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This article describes an innovative method for measuring lighting levels and other lighting parameters through the use of aerial imagery of towns and cities. Combined with electricity consumption data from smart electricity meters, it was possible to measure the energy efficiency of public lighting installations. The results of this study also confirmed that lighting measurements, installation material, luminaire position, and electricity consumption data can be easily integrated into geographic information systems (GIS). The main advantage of this new methodology is that it provides information about lighting installations in large areas in less time than more conventional procedures. It is thus a more effective way of obtaining the data required to calculate the energy efficiency of lighting levels and electricity consumption. There is even the possibility of generating street lighting maps that provide local administrations with up-to-date information regarding the status of public lighting installations in their city. In this way, modifications or improvements can be made to achieve greater energy savings and, if necessary, to correct the distribution or configuration of public lighting systems to make them more efficient and sustainable. This research studied levels of street lighting and calculated the energy efficiency in various streets of Deifontes (Granada), through the use of aerial imagery.

3D city models are a useful tool to analyze the solar potential of neighborhoods and cities. These models are built from buildings footprints and elevation measurements. Footprints are widely available, but elevation datasets remain expensive and time-consuming to acquire. Our hypothesis is that the GIS cadastral data can be used to build a 3D model automatically, so that generating complete cities 3D models can be done in a short time with already available data. We propose a method for the automatic construction of 3D models of cities and neighborhoods from 2D cadastral data and study their usefulness for solar analysis by comparing the results with those from a hand-built model. The results show that the accuracy in evaluating solar access on pedestrian areas and solar potential on rooftops with the automatic method is close to that from the hand-built model with slight differences of 3.4% and 2.2%, respectively. On the other hand, time saving with the automatic models is significant. A neighborhood of 400,000 m2 can be built up in 30 min, 50 times faster than by hand, and an entire city of 967 km2 can be built in 8.5 h.

The cataloguing and revision of reactor pressure vessels (RPV) manufacturing and in-service inspection codes and their standardized material specifications—as a technical heritage—are essential for understanding the historical evolution of criteria and for enabling the comparison of the various national regulations, integrating the most relevant results from the scientific research. The analysis of the development of documents including standardized requirements and the comparison of regulations is crucial to be able to implement learned lessons and comprehend the progress of increasingly stringent safety criteria, contributing to sustainable nuclear power generation in the future. A novel methodology is presented in this work where a thorough review of the regulations and technical codes for the manufacture and in-service inspection of RPVs, considering the implementation of scientific advances, is performed. In addition, an analysis focused on the differences between irradiation embrittlement prediction models and acceptance criteria for detected defects (both during manufacturing and in-service inspection) described by the different technical codes as required by different national regulations such as American, German, French or Russian is performed. The most stringent materials requirements for RPV manufacturing are provided by the American and German codes. The French code is the most stringent with respect to the reference defect size using as a criterion in the in-service inspection.

The objective of this paper involves the analysis of opportunities for the management of Railway Systems’ demand using Physical-Based models and aggregation tools well-known in “conventional” Power Systems to develop and enlarge the portfolio of Distributed Energy Resources. This proposed framework would also enable the use of railway flexible resources to their use in Power Systems. The work considers trends for the development of railway transportation units through the adoption of technologies that increase the flexibility of railway units. For instance, we mean a set of resources such as onboard generation in dual units, energy storage and generation in last-mile units, and auxiliary loads. Their inherent flexibility can contribute to increasing the management possibilities of the overall net demand. The proposed scenario under study faces some of the energy concerns of periodic timetables: fast and high-power peaks in demand unknown in conventional Power Systems. The simulation results present the achieved flexibility and its potential: a decrease in peak demand by around 20% and an increase in energy recovery by 10%, lagging new investments in infrastructure. These results improve the social and economic benefits of railway transportation on the overall energy and environmental objectives while reducing energy concerns due to the increasing use of railways and boosting the sustainability of the transportation system in the coming decades.

The global energy system subsumes both extreme wealth (and waste) and extreme poverty. A minority of the global population is consuming the majority of the fossil fuel-based energy and causing global warming. While the mature industrialized economies maintain their high levels of energy consumption, the emerging economies are rapidly expanding their fossil energy systems, emulating traditional patterns of industrialization. We take a global, socio-metabolic perspective on the energy transition phases—take-off, maturation, and completion—of 142 countries between 1971 and 2015. Even within our global fossil energy system, the transition to fossil energy is still ongoing; many countries are in the process of replacing renewable energy with fossil energy. However, due to globally limited supplies and sinks, continuing the fossil energy transition is not an indefinite option. Rather than a “Big Push” for renewable energy within pockets of the fossil energy system, a sustainability transformation is required that would change far more than patterns of energy supply and use. Where this far-reaching change requires pushing back against the fossil energy system, the energy underdogs—the latecomers to the fossil energy transition—just might come out on top.

The self-consumption without surplus to the grid is one of the aspects of the new Spanish law for prosumers. Increasing the share of renewable energy sources into the grid inherently leads to several constraints. The mismatch between the energy demand and the renewable energy production, which is intermittent in nature, is one of those challenges. Storage offers the possibility to decouple demand and supply, and therefore, it adds flexibility to the electric system. This research evaluates expanding electricity self-consumption without surplus to the grid by harnessing thermal mass storage in the residential sector. The methodology is investigated by using a variable refrigerant flow air conditioner system. Because there is no option to export the excess capacity to the grid, this research proposes an approach to profiting from this surplus energy by activating structural thermal mass, which is quantified from the information acquired using a building energy model. For this purpose, an EnergyPlus model of a flat in Pamplona (Spain) was used. The optimization analysis was based on a set-point modulation control strategy. Results show that under adequate climatological circumstances, the proposed methodology can reduce the total electric energy from the grid between by 60– 80 % .

The Internet of Things (IoT) is an emerging technology and provides connectivity among physical objects with the support of 5G communication. In recent decades, there have been a lot of applications based on IoT technology for the sustainability of smart cities, such as farming, e-healthcare, education, smart homes, weather monitoring, etc. These applications communicate in a collaborative manner between embedded IoT devices and systematize daily routine tasks. In the literature, many solutions facilitate remote users to gather the observed data by accessing the stored information on the cloud network and lead to smart systems. However, most of the solutions raise significant research challenges regarding information sharing in mobile IoT networks and must be able to stabilize the performance of smart operations in terms of security and intelligence. Many solutions are based on 5G communication to support high user mobility and increase the connectivity among a huge number of IoT devices. However, such approaches lack user and data privacy against anonymous threats and incur resource costs. In this paper, we present a mobility support 5G architecture with real-time routing for sustainable smart cities that aims to decrease the loss of data against network disconnectivity and increase the reliability for 5G-based public healthcare networks. The proposed architecture firstly establishes a mutual relationship among the nodes and mobile sink with shared secret information and lightweight processing. Secondly, multi-secured levels are proposed to protect the interaction with smart transmission systems by increasing the trust threshold over the insecure channels. The conducted experiments are analyzed, and it is concluded that their performance significantly increases the information sustainability for mobile networks in terms of security and routing.