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International Conference on European Electricity Market, EEM

作者： Gabriel Santos Ricardo Faia Fernando Lezama Zita Vale GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI – Intelligent Systems Associate Laboratory Polytechnic of Porto Porto Portugal

The EU is encouraging the creation of local energy communities (LECs) for electricity trading, promoting local balance and a self-sustained community while reducing electricity bills. Local electricity markets (LEMs) ease the electricity trading of distributed energy resources while incentivizing the integration of renewable energy sources into the grid. However, presently, LEMs have low liquidity, and the demand is significantly higher than the supply. One possible solution to address this issue is participation in the wholesale market, assessing lower prices, and providing additional savings. This work proposes a multilevel electricity trading framework for LECs’ participation. The simulation framework comprises different LEM models for electricity trading at different levels, culminating in wholesale market participation through a LEC aggregator. Results show the benefits of LECs’ participation in the multilevel trading platform with significant savings.

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Local Energy Market Competition Approach for Demand Response Events

Local Energy Market Competition Approach for Demand Response...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Cátia Silva Pedro Faria Zita Vale Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) Intelligent Systems Associated Laboratory (LASI) Polytechnic of Porto Porto Portugal

In local energy markets, Demand Response (DR) concept plays an essential role in balancing the generation and demand at a local level. Consumers and prosumers, assisted by aggregators, participate in DR events by responding to signals to adjust their energy consumption patterns. Aggregators act as intermediaries of small consumers, coordinating their participation. However, their response is uncertain due to their volatile behavior. Previous work by the authors designed a trustworthy rate to deal with uncertainty but did not consider any competition between players. This study approach allows competition between power and energy players. The idea is to give freedom of choice to the DR participants using a tool developed by the authors. In the end, it is expected to create an aggregator portfolio that aligns more closely with its objectives, particularly when it comes to maximizing profits.

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Inverse Neural Control of a Magnetic Levitation System: Experimental Results 20th

Inverse Neural Control of a Magnetic Levitation System: Expe...

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20th International Conference on Hybrid intelligent Systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired computing, NaBIC 2020

作者： Silva, Bruno E. Barbosa, Ramiro S. Porto Portugal GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development ISEP/IPP Porto Portugal

ISBN: (纸本)9783030730499

In this paper we investigate the use of inverse neural models to control a nonlinear and unstable magnetic levitation system composed of an electromagnet and a magnetic disk. The neural controllers are tested and analyzed on a low-cost Arduino control platform using MATLAB/Simulink. Experimental results show the effectiveness of neural networks to control nonlinear systems with better performance than conventional algorithms. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Costs

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A Multi-Agent System Empowered by Federated Learning and Genetic Programming

A Multi-Agent System Empowered by Federated Learning and Gen...

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IEEE Signal Processing and Communications Applications (SIU)

作者： Luis Gomes Bruno Ribeiro Fernando Lezama Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI - Intelligent Systems Associate Laboratory Polytechnic of Porto Porto Portugal

The use of multi-agent systems enables the modelling of complex and decentralized solutions, giving the ability to have agents representing different entities and assets in a social environment where they can interact and pursue their individual goals. However, multi-agent systems are usually data-driven solutions in which interactions are performed based on data sharing and environmental feedback. Therefore, the integration of multi-agent systems with federated learning, a knowledge-driven approach, allows agents to share knowledge among them in a collaborative and cooperative approach. This integration can be well seen in decentralized solutions where similar entities can benefit from collaborative and cooperative environments. This is the case in industrial environments and in smart grid environments, namely for the improvement of learning models. This paper proposes a methodology composed of a multi-agent system where the agents are empowered by federated learning. The proposed methodology was tested and validated using a genetic programming model with MNIST dataset in terms of feasibility and performance.

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Smart and advanced Electrical Skills: Identifying Current Gaps and Emerging Trends

Smart and Advanced Electrical Skills: Identifying Current Ga...

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Communications, Information, Electronic and Energy Systems (CIEES), International Conference on

作者： Emmanuel Karapidakis Marini Markaki Spyridon Apostolakis Bruno Canizes Radamanthys Androulakis Fábio Castro Electrical and Computer Engineering Department Hellenic Mediterranean University Heraklion Greece GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic Institute of Porto Porto Portugal GECAD - Research Group on Research Department ECTE Rethymno Greece

ISBN: (数字)9798350352863

ISBN: (纸本)9798350352870

With the rise of smart buildings, new expertise gaps and security vulnerabilities are emerging, necessitating a comprehensive understanding of their current state and proactive future planning to address these challeng.s. Such identification is crucial for mapping the pathway towards vocational modernization (keeping up with trends and goal alignment). To assess these gaps, this paper explores the extensive literature that draws on workshops, expert interviews, and research to identify emerging roles and training needs across seven countries: Greece, Spain, Portugal, Italy, North Macedonia, Germany, and the Netherlands. In particular, it examines the validity of its findings in critical areas such as security, privacy, and the integration of smart grids with energy markets. Additionally, the paper highlights future skills gaps emerging from advancements in IoT, automation, and renewable energy technologies. It emphasizes the growing demand for specialized electrical expertise to optimize energy production, integrate monitoring and storage systems, and manage electric vehicle charging and energy communities effectively. In conclusion, the study identifies critical gaps in expertise and training needed to keep up with the rapid evolution of smart building technologies. Emerging trends highlight the demand for interdisciplinary skills, particularly in IoT, automation, and renewable energy. As these fields advance, expertise in cybersecurity, energy management, and smart grid integration will be crucial, emphasizing the need for proactive workforce development and planning. The findings can be used to inform and direct policymakers towards the smooth reexamination of vocational training.

关键词： Renewable energy sources Smart buildings Automation Production Market research Vocational training Smart grids Planning Computer security Energy management

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Using Supervised Learning to Assign New Consumers to Demand Response Programs According to the Context

Using Supervised Learning to Assign New Consumers to Demand ...

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International Conference on Environment and Electrical eng.neering (EEEIC)

作者： Cá tia Silva Pedro Faria Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

Active consumers have now been empowered thanks to the smart grid concept. To avoid fossil fuels, the demand side must provide flexibility through Demand Response events. However, selecting the proper participants for an event can be complex due to response uncertainty. The authors design a Contextual Consumer Rate to identify the trustworthy participants according to previous performances. In the present case study, the authors address the problem of new players with no information. In this way, two different methods were compared to predict their rate. Besides, the authors also refer to the consumer privacy testing of the dataset with and without information that could lead to the participant identification. The results found to prove that, for the proposed methodology, private information does not have a high impact to attribute a rate.

关键词： Schedules Uncertainty Sensitivity Supervised learning Demand response Smart grids Security

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Virtual Power Plant Optimization Service-Benchmark of Solvers

Virtual Power Plant Optimization Service-Benchmark of Solver...

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Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Filipe Alves Rui Ribeiro Maria Petiz Ali Abbasi Pedro Carvalho Ricardo Faia Pedro Faria Zita Vaie Ricardo Rodrigues DTx—Digital Transformation CoLAB University of Minho Guimarães Portugal GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI-Intelligent Systems Associate Laboratory Polytechnic of Porto Porto Portugal

ISBN: (数字)9788396960160

ISBN: (纸本)9798350359718

This work provides a comprehensive analysis of the optimization of a Virtual Power Plant (VPP), that consider the presence of energy storage systems and controllable loads, through the benchmarking of various solvers. It delves into the development of a Mixed Integer Linear Programming (MILP) algorithm aiming at optimizing energy management and exchange within a VPP, that takes into account the operation of shift electric appliances and battery storage systems among different houses. The proposed model aims to minimize the overall electricity cost while ensuring that the energy demand of the system is met, the battery state of charge is maintained within safe operating limits, and the shift electrical appliance is scheduled. Furthermore, the experimental comparisons, the study evaluates the performance of commercial and open-source solvers in handling the complex dynamics of energy demand and supply. The findings highlight the importance of solver selection in enhancing the management, scalability, and reliability of VPP optimization strategies, offering insights into the optimal combination of programming interfaces and solvers for efficient VPP operation.

关键词： Energy consumption Scalability Virtual power plants Programming Batteries Mixed integer linear programming State of charge Reliability Optimization Load modeling

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Bidding in Local Electricity Markets Considering Community Storage Systems

Bidding in Local Electricity Markets Considering Community S...

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International Conference on Environment and Electrical eng.neering (EEEIC)

作者： Fernando Lezama Joao Soares Zahra Foroozandeh Zita Vale Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) LASI - Polytechnic of Porto Porto Portugal

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

Local energy markets are complex environments with interactions from different actors pursuing diverse objectives. This article introduces a model for bidding in local energy markets considering consumers, small producers, and prosumers with renewable generation. In addition, the model includes a community centralized energy storage system (ESS) that consumers as a community can freely use, paying an incentive to small producers for charging the storage device. Due to its complexity, the problem is solved using metaheuristic optimization. Through an experiment in a case study with nine agents and a 13.2 kWh ESS, we show that the community can benefit from the centralized storage unit, minimizing the consumers' cost and at the same time increasing the profits of the small generators. However, it is also shown that the way in which the community makes use of the central unit and splits the cost and profits is not trivial, and further discussion about the fair share of profits obtained from the battery requires scrutiny of the results.

关键词： Degradation Renewable energy sources Costs Metaheuristics Stochastic processes Europe Electricity supply industry

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Energy Community Consumption and Generation Dataset with Appliance Allocation

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IFAC-PapersOnLine 2022年第9期55卷 285-290页

作者： Calvin Goncalves Ruben Barreto Pedro Faria Luis Gomes Zita Vale GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (P.PORTO) P-4200-072 Porto Portugal

New energy approaches and models require an ample amount of data to be collected in order to be tested and validated, however ordinary on-site load data measuring from buildings or households can be expensive and time-consuming. This paper creates a dataset of a residential community by attributing sample consumption and photovoltaic production profiles and disaggregating the total power consumption of these households into the consumption of several individual appliances commonly used. Initially, a few consumption and photovoltaic production profiles and an extensive library of appliance profiles were collected, allowing the tool created to randomly assign the appliances’ load profile, if possible, into the available consumption areas of each end-user and in certain intervals previously defined by the user. In the case study, we generated a community with 49 households and a public building (municipal library) in 50 buildings and attributed 15 of these with renewable solar energy. The results show the creation of a flexible energy community where the appliances allocated can occupy approximately 40% of the total consumption profiles.

关键词： Appliance Allocation End-user Energy Profile Energy Community Renewable Energy

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Incentive-based and Price-based Demand Response to Prevent Congestion in Energy Communities

Incentive-based and Price-based Demand Response to Prevent C...

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International Conference on Environment and Electrical eng.neering (EEEIC)

作者： Helder Pereira Ricardo Faia Luis Gomes Pedro Faria Zita Vale Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) Polytechnic of Porto (ISEP/IPP) Porto Portugal

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

Under the current strategy of the European Union, energy communities have the utmost importance for increasing active participation in local energy markets. Thus, it is essential to maintain the networks that support them operational to all the processes involving energy transactions. To solve this problem, this paper proposes two preventive demand response models, one incentive-based, and the other price-based. These models make use of a power flow algorithm, to detect the periods susceptible to grid issues, and define the needed consumption reduction in the community. The ability to apply the two demand response methods sequentially brings greater robustness to the system when it is necessary to solve critical situations that required high values of flexibility. This is remonstrated in the case study, where there is a scenario where a single program cannot not solve the issue, and an increase of 4.05 % of the price was needed even after the incentive-based demand response program.

关键词： Scalability Europe Predictive models Demand response Robustness Data models Load flow

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