Economic Evaluation of PV Installations for Self-Consumption in Industrial Parks

This paper presents an analysis of the economic performance of photovoltaic (PV) selfconsumption systems at an industrial park in the Basque Country (north of Spain). The economic feasibility of the installations is largely dependent on self-consumption and compensation due to electricity injected into the grid, as well as the assumed evolution of the electricity prices. A sensitivity analysis is carried out for different installation sizes and different evolution scenarios concerning electricity prices. The potential for installations for shared self-consumption with dynamic and static distribution coefficients is also analyzed. The results show that medium sized installations are generally a cost effective way to reduce energy bills, while the economic performance of larger installations is more uncertain, and is largely dependent on the selling price for electricity injected into the grid. This case study found that the economic benefits of shared self-consumption between different companies are substantial, and are slightly more favorable when applying dynamic distribution factors.The work described in this article was partially funded by S-PARCS project, European Union’s Horizon 2020 research and innovation program under grant agreement Number 785134

Environmental and Economic Prioritization of Building Energy Refurbishment Strategies with Life-Cycle Approach

An increasing number of studies apply life-cycle assessment methodology to assess the impact of a new building or to prioritize between different building refurbishment strategies. Among the different hypotheses to consider during the application of this methodology, the selection of the impact indicator is critical, as this choice will completely change the interpretation of the results. This article proposes applying four indicators that allow analysing the results of a refurbishment project of a residential building with the life-cycle approach: non-renewable primary energy use reduction (NRPER), net energy ratio (NER), internal rate of return (IRR), and life-cycle payback (LC-PB). The combination of environmental and economic indicators when evaluating the results has allowed to prioritize among the different strategies defined for this case study. Furthermore, an extensive sensitivity assessment reflects the high uncertainty of some of the parameters and their high influence on the final results. To this end, new hypotheses related to the following parameters have been considered: reference service life of the building, estimated service life of material, operational energy use, conversion factor, energy price, and inflation rate. The results show that the NRPE use reduction value could vary up to −44%. The variation of the other indicators is also very relevant, reaching variation rates such as 100% in the NER, 450% in the IRR, and 300% in the LC-PB. Finally, the results allow to define the type of input or hypothesis that influences each indicator the most, which is relevant when calibrating the prioritization process for the refurbishment strategy

Multi-Physics Tool for Electrical Machine Sizing

Society is turning to electrification to reduce air pollution, increasing electric machine demand. For industrial mass production, a detailed design of one machine is usually done first, then a design of similar machines, but different ratings are reached by geometry scaling. This design process may be highly time-consuming, so, in this paper, a new sizing method is proposed to reduce this time, maintaining accuracy. It is based on magnetic flux and thermal maps, both linked with an algorithm so that the sizing process of an electrical machine can be carried out in less than one minute. The magnetic flux maps are obtained by Finite Element Analysis (FEA) and the thermal maps are obtained by analytical models based on Lumped Parameter Circuits (LPC), applying a time-efficient procedure. The proposed methodology is validated in a real case study, sizing 10 different industrial machines. Then, the accuracy of the sizing tool is validated performing the experimental test over the 10 machines. A very good agreement is achieved between the experimental results and the performances calculated by the sizing tools, as the maximum error is around 5%

How to Achieve Positive Energy Districts for Sustainable Cities: A Proposed Calculation Methodology

In this paper, a methodology for calculating the energy balance at the district level and energy performance of those districts aspiring to become a Positive Energy District (PED) is proposed. PEDs are understood as districts that achieve a positive energy balance on an annual basis by means of exporting more energy than is consumed within their limits. The main issue to standardize the concept, besides which characteristics should be considered, is that current standards to calculate an energy balance are not applied at the district level. This paper reviews the current standards and adapts them to propose an energy balance calculation methodology. Calculation of an energy balance at the district level is complex since it includes several parameters, such as which loads (or elements) should be included, which renewable energy technologies should be considered on-site production, and which primary energy factors should be used. The proposed methodology is thought to help cities at the design stage of a district and to evaluate its annual energy balance. The methodology is performed in eight steps, and all the needed assumptions that affect the calculation of the annual energy balance are discussed in each stepThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824418 (MAKING-CITY)

A GIS-Based Multicriteria Assessment for Identification of Positive Energy Districts Boundary in Cities

Discussions regarding the definition of Positive Energy Districts and the concept of a boundary are still being actively held. Even though there are certain initiatives working on the boundary limitations for PEDs, there is no methodology or tool developed for selecting peculiar spaces for future PED implementations. The paper focuses on a flexible GIS-based Multicriteria assessment method that identifies the most suitable areas to reach an annual positive non-renewable energy balance. For that purpose, a GIS-based tool is developed to indicate the boundary from an energy perspective harmonized with urban design and land-use planning. The method emphasizes evaluation through economic, social, political, legal, environmental, and technical criteria, and the results present the suitability of areas at macro and micro scales. The current study outlines macro scale analyses in six European cities that represent Follower Cities under the MAKING-CITY H2020 project. Further research will be conducted for micro-scale analyses and the outcomes will pursue a technology selection process.This research was funded by the EU H2020 Programme under grant agreement n◦82441

Methodology for integrated modelling and impact assessment of city energy system scenarios

Cities are ought to play a key role in the energy transition to a low carbon society as they concentrate more than half of the world's population and are responsible for about 67% primary energy consumption and around 70% of the energy-related CO2 emissions. To achieve the agreed climate targets, efficient urban planning is a must. Tools and methods have risen to model different aspects of the energy performance of urban areas. Nevertheless, addressing the complexity of a city energy system is a great challenge and new integrated tools and methods are still needed. This paper presents a methodology for integrated city energy modelling and assessment, from the characterization of the city's current energy performance to the development and assessment of future scenarios. Energy characterization is based on the combination of bottom-up approaches with top-down data to establish the city's energy baseline. This baseline integrates bottom-up results from a GIS based model which is used to characterize the city's building stock energy performance, while available information on the vehicle stock is used to model the mobility sector. Scenarios are developed from this baseline and assessed through a multi-criteria impact assessment model. A simplified case study is carried out for the city of Valencia (Spain) to demonstrate the suggested methodology, and results are shown for three different scenarios: one focused on the building sector, one on transport, and one combining measures in both sectors. The transport-focused scenario demonstrates to be the most favourable in terms of energy savings and emissions reductions. The application of the proposed method is intended to support the development of strategies and plans for energy transition at city level. The main challenges for its application in cities are data availability at urban level, the uncertainty related to modelling the transport sector, and the unavailability of adapted I/O tables at city scale to assess socioeconomic impacts

Sensors Data Analysis in Supervisory Control and Data Acquisition (SCADA) Systems to Foresee Failures with an Undetermined Origin

This paper presents the design and implementation of a supervisory control and data acquisition (SCADA) system for automatic fault detection. The proposed system offers advantages in three areas: the prognostic capacity for preventive and predictive maintenance, improvement in the quality of the machined product and a reduction in breakdown times. The complementary technologies, the Industrial Internet of Things (IIoT) and various machine learning (ML) techniques, are employed with SCADA systems to obtain the objectives. The analysis of different data sources and the replacement of specific digital sensors with analog sensors improve the prognostic capacity for the detection of faults with an undetermined origin. Also presented is an anomaly detection algorithm to foresee failures and to recognize their occurrence even when they do not register as alarms or events. The improvement in machine availability after the implementation of the novel system guarantees the accomplishment of the proposed objectives.This work was supported partially by the Basque Government through project IT1207-19, and by the MCIU/MINECO through RTI2018-094902-B-C21/RTI2018-094902-B-C22 (MCIU/AEI/FEDER, UE). The authors would like to thank Intenance Company for its collaboration and help

A Holistic and Interoperable Approach towards the Implementation of Services for the Digital Transformation of Smart Cities: The Case of Vitoria-Gasteiz (Spain)

Cities in the 21st century play a major role in the sustainability and climate impact reduction challenges set by the European agenda. As the population of cities grows and their environmental impact becomes more evident, the European strategy aims to reduce greenhouse gas emissions—the main cause of climate change. Measures to reduce the impact of climate change include reducing energy consumption, improving mobility, harnessing resources and renewable energies, integrating nature-based solutions and efficiently managing infrastructure. The monitoring and control of all this activity is essential for its proper functioning. In this context, Information and Communication Technology (ICT) plays a key role in the digitisation, monitoring, and managing of these different verticals. Urban data platforms support cities on extracting Key Performance Indicators (KPI) in their efforts to make better decisions. Cities must be transformed by applying efficient urban planning measures and taking into account not only technological aspects, but also by applying a holistic vision in building solutions where citizens are at the centre. In addition, standardisation of platforms where applications are integrated as one is necessary. This requires interoperability between different verticals. This article presents the information platform developed for the city of Vitoria-Gasteiz in Spain. The platform is based on the UNE 178104 standard to provide a holistic architecture that integrates information from the different urban planning measures implemented in the city. The platform was constructed in the context of the SmartEnCity project following the urban transformation strategy established by the city. The article presents the value-added solutions implemented in the platform. These solutions have been developed by applying co-creation techniques in which stakeholders have been involved throughout the process. The platform proposes a step forward towards standardization, harmonises the integration of data from multiple vertical, provides interoperability between services, and simplifies scalability and replicability due to its microservice architecture.This work has been supported by the Department of Education, Universities, and Research of the Basque Government under the projects Ikerketa Taldeak (Software and Systems Engineering research group of Mondragon Unibertsitatea) and the European Union’s Horizon 2020 research and innovation programme under the project SmartEnCity with the grant agreement no. 691883

DC-Link Voltage and Catenary Current Sensors Fault Reconstruction for Railway Traction Drives

Due to the importance of sensors in control strategy and safety, early detection of faults in sensors has become a key point to improve the availability of railway traction drives. The presented sensor fault reconstruction is based on sliding mode observers and equivalent injection signals, and it allows detecting defective sensors and isolating faults. Moreover, the severity of faults is provided. The proposed on-board fault reconstruction has been validated in a hardware-in-the-loop platform, composed of a real-time simulator and a commercial traction control unit for a tram. Low computational resources, robustness to measurement noise, and easiness to tune are the main requirements for industrial acceptance. As railway applications are not safety-critical systems, compared to aerospace applications, a fault evaluation procedure is proposed, since there is enough time to perform diagnostic tasks. This procedure analyses the fault reconstruction in the steady state, delaying the decision-making in some seconds, but minimising false detections

A Hybrid Sensor Fault Diagnosis for Maintenance in Railway Traction Drives

Due to the importance of sensors in railway traction drives availability, sensor fault diagnosis has become a key point in order tomove frompreventivemaintenance to condition-basedmaintenance. Most research works are limited to sensor fault detection and isolation, but only a few of them analyze the types of sensor faults, such as offset or gain, with the aim of reconfiguring the sensor in order to implement a fault tolerant system. This article is based on a fusion of model-based and data-driven techniques. First, an observer-based approach, using a Sliding Mode observer, is utilized for sensor fault reconstruction in real time. Then, once the fault is detected, a timewindowof sensormeasurements and sensor fault reconstruction is sent to the remotemaintenance center for fault evaluation. Finally, an offline processing is carried out to discriminate between gain and offset sensor faults, in order to get a maintenance decision-making to reconfigure the sensor during the next train stop. Fault classification is done by means of histograms and statistics. The technique here proposed is applied to the DC-link voltage sensor in a railway traction drive and is validated in a hardware-in-the-loop platform