Recently my work was published in conference like IFIP Interact, ICT4S, IFIP SustainIT, IEEE SmartGridComm, and ACM BuildSys. Below is an up-to-date listing of my publications. Check my Google Scholar and ORCID profiles for additional information.
Lucas Pereira
ITI, LARSyS, Técnico Lisboa
&
prsma.com
Publications
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Co-optimizing Energy Storage for Prosumers Using Convex Relaxations
Ultrasonic Waste Monitoring in the Future Industrial Kitchen
Abstract
This paper presents the initial results of ultrasonic waste monitoring during the operation of one industrial kitchen. Undifferentiated, paper and plastic waste bins were monitored, and a heuristic-based waste disposal event detector was developed and evaluated. The results show that it is possible to identify disposal events in the three waste bins. Furthermore, it is also possible to determine when paper and plastic are compressed to make additional room.
Poster
Future Industrial Kitchen: Challenges and Opportunities
Abstract
Large amounts of electricity, water, and food are used every day in Industrial Kitchens (IK). Still, very little attention has been devoted by the research community to this potential source of resource over-consumption. This abstract paper builds on the deployment of sensing technology in three IKs to present the main challenges and potential research directions towards more sustainable IKs.
Presentation Slides
Electricity Consumption Data Sets: Pitfalls and Opportunities
Abstract
Real-world data sets are crucial to develop and test signal processing and machine learning algorithms to solve energy-related problems.
Their scope and data resolution is, however, often limited to the means required to fulfill the experimenters’ objectives and moreover governed by personal experience, budgetary and time constraints, and the availability of equipment.
As a result, numerous differences between data sets can be observed, e.g., regarding their sampling rates, the number of sensors deployed, their amplitude resolutions, storage formats, or the availability and extent of ground-truth annotations.
This heterogeneity poses a significant problem for researchers intending to comparatively use data sets because of the required data conversion, re-sampling, and adaptation steps.
In short, there is a lack of widely agreed best practices for designing, deploying, and operating electrical data collection systems.
We address this limitation by dissecting the collection methodologies used in existing data sets.
By offering recommendations for data collection, data storage, and data provision, we intend to foster the creation of data sets with increased usability and comparability, and thus a greater benefit to the community.
Presentation Slides
On the Value Proposition of Battery Energy Storage in Self-Consumption Only Scenarios: A Case-Study in Madeira Island
Abstract
This paper presents a Techno-Economic assessment of the value proposition of introducing battery energy storage in the Madeira Island electric grid, where only micro-production for self-consumption is currently allowed. The evaluation was conducted against two local micro-producers using one year of energy consumption and solar PV production measurements. The assessments considered three different pairs of battery capacity/inverter size, and the outputs analyzed considering self-consumption, self-sufficiency, and energy costs. The results show that despite the increase in self-consumption and self-sufficiency, the value proposition of battery energy storage is still considerably low even considering a massive decrease in the costs of storage. Furthermore, the results also suggest that given the small size of the solar PV installations, inverters with half the size of the installed PV capacity represent the best value for money.
Poster
NILMPEds: A Performance Evaluation Dataset for Event Detection Algorithms in Non-Intrusive Load Monitoring
dsCleaner: A Python Library to Clean, Preprocess and Convert Non-Intrusive Load Monitoring Datasets
The Acceptance of Energy Monitoring Technologies – The Case of Local Prosumers
Conference
Proceedings of the 6th International Conference on ICT4S, Lappeenranta, Finland
Publication year: 2019
Energy Storage in Madeira, Portugal: Co-optimizing for Arbitrage, Self-Sufficiency, Peak Shaving and Energy Backup
MyTukxi: Low Cost Smart Charging for Small Scale EVs
Extended Abstract
CHI’19 Extended Abstracts, May 4–9, 2019, Glasgow, Scotland UK
Publication year: 2019
A Mouse (H)Over a Hotspot Survey: An Exploration of Patterns of Hesitation through Cursor Movement Metrics
Extended Abstract
CHI’19 Extended Abstracts, May 4–9, 2019, Glasgow, Scotland UK
Publication year: 2019
Abstract:
This paper presents the results of an empirical exploration of 10 cursor movement metrics designed to measure respondent hesitation in online surveys. As a use case, this work considers an online survey aimed at exploring how people gauge the electricity consumption of domestic appliances. The cursor metrics were derived computationally from the mouse trajectories when rating the consumption of each appliance and analyzed using Multidimensional Scaling, Jenks Natural Breaks, and the Jaccard Similarity Index techniques. The results show that despite the fact that the metrics measure different aspects of the mouse trajectories, there is an agreement with respect to the appliances that generated higher levels of hesitation. The paper concludes with an outline of future work that should be carried out in order to further understand how cursor trajectories can be used to measure respondent hesitation.
Poster:
Reproducible Research:
Data and scripts will be added soon.
A global monitoring system for electricity consumption and production of household roof-top PV systems in Madeira
Journal
Neural Computing and Applications, Oct. 2018; doi: 10.1007/s00521-018-3832-3
Publication year: 2018
Highlights of ES2DE and IWOBI 2017: extended versions of selected best papers
Implementation Strategy of Convolution Neural Networks on Field Programmable Gate Arrays for Appliance Classification Using the Voltage and Current (V-I) Trajectory
On the Challenges of Charging Electric Vehicles in Domestic Environments
Poster Abstract
Proceedings of ACM e-Energy 2018, Pages 225-226. Karlsruhe, Germany
Publication year: 2018
Madeira Pilot User Acceptance Report of the Initial Smart Meter Deployment
Technical Report
H2020 SMILE, EUROPEAN COMMISSION, Funchal, Portugal, Technical report 4.4, Jun. 2018.
Publication year: 2018
Data Collection, Modelling, Simulation and Decision
Technical Report
H2020 SMILE, EUROPEAN COMMISSION, Funchal, Portugal, Technical report 4.3, Jun. 2018
Publication year: 2018
Madeira Pilot Infrastructure Preparation and Kick-off
Technical Report
H2020 SMILE, EUROPEAN COMMISSION, Funchal, Portugal, Technical report 4.2, Jun. 2018
Publication year: 2018
Madeira Pilot Case Study Specification and Assessment
Technical Report
H2020 SMILE, EUROPEAN COMMISSION, Funchal, Portugal, Technical report 4.1, Oct. 2017.
Publication year: 2017
Proceedings of the 2017 Sustainable Internet and ICT for Sustainability (SustainIT)
Collection
IFIP Conference on Sustainable Internet and ICT for Sustainability
Publication year: 2017
Performance Evaluation in Non-Intrusive Load Monitoring: datasets, metrics and tools - a review
Data Storage and Maintenance Challenges: The Case of Advanced Metering Infrastructure Systems
Conference
Proceedings of the 5th International Conference on ICT4S, Toronto, Canada
Publication year: 2018
An Experimental Comparison of Performance Metrics for Event Detection Algorithms in NILM
Workshop
Proceedings of the 4th International Workshop on Non-Intrusive Load Monitoring
Publication year: 2018
A Mouse over a Hotspot Survey: An exploration of perceptions of electricity consumption and patterns of indecision
Engineering and Deploying a Hardware and Software Platform to Collect and Label Non-Intrusive Load Monitoring Datasets
Abstract
Current approaches for collecting and labeling Non- Intrusive Load Monitoring (NILM) datasets still rely heavily on a lengthy and error-prone manual inspection of the whole dataset. Consequently, it is still difficult to find fully labeled datasets that could help furthering, even more, the research in this field. In an attempt to overcome this situation, we propose a hardware and software platform to collect and label NILM sensor data in a semi-automatic labeling fashion. Our platform combines aggregate and plug-level smart-meters to measure consumption data, software algorithms to automatically detect changes in the different monitored loads and a graphical user interface where the end-user can supervise the labeling process. In this paper, we describe the different components that comprise our platform. We also present the results of one live deployment that was performed to test the feasibility of our approach. The results of the deployment show that our system was capable of explaining about 82% of the aggregate load, and automatically detect 94% of the power transitions in the plug-level loads.
Resources
Software (GitLab Repository)
Data (SustDataED Public Dataset)
Developing and Evaluating a Probabilistic Event Detector for Non-Intrusive Load Monitoring
EMD-DF: A Data Model and File Format for Energy Monitoring and Disaggregation Datasets
A Comparison of Performance Metrics for Event Classification in Non-Intrusive Load Monitoring
SustDataED: A Public Dataset for Electric Energy Disaggregation Research
Poster Abstract
Proceedings of ICT for Sustainability 2016. Amsterdam, The Netherlands
Publication year: 2016
Towards using Low-Cost Opportunistic Energy Sensing for Promoting Energy Conservation
What-a-Watt: Exploring Electricity Production Literacy Through a Long Term Eco-Feedback Study
Towards Systematic Performance Evaluation of Non-Intrusive Load Monitoring Algorithms and Systems
EnerSpectrum: Exposing the source of energy through plug-level eco-feedack
Semi-Automatic Labeling for Non-Intrusive Load Monitoring Datasets
Understanding families’ motivations for sustainable behaviors
Show Me or Tell Me: Designing Avatars for Feedback
SustData: A Public Dataset for ICT4S Electric Energy Research
SURF and SURF-PI: A File Format and API for Non-Intrusive Load Monitoring Public Datasets
Poster Abstract
Proceedings of ACM e-Energy 2014, Pages 225-226. Cambridge, UK
Publication year: 2014
What-a-Watt : Where does my electricity comes from?
WattsBurning on my mailbox: a tangible art inspired eco-feedback visualization for sharing energy consumption
WATTSBurning: design and evaluation of an innovative eco-feedback system
Understanding the Limitations of Eco-feedback: a One Year Long-term Study
Towards Automating the Performance Evaluation of Non-Intrusive Load Monitoring Systems
Workshop
Adjunct Proceedings of ICT for Sustainability 2013. Zurich, Switzerland
Publication year: 2013
Low cost framework for non-intrusive home energy monitoring and research
HomeTree – An Art Inspired Mobile Eco-feedback Visualization
A long-term study of energy eco-feedback using non-intrusive load monitoring
Poster Abstract
Adjunct Proceedings of Persuasive Technology 2012. Linköping, Sweden
Publication year: 2012