as the proliferation of microservices solutions, have allowed software architects to experiment and develop new ways of building open and adaptable computer systems at runtime. Home automation, intelligent buildings, robotics, graphical user interfaces are some of the social atmosphere environments suitable in which to apply certain innovative trends. This paper presents a schema for the adaptation of Dynamic Computer Systems (DCS) using interdisciplinary techniques on model-driven engineering, service engineering and soft computing. The proposal manages an orchestrated microservices schema for adapting component-based software architectural systems at runtime. This schema has been developed as a three-layer adaptive transformation process that is supported on a rule-based decision-making service implemented by means of Machine Learning (ML) algorithms. The experimental development was implemented in the Solar Energy Research Center (CIESOL) applying the proposed microservices schema for adapting home architectural atmosphere systems on Green Buildings