Browsing by Author "Pereira, Lucas"
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- Energy monitoring in the wild: platform development and lessons learned from a real-world demonstratorPublication . Quintal, Filipe; Garigali, Daniel; Vasconcelos, Dino; Cavaleiro, Jonathan; Santos, Wilson; Pereira, LucasThis paper presents the development and evaluation of EnnerSpectrum, a platform for electricity monitoring. The development was motivated by a gap between academic, fully custom made monitoring solutions and commercial proprietary monitoring approaches. EnnerSpectrum is composed of two main entities, the back end, and the Gateway. The back end is a server comprised of flexible entities that can be configured to different monitoring scenarios. The Gateway interacts with equipment at a site that cannot interact directly with the back end. The paper presents the architecture and configuration of EnnerSpectrum for a long-term case study with 13 prosumers of electricity for approximately 36 months. During this period, the proposed system was able to adapt to several building and monitoring conditions while acquiring 95% of all the available consumption data. To finalize, the paper presents a set of lessons learned from running such a long-term study in the real world.
- A global monitoring system for electricity consumption and production of household roof-top PV systems in MadeiraPublication . Torabi, Roham; Rodrigues, Sandy; Cafôfo, Nuno; Pereira, Lucas; Quintal, Filipe; Nunes, Nuno; Dias, Fernando MorgadoThis paper describes recent work on the development of a wireless-based remote monitoring system for household energy consumption and generation in Madeira Island, Portugal. It contains three different main sections: (1) a monitoring system for consumed and produced energy of residencies equipped with photovoltaic (PV) systems, (2) developing a tool to predict the electricity production, (3) and proposing a solution to detect the PV system malfunctions. With the later tool, the user (owner) or the energy management system can monitor its own PV system and make an efficient schedule use of electricity at the consumption side. In addition, currently, the owners of PV systems are notified about a failure in the system only when they receive the bill, whereas using the proposed method conveniently would notify owners prior to bill issue. The artificial neural network was employed as a tool together with the hardware-based monitoring system which allows a daily analysis of the performance of the system. The comparison of the predicted value of the produced electricity with the actual production for each day shows the validity of the method.
- HomeTree: an art inspired mobile eco-feedback visualizationPublication . Quintal, Filipe; Nisi, Valentina; Nunes, Nuno; Barreto, Mary; Pereira, LucasThis paper presents HomeTree a prototype of an art-inspired mobile eco feedback system. The system is implemented on a tablet PC and relies on a non intrusive energy-monitoring infrastructure to access consumption and power event information. Our prototype addresses an important problem in eco feedback, which is the fact that users loose interest about their energy consump tion after a period of several weeks. To accomplish this HomeTree implements a dual visualization strategy. Initially HomeTree presents users with a screensa ver that shows energy consumption mapped in a dynamic illustration of the lo cal forest. Through this strategy we leverage the emotional connection between the short-term energy consumption and the long-term effects on nature through the local depicted landscape. In a second mode of operation users can interact with HomeTree directly by checking the historical records of their consumption data, and check which days or weeks they have reduced or increased consump tion. Furthermore a comparison with a more objective baseline, such as the city of Funchal energy consumption is provided, in order to give users a sense of the level of their consumption in a wider context.
- Implementation Strategy of Convolution Neural Networks on Field Programmable Gate Arrays for Appliance Classification Using the Voltage and Current (V-I) TrajectoryPublication . Baptista, Darío; Mostafa, Sheikh Shanawaz; Pereira, Lucas; Sousa, Leonel; Dias, Fernando MorgadoSpecific information about types of appliances and their use in a specific time window could help determining in details the electrical energy consumption information. However, conventional main power meters fail to provide any specific information. One of the best ways to solve these problems is through non-intrusive load monitoring, which is cheaper and easier to implement than other methods. However, developing a classifier for deducing what kind of appliances are used at home is a difficult assignment, because the system should identify the appliance as fast as possible with a higher degree of certainty. To achieve all these requirements, a convolution neural network implemented on hardware was used to identify the appliance through the voltage and current (V-I) trajectory. For the implementation on hardware, a field programmable gate array (FPGA) was used to exploit processing parallelism in order to achieve optimal performance. To validate the design, a publicly available Plug Load Appliance Identification Dataset (PLAID), constituted by 11 different appliances, has been used. The overall average F-score achieved using this classifier is 78.16% for the PLAID 1 dataset. The convolution neural network implemented on hardware has a processing time of approximately 5.7 ms and a power consumption of 1.868 W.
- MyTukxi: low cost smart charging for small scale EVsPublication . Quintal, Filipe; Scuri, Sabrina; Barreto, Mary; Pereira, Lucas; Vasconcelos, Dino; Pestana, DanielAs the electrification of the transportation sector grows the electric grid must handle the new load resulting from electric vehicles (EV) charging. The integration of this new load in the grid has been subject to work in the smart-charging research field, however, while normal-sized EVs often offer chargers or other functions that support smart-charging, smaller EVs do not, which could be problem atic. Especially considering that the consumption of small EV when aggregated can be significant. This article presents the motivation and development behind the development of MyTukxi, a hardware and software system that aims at implementing smart-charging algorithms for low consuming electric vehicles (EV), interacting with drivers to compensate for the lack of charging control in such vehicles.
- The acceptance of energy monitoring technologies: the case of local prosumersPublication . Barreto, Mary; Pereira, Lucas; Quintal, FilipeWith transformations happening in the electricity sector, we need to ensure consumers have access to updated and correct information to accompany such changes. Consumers need to understand technologies available to them but also, learn how to use them to optimize their personal investment in such types of equipment. In this paper, we explore how a group of local pro sumers has adopted energy monitoring technologies, their day to-day strategies, and expectations when handling such systems. We studied 11 prosumers and the technologies they have used for three years, evaluated their satisfaction with the feedback provided and analyzed how a more modern visualization of their energy practices was introduced and adopted into their daily lives. We conducted interviews and questionnaires to evaluate their engagement with these tools. This initial work suggests this particular group of users have already a high level of knowledge about their systems, and as a result have integrated these into their routines. However, more support would be needed from other local actors to help them reach more benefits and as such, more satisfaction as consumers. We conclude by reflecting on barriers that need to be addressed to increase user satisfaction with these systems.
- Towards using Low-Cost Opportunistic Energy Sensing for Promoting Energy ConservationPublication . Nunes, Nuno J.; Pereira, Lucas; Nisi, ValentinaThis position paper discusses how to leverage low-cost energy sensing to opportunistically develop activity-based approaches to energy conservation. Based on our extensive experience developing low-cost sensing infrastructures and long term deployment of ecofeedback systems, we discuss the possibility of unobtrusively inferring domestic activities from the overall aggregated energy consumption of households. We then postulate how the combination of this information with daily household activities could lead to more effective and meaningful ways to re-aggregate residential energy consumption for the purpose of ecofeedback. Here we briefly present a practical approach towards this new research direction that leverages HCI related methods, in particular using the day reconstruction method to provide semi-supervised approaches for automatic detection of household activities.
- Understanding families’ motivations for sustainable behaviorsPublication . Barreto, Mary L.; Szóstek, Agnieszka; Karapanos, Evangelos; Nunes, Nuno J.; Pereira, Lucas; Quintal, FilipeWhile interest in eco-feedback technologies has peaked over the last decade, research increasingly high lights that simply providing information to individuals regarding their consumption behaviors does not guarantee behavior change. This has lead to an increasing body of work that attempts to characterize individuals’ latent motivations that drive sustainable behaviors. With this paper we aim at expanding this body of work by analyzing such motivations in the context of families. We report findings from inter views with 15 families who used an eco-feedback interface over a period of 2 years. Our study reveals that motivations for sustainable behavior were not only rooted in individuals’ environmental concerns and need for expense management but they also regarded: (i) individuals’ and families’ need for a sense of control and security, (ii) parents’ self-perceived responsibility of their role as parents and (iii) the percep tion of individual as well as family identity. We argue that in order for eco-feedback technologies to attain long-lasting behavioral changes in the domestic environment they need to address basic family needs that go beyond individual ideals of pro-environmental behavior
- Understanding the challenges behind electric vehicle usage by drivers: a case study in the Madeira Autonomous RegionPublication . Barros, Luísa; Barreto, Mary; Pereira, LucasElectric Vehicles (EV) adoption targets have been set by govern ments from countries throughout Europe, related to the European goals, for the decarbonization of the road transport sector. The change for electric vehicle technology can be challenging to EV users for several reasons such as battery autonomy, time to charge the vehicle, and the different driving conditions. The work in this paper aims to study how users from Madeira and Porto Santo is lands deal with the challenges of EV usage. Furthermore, this paper also studies the role of the orography in the Regenerative Braking System technology integrated into electric vehicles. To assess such information, an online questionnaire was prepared and sent out to the electric vehicle community of both islands. The main results of this study show drivers’ preference to charge the vehicles at their household and that users are satisfied with the vehicle’s technology. Also, users’ battery range anxiety did not seem to have a significant impact. Moreover, from the drivers’ point of view, there is still the need to study the role of orography, while using the regenerative braking system.
- Understanding the limitations of eco-feedback: a one-year long-term studyPublication . Pereira, Lucas; Quintal, Filipe; Barreto, Mary; Nunes, Nuno J.For the last couple of decades the world has been witnessing a change in habits of energy consumption in domestic environments, with elec tricity emerging as the main source of energy consumed. The effects of these changes in our eco-system are hard to assess, therefore encouraging researchers from different fields to conduct studies with the goal of understanding and im proving perceptions and behaviors regarding household energy consumption. While several of these studies report success in increasing awareness, most of them are limited to short periods of time, thus resulting in a reduced knowledge of how householders will behave in the long-term. In this paper we attempt to reduce this gap presenting a long-term study on household electricity consump tion. We deployed a real-time non-intrusive energy monitoring and eco feedback system in 12 families during 52 weeks. Results show an increased awareness regarding electricity consumption despite a significant decrease in interactions with the eco-feedback system over time. We conclude that after one year of deployment of eco-feedback it was not possible to see any significant increase or decrease in the household consumption. Our results also confirm that consumption is tightly coupled with independent variables like the house hold size and the income-level of the families.