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17th International Conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2022

作者： Mota, Bruno Faria, Pedro Ramos, Carlos GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal LASI - Intelligent Systems Associate Laboratory Polytechnic of Porto Porto Portugal

ISBN: (纸本)9783031180491

Recent advancements in technologies such as in Big data and Internet of Things have made Predictive Maintenance (PdM) a key strategy to reduce unnecessary maintenance costs and improve product quality in the manufacturing sector. The premise of this paper is to implement and explore some of the most promising machine learning models for PdM, a Gradient Boosting (GB) model, and a Support Vector Machine (SVM) model. An innovative methodology for model training is proposed that aims to improve model performance while also allowing for continuous training. Furthermore, it is proposed an automatic hyperparameter tunning approach for the GB and SVM models. A synthetic dataset that reflects industrial machine data was used to validate the proposed methodology. The implemented models can achieve up to 0.92 recall and 94.55% accuracy, highlighting the effectiveness of the proposed methodology. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Predictive maintenance

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Simulation and Operation Analysis of a Smart Grid Using Simulink 14th

Simulation and Operation Analysis of a Smart Grid Using Simu...

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14th International conference of the IMACS TC1 Committee, ELECTRIMACS 2022

作者： Van Waeyenberge, Alexander Canizes, Bruno Soares, João Ramos, Sérgio Ravyts, Simon Chavez, Juliana Vale, Zita GECAD Research Center Polytechnic of Porto Porto Portugal GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto Porto Portugal ESAT ELECTA KU Leuven Ghent Belgium

ISBN: (纸本)9783031248368

Changes will be required to handle the increased power flow in the network as the distribution infrastructure ages and the number of EVs and renewable grows. Designing and operating an intelligent network that reacts to changing power flows to ensure the optimal operation is the most economical option than fortifying the network with heavier cables. This work aims to build a model of a 13 bus medium voltage distribution network with high penetration of distributed energy resources and use it to analyze network conditions. The MATLAB Simulink software is used to model and evaluate the network. The outcomes suggest the model is promising and valid even when renewable generation is at low levels. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Smart power grids

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Open-access tools for the modelling and simulation of electricity markets

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Energy Informatics 2022年第4期5卷 43页

作者： Carvalho, Rui Santos, Gabriel Vale, Zita GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI - Intelligent Systems Associate Laboratory Institute of Engineering Polytechnic of Porto Rua Dr. Antonio Bernardino de Almeida 431 Porto4249-015 Portugal

Globally, the amount of renewable energy generation is increasing, which raises the complexity of operating electrical grids to maintain stability and balance and boosts the need for developing new electricity market (EM) models fitting this new reality. To test, study, and validate the possible effects of novel EM designs, simulation techniques are frequently employed. This work proposes the use of two open-access tools for the modeling and simulation of complex EMs. These are the Electricity Markets Service (EMS) and the Spine Toolbox. EMS enables the simulation of two commonly used auction-based algorithms and the execution of three European wholesale EMs. Being published as a web service facilitates its integration with other services, systems, or software agents, such as the Spine Toolbox. The Spine Toolbox, in turn, is an open-source software for complex energy systems modeling. Combining them allows the modeling and simulation of complex EMs from the wholesale to local markets, as well as testing and validating new market designs. This work’s case study demonstrates how to use these tools to simulate the operation of the Iberian EM – MIBEL – for a month, using public data available from the market operator’s website. The results are analyzed from the perspective of the market operator and two players, i.e., a selected buyer and seller, for a specific day and the whole month. © 2022, The Author(s).

关键词： Web services

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Flexibility Provision from Residential Houses: a Sensitive Analysis on Net Consumption Limits

Flexibility Provision from Residential Houses: a Sensitive A...

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Mediterranean Electrotechnical Conference (MELECON)

作者： Ricardo Faia Pedro Faria Luis Gomes Zita Vale Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) Intelligent Systems Associate Laboratory (LASI) Porto Portugal

ISBN: (数字)9798350387025

ISBN: (纸本)9798350387032

This paper explores the potential for flexibility provision a residential house equipped with 12 different loads, integrated with a battery storage system and photovoltaic panels. The study employs a sensitive analysis framework to examine the net consumption limits associated with total flexibility provision throughout different periods of the day. By incorporating renewable energy sources such as PV panels and energy storage via batteries, the research addresses the load management in modern households. The use of shifting properties to the loads enhances the potential for flexibility provision. The findings offer valuable insights into optimizing energy consumption, balancing loads, and improving the overall efficiency of residential energy systems. This work contributes to the advancement of smart grid technologies, sustainable energy practices, and the integration of renewable sources in residential settings.

关键词： Photovoltaic systems Renewable energy sources Costs Load management Linear programming Mathematical models Batteries

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Pedestrian Flow Early Warning System Based on WiFi Probe

Pedestrian Flow Early Warning System Based on WiFi Probe

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International Conference on Internet of Things, Communication and Intelligent Technology, IoTCIT 2022

作者： Wang, Yichan Ouyang, Hongbo Duan, Yun Xiangnan University Hunan Chenzhou423000 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Chenzhou China China Post Group Co. Ltd Hunan Chenzhou423000 China

ISBN: (纸本)9789819904150

With the social development and the increasing population, the person flowrate increases year by year in various public places, such as stations、hospitals and shopping malls;in different periods of time, the person flowrate will appears different data values in such places. Therefore, the monitoring of person flowrate data is very important, as an important indicator of regional public health events. The unique MAC address of the customer's mobile phone could be collected by WiFi probe for the unique identification, through data analysis technology it can provide a certain degree of data decision-making basis for decision-makers. Data analysis based on the collected by WiFi probe, break the traditional mode, provide reliable person flowrate analysis, use the extended management ability to deeply understand and provide real flow information, provide effective support for hierarchical early warning of public health events. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Probes

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Learning-Based Models for Intelligent Control Over Air Conditioning Units in a Smart Building 19th

Learning-Based Models for Intelligent Control Over Air Condi...

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19th International Conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2024

作者： Ribeiro, Bruno Silva, Rafael Mota, Bruno Gomes, Luis Vale, Zita Polytechnic of Porto Porto Portugal GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9783031750120

In power and energy systems, artificial intelligence is commonly used for energy forecasting and decision-making. However, the real deployment of artificial intelligence models for operation in smart buildings is not common, and there is a significant gap between the literature-proposed models and deployed models. In this research, the authors apply multiple machine learning models to learn user-profiles and comfort levels regarding air conditioning usage: decision tree, random forest, support vector machine, and artificial neural network. To validate the models, a real use case with a one-year dataset was used. The dataset preparation is also part of this research. The models were analyzed using simulation and the best solution, in this case support vector machine, was deployed in a real uncontrollable environment using a containerized-based solution. The promising results demonstrate that the proposed methodology can be deployed in real buildings and learn the air conditioning usage profiles within one year of use. The authors also proceed with the deployment of a learning model in a smart building. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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Knowledge Retrieval Mechanism for Smart Buildings Based on IoT Devices Data 1

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9th International Conference on Energy and Environment research, ICEER 2022

作者： Teixeira, Nuno Gomes, Luis Vale, Zita GECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto Rua Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (数字)9783031435591

ISBN: (纸本)9783031435584

The use of smart building solutions can bring advantages to both a building and its users. The main motivation of this work is to propose a solution based on internet of things devices to retrieve knowledge from historic data and, using the knowledge gained, contribute to the comfort of the user and the building’s sustainability. The use of internet of things devices enables the easy deployment of the proposed system in today’s buildings, where this kind of devices are commonly found. The knowledge regarding the role of each device and how they interact or impact each other will be studied by the proposed solutions that will deploy a continuous mechanism. The designed software architecture was developed in python, to allow easy implementation of different features. To test the proposed solution, it was used real data from a research building where several types of sensors were correlated to assess relations among data. The results show significant correlations between celling light consumption and the room’s light intensity sensor, and between the operation of air conditioning units and the room’s temperature, for example, data from 2 months, regarding air conditioner unit in room N102, demonstrates a − 0.85 correlation with the room temperature, when operating in cooling mode. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Internet of things

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Hourly uncertainty applied to optimal expansion planning considering energy storage and seasonal network impacts

Hourly uncertainty applied to optimal expansion planning con...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Castro, Fábio Canizes, Bruno Soares, João Vale, Zita GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI – Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9798350396782

The prevalence of renewable energy on most networks has grown exponentially in recent years. This introduces previously unknown issues, such as how unpredictable output may be and the fact that it is not continuous, necessitating extra preparation for network planning. This study presents a stochastic methodology to enable the network to consider investments in new lines and any energy storage systems it sees fit. Sixteen alternative situational scenarios are produced by segmenting the study into seasonal phases, which are then broken into four circumstances (morning, peak, afternoon, and night) for each of the four seasons. However, these are divided into hourly scenarios (totaling 8760), with different states for generation, load, storage, and electric vehicles. The model is evaluated on a 180-bus network in Portugal that includes distributed generation, a substation, and a number of the distribution operator's biomass generators in addition to the distributed generation. © 2023 IEEE.

关键词： Distribution Networks Energy Storage systems Optimal Planning Renewable Energy Seasonal Impacts Uncertainty

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Federated Genetic Programming: A Study About the Effects of Non-IID and Federation Size 20th

Federated Genetic Programming: A Study About the Effects of ...

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20th International Symposium on Distributed computing and Artificial Intelligence, DCAI 2023

作者： Ribeiro, Bruno Gomes, Luis Faia, Ricardo Vale, Zita GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9783031383328

The privacy and security of users’ data have been a concern in the last few years. New techniques like federated learning have appeared to allow the training of machine learning models without sharing the users’ personal data. These systems have a lot of variables that can change the outcome of the models. Studies have been made to explore the effect of these variables and their importance. However, those studies only focus on machine learning models, namely deep learning. This paper explores the impact of the federation size in unbalanced data using a genetic programming model for image classification. The results show that the federation size can have impact on the contributions of each client, and the dataset size can influence the quality of the individuals. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image classification

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Energy Community Integration of a Smart Home Based on an Open Source Multiagent System 21st

Energy Community Integration of a Smart Home Based on an Ope...

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21st International Conference on Practical Applications of Agents and Multi-Agent systems, PAAMS 2023

作者： Ribeiro, Bruno Faia, Ricardo Gomes, Luis Vale, Zita GECAD Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI—Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

ISBN: (纸本)9783031376153

Smart grid is a revolutionary concept that came to renew the way the power systems are thought. However, for these systems to be possible it is necessary and recommended that the consumers have the right technology integrated in their houses, in other words, have smart homes. This paper describes the demonstration of a smart home solution based on multiagent systems for the optimization of the house energy usage. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Multi agent systems

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