Smart Cities

In this work, two segmentation techniques for photovoltaic (PV) solar panels are explored: filtering by area and the second to the method of active contours level-set method (ACM LS). Tuning these techniques enables the contours of the solar panels to be obtained. Once these contours are established, morphological operations are used to refine the obtained edges and the Hough transform technique is used to find the main lines in the image. The vertices are then found from the possible intersections between the lines. Finally, the vertices are brought to the desired position at scale according to the reference of the PV panels projection transformations. The extraction of the region of interest is evaluated from the Dice similarity coefficient (DSC), Intersection over Union (IoU), and recall segmentation metrics.

With the increase of population living in urban areas, many transportation-related problems have grown very rapidly. Pollution causes many inhabitants health problems. A major concern for the International Community is pollution, which causes many inhabitants health problems. Accordingly, and under the risk of fines, countries are required to reduce noise and air pollutants. As a way to do so, road restrictions policies are applied in urban areas. Evaluating objectively the benefits of this type of measures is important to asses their real impact. In this work, we analyze the application of Madrid Central (MC), which is a set of road traffic limitation measures applied in the downtown of Madrid (Spain), by using smart city tools. According to our results, MC significantly reduces the nitrogen dioxide (\(NO_2\)) concentration in the air and the levels of noise in Madrid, while not arising any border effect.

Innovative, low-cost, environmentally friendly and renewable resource-based solutions are emerging to meet growing global energy demand. Hydroelectric technology is quite old and mature. Despite its importance, it is associated with large plants, with environmental impact. On contrary, small-scale systems, called pico-hydro systems (up to 5 kW) are not yet explored. Anyway, the exploration of pico-hydro systems has been increasing consistently, from the first off-grid applications in remote places to distributed generation, with the injection of the generated energy in the main grid or microgrids. Very recently, there have been advances in grid connection of these small-scale systems, using off-the-shelf components. Indeed, pico-hydro systems can be connected to the grid using off-the-shelf components, namely photovoltaic inverters. Thus, grid-connected pico-hydro systems have gained an enormous potential in distributed production. However, in situations of over-power, or whenever the generator is under no load, there is a need for effective over-voltage protection, unlike photovoltaic systems. The goal of this paper is to propose an over-voltage protection circuit, designed to ensure the integration of low-power pico-hydro systems connected to the grid using conventional photovoltaic microinverters. Extensive tests were performed on an experimental platform using three microinverters easily found on the market and a low power generator (300 W) developed for small wind turbines. The experimental results, demonstrated the performance of the proposed over-voltage protection circuit in four different situations, presented in this work, thus avoiding irreversible damages of generators and microinverters, in the context of the above described grid connection approach.

One of the most important challenges to mitigate global climate change is to move towards replacing petroleum-based energy sources. In this idea, non-conventional renewable energy sources such as photovoltaic (PV) solar and wind power are the most used worldwide. In the case of the massification of PV solar generation systems due to its low cost, it has resulted in the use of large-scale supervision techniques that allow a quick and effective determination of the health status of its main components. This study, performs an analysis of the performance of different low-cost cameras for thermography. The analysis compares the accuracy of the thermal images obtained and the error is quantified by means of an image dispersion analysis in each of them. Three-dimensional meshes and contours figures are also made to determine the temperature of a faulty cell. The study shows that the performance obtained with low-cost cameras presents errors below 10% in costs and less than 0.015 USD/pixel.

This paper presents an hybrid energy storage system for the integration of renewable-based power plants in power networks. A hybrid energy storage system is defined as that able to integrate and maximize the contribution of a heterogeneous grouping of storage systems. The services which this hybrid solution is able to perform are identified and then related to a specific storage technology which have the best potential to solve the issues created by the intermittent renewable generation. The presented solution combines three different storage technologies, a lead-acid battery pack, a flywheel and a set of supercapacitors. The description of the system is complemented by a study case, for the performance analysis of the set of supercapacitors.

IoT (Internet of Things) refers to an integration concept of different communication systems used for connecting heterogeneous devices with constraints on processing, storage capabilities and power consumption to the Internet, with the purpose of data collecting for analysis and decision making about the measurements of data collected. This new paradigm can be applied in different fields to wirelessly measure variables through mobile devices, laptops and wireless devices having in mind restrictions in terms of battery lifetime, capacity, and cost. This paper describes the implementation of a flexible and low-cost monitoring and data collecting platform using sensors based on open hardware such as Arduino, interconnected through a LoRa network and a cloud-based data storage system developed using open source code. The main objective is to quickly collect different types of variables based on a flexible monitoring and collecting platform adaptable to different types of sensors which could be used in both rural and urban areas in applications that require long-range transmission and low energy consumption. In the future, research on the analysis of performance and improvement solutions will be carried out, as well as the use of other types of devices and protocols in order to compare performance and expand the field of implementation of the proposed platform.

Sustainable mobility is a very relevant approach within the novel paradigm of smart cities. This article presents an analysis of sustainable mobility initiatives recently developed in the public transportation of Montevideo, Uruguay. The case study is analyzed considering the main concepts from related works and well-known quantitative and qualitative indicators. Three initiatives are studied: electric bus, public bicycles, and electric scooters. They constitutes novel and promising ways for public transportation in the city. The reported results for each mean of transportation suggest that the first initiatives focus on specific sectors of the population and should be improved in order to extend their accessibility and affordability. Specific recommendations are formulated to develop and improve sustainable mobility in Montevideo.

As part of the energy sustainability program intended to reduce the carbon footprint of the National Polytechnic Institute, solar photovoltaic electricity generation systems along with electricity consumption reduction actions have been implemented in three entities. These actions were implemented in accordance with recommendations defined by environmental committees and considering the diagnoses of baseline energy consumption. This work reports the quantification of the savings generated by the implementation of operational measures of technological substitution and solar photovoltaic electric power generation. The foregoing includes a process of identification of the baseline of electricity consumption, the replacement of infrastructure and equipment of high energy consumption with equipment of low consumption and environmental impact, as well as the installation of technology for the generation of electrical energy by renewable sources. Three solar photovoltaic systems were installed, replacement of luminaires, replacement of hand dryers and replacement of obsolete air conditioning equipment. It was found that on average the reduction in monthly electricity consumption is 31% with the consequent economic savings. Regarding the reduction of the carbon footprint, an impact on non-generation of tonnes of CO2 equivalent amount 37% quantified with reference to the generation before the implementation of the operational and power generation measures. This is equivalent to not having generated 18.31 tCO2e per month. This work describes the activities carried out and the methodology used to calculate the savings found, both in energy consumption, economic, and in reducing the carbon footprint.

Microgrids are an alternative approach for the supply of energy integrating decentralized power sources, electrical loads, energy storage, and management in a local grid. The system has the capability of power control and energy management using communications’ network between all devices, and is known as smart microgrid. This paper presents the implementation of a smart microgrid in the Silk House, a museum dedicated to dissemination of science located in Bragança, Portugal. It was funded by the Foundation for Science and Technology of Portugal under the SilkHouse Project. The goal is to transform the House of Silk in a self-sustainable museum contributing to the dissemination of renewable sources and new technologies for future buildings in smart cities. This work presents the context and requirements for the microgrid and describes the implementation of the renewable sources (photovoltaic and pico-hydro) and the SMA Flexible Storage System based on Sunny Island and Sunny Home Manager. This work also presents and analysis the first operating results since the start of operation at the end of July 2019.

Within this paper it is proposed the design and development of an instrument with extended capabilities for photovoltaic (PV) devices I/V tracing. Commercial instruments that measure I-V curves from PV devices are suitable for a wide range of applications. However, more specific research and measurements require developing customized equipment. Custom-made development provides flexibility, and allows to implement tailored algorithms and to have accurate control of obtained information. Full control offers better flexibility for testing and extends the measurement possibilities. Designed I-V tester is capable to measure low voltages and manages very low resistance load to provide short circuit current values with voltages close to zero.

Forecasting the day-ahead electricity load is beneficial for both suppliers and consumers. The reduction of electricity waste and the rational dispatch of electric generator units can be significantly improved with accurate load forecasts. This article is focused on studying and developing computational intelligence techniques for electricity load forecasting. Several models are developed to forecast the electricity load of the next hour using real data from an industrial pole in Spain. Feature selection and feature extraction are performed to reduce overfitting and therefore achieve better models, reducing the training time of the developed methods. The best of the implemented models is optimized using grid search strategies on hyperparameter space. Then, twenty four different instances of the optimal model are trained to forecast the next twenty four hours. Considering the computational complexity of the applied techniques, they are developed and evaluated on the computational platform of the National Supercomputing Center (Cluster-UY), Uruguay. Standard performance metrics are applied to evaluate the proposed models. The main results indicate that the best model based on ExtraTreesRegressor obtained has a mean absolute percentage error of 2.55% on day ahead hourly forecast which is a promising result.

In this work, we present the study of seawater desalination potential using the energy surpluses of a microgrid based on renewable energies and a thermosolar absorption cooling system, installed in the isolated community of Puertecitos, Mexico and its primary school, respectively. Given the profile of electricity demand of the community in winter and the non-need for air conditioning, both systems can be used for the desalination of seawater, a resource greatly needed in the region because of the scarcity that is presented. Using the software TRNSYS and Aspen Plus, the simulation of the generating systems was carried out, activating a multiple-effect seawater desalination system during a typical week of February with measured data of electrical consumption. The results show that, with the energy available from both systems, it is possible to desalinate 2,500 kg/day of water with a thermal consumption of 25 kW, during 6 h daily operation. The electrical energy supplied by the microgrid contributes four times more to the desalination of water than the thermal solar field. With this production, it is possible to satisfy the basic requirements of hygiene, hydration and food for 25 people.

The increase in the penetration of renewable generation sources is fundamental in Smart Cities. But these renewable sources can be integrated with distributed electrical storage and intelligence for the management of all assets through electric microgrids. Therefore, these new generation and consumption environments will be present in the Smart City. In this sense, this paper presents one of the most versatile and interesting electric microgrid that exists today, specifically the microgrid of the Center for the Development of Renewable Energies (CEDER) located in Soria (Spain).

The implicit difficulties (resources and intermittent generation) of renewable energies prevent their insertion with greater security and reliability in electricity networks. However, as the priority of favoring environmental issues and represent one of the main axes of the electricity sector, it is essential to make efforts that characterize the behavior of the effective production of photovoltaic systems in real applications. In this way, the objective of this article is to propose a methodology where the monthly profile of future facilities is estimated. To this end, the received solar radiation (based on the Gamma probability distribution) is modeled along with the generation of seven photovoltaic arrays of different technology, connected to the microgrid of the Center for the Development of Renewable Energies (CEDER), belonging to the Center of Energy, Environmental and Technological Research (CIEMAT), located in Soria, Spain. The measurement of the solar resource was made with a Baseline Surface Radiation Network, and the injection of photovoltaic power to the microgrid was acquired with the help of smart meters. The verification of the procedure was carried out with simulations in Matlab and the statistical analyzes were confirmed with the JMP software. The results may be helpful in sizing a backup model and will collaborate in the proper management of the case study energy.

This article presents a study of the public transportation system in Montevideo, Uruguay, following a data science approach. More than 20 million records from the Intelligent Transportation System (ITS) are analyzed in order to characterize mobility in the city. Several useful pieces of information are obtained through data analysis, related to tickets sold, patterns of smart card utilization, most used bus lines and stops, and socioeconomic insights about passengers behavior. Practical case studies are also presented: anomaly detection in space and time, and a study of potential safety hazards due to reckless driving. The work reported in this article constitutes one of the first steps towards using data from the ITS in Montevideo to understand mobility in the city.

In the last years, the concept of Smart City has moved from a predominantly technological perspective towards a more human based approach, where terms as sustainability and inclusiveness are presents and are part of a new concept referred as Human Smart Cities. In this context, the mobility of people and services represents one of the major challenges that cities must solve. Therefore, urban mobility policies must integrate new mobility needs as well as minimize the impact transportation has on the environment and the quality of life in our cities. Urban areas need to develop new sustainable urban mobility systems integrating traffic state, transport users demand, transport capacity providers, etc. These requirements involve the use of new techniques and methods as Big Data and IoT, but it is necessary to include a social component to ensure social inclusion and inclusiveness, sustainability and inclusiveness. In this paper, we describe some challenges regarding barriers to access new mobility systems and their relevant information. Therefore, we propose a smart bus stop taking into account cultural and socioeconomics characteristics of the transport users employing as a basis the access to information systems.

Massive public infrastructure is usually structured into hierarchical levels, where different technologies handle different scales of requirements allowing most efficient and scalable implementations. In opposition to the aforementioned architecture, the public transport system in Montevideo (Uruguay) uses a single/flat level, with buses as the only means. This work explores the performance benefits and the cost feasibility of a new hierarchically segmented metropolitan trunk network for the public system in Montevideo, a problem that is tackled through combinatorial optimization approaches. The reference structure assumes light railway trams (LRTs) are used to massively transfer passengers between remote points of the city, while buses are reassigned as feeders of the new backbone in the network. The real-world example integrates demands information, realistic travel and waiting times as well as standard deployment costs. Results show that this new structure is economically competitive and significantly better in terms of quality of service.

The paper analyses the alternatives for the power supply of a Hyperloop type railway transport. The particular case of the technology of the Spanish company ZELEROS is studied. Specifications related to both a first prototype and a commercial system are presented and the power supply requirements analysed. After considering different alternatives, energy storage based on supercapacitors is obtained as a feasible and competitive solution for the power supply of this application due to the power/energy ratio and the cycles capability. A preliminary design methodology for the energy storage requirements is presented in the paper. Once selected the type of linear motor, the power supply scheme is presented, based on a motor-side power electronic converter and a DC/DC converter which connects to the energy storage devices. An additional low power grid-tie converter for the recharge of the energy storage system is also used. Different track sections are defined, connected to the power electronic converter through corresponding switches, being supplied sequentially when the capsule presence is detected along the track. The number of track sections depends on the limitations of voltage and current, defined by the power electronic converter selected and particular issues like current density selection and the evaluation of skin effect are very important for this application.

The major environmental pressures associated with urban centers are noise and air pollution, making its monitoring of utmost importance to evaluate and reduce the exposure of the population to these environmental risk factors. In this study, continuous monitoring of sound pressure levels, ozone, nitric oxides, carbon monoxide concentrations, and local meteorological variables were performed during the winter and spring months of 2019 at the Mirandela industrial park. Ozone and nitric oxide levels followed a characteristic daily cycle, consistent with the diurnal evolution of radiation and the intensity of the main air pollution sources prevailing in the local. Hourly ozone levels were highest in July, reaching magnitudes of approximately 80 ppb. Ozone concentrations in the industrial park had a strong local influence, mainly related to the local nitric oxides emissions. The results also showed high influence of meteorological parameters on ozone production, especially during daytime. Regarding noise, typical daily and weekly patterns were observed, and sound pressure levels were compatible with those defined for mixed zones according to the Portuguese General Noise Regulation.

The number of electric vehicles is expected to increase exponentially in the next decade. This represents a huge potential for grid support, such as energy storage in their batteries, with advantages for grid operators and for customers. For this purpose, flexible power interfaces are required. This paper presents a simulation of a bidirectional single-phase power interface between an electric vehicle battery and the grid. The proposed system is fully simulated and counts with features such as vehicle-to-grid, vehicle-to-home and grid-to-vehicle. All power flow and the controllers for these modes of operation are described in detail. The simulation was developed in a Software-in-the-Loop scheme to facilitate a future physical implementation with a Hardware-in-the-Loop platform. The proposed system was extensively tested via simulation, the results proving the system is stable, able to change operation modes smoothly and definition of the exchanged active and reactive powers.