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Web-based platform for the management of citizen energy communities and their members

Energy Informatics 2021年第2期4卷 1-17页

作者： Pereira, Helder Gomes, Luis Faria, Pedro Vale, Zita Coelho, Carlos GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Rua Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal Institute of Engineering - Polytechnic of Porto Rua Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

The appearance of citizen energy communities demands the conception, development, and testing of new management models for the community and its end-users. Citizen energy communities promote the active participation of end-users, including them in the management of the community. End-users are incentivized to participate in demand response programs and share their energy among peers, enabling a decrease in their energy costs. In this paper, it is proposed a platform for the management of citizen energy communities. The paper focuses and presents four services related to energy tariffs, end-users’ aggregation, price elasticity, and load response. The services are based on historical data and enable deep analysis of end-users’ energy profiles. As the platform allows the upload of different scenarios, it is possible to test and validate management models in multiple energy communities and scenarios and study their impact in different conditions. The paper presents a case study, where all the services are applied to a community with 996 end-users. © 2021, The Author(s).

关键词： Elasticity

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Study of multi-tariff influence on the distributed generation remuneration 16th

Study of multi-tariff influence on the distributed generatio...

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16th International Conference on Distributed computing and Artificial Intelligence, DCAI 2019

作者： Silva, Cátia Faria, Pedro Vale, Zita GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development IPP - Polytechnic Institute of Porto Rua DR. Antonio Bernardino de Almeida Porto431 4200-072 Portugal

ISBN: (纸本)9783030239459

The energy market, with the introduction of the smart grids concept, opens the door to small distributed energy resources. However, these resources introduce an added level of difficulty to market management, requiring an entity to aggregate and manage them optimally. This paper proposes an approach that integrates these small resources. The methodology is composed of optimal scheduling, aggregation and remuneration based on aggregation. The method chosen for aggregation is k-means. In relation to previous works, the innovation goes through the multi-period and the comparison that this can have in the formation of groups. Thus, three scenarios were created: Whole Week, Work Days and Weekend. Profiles were added for 548 units of DG. The justification for the formation of groups will be a fairer remuneration and according to the contribution of each resource to the management of the network. © 2020, Springer Nature Switzerland AG.

关键词： Distributed power generation

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Climatization and luminosity optimization of buildings using genetic algorithm, random forest, and regression models

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Energy Informatics 2021年第2期4卷 1-18页

作者： Mota, Bruno Albergaria, Miguel Pereira, Helder Silva, José Gomes, Luis Vale, Zita Ramos, Carlos Institute of Engineering - Polytechnic of Porto Rua Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Rua Dr. António Bernardino de Almeida 431 Porto4200-072 Portugal

With the rise in popularity of artificial intelligence, coupled with the growing concern over the environment, there has been a surge in the use of intelligent energy management systems. Additionally, as more buildings transition into the smart grid and, consequently, more energy and environmental data is gathered, there has been a significant increase in the number of data-driven approaches for building management systems. This paper proposes a methodology that aims to optimize the climatization and luminosity inside a building, using a genetic algorithm, a random forest, and two polynomial models. The proposed methodology enables the real-time management of the building taking into account the user needs and preferences. Air conditioner units and light systems are optimized to minimize energy costs, while also improving the air quality and considering the users’ temperature and luminosity preferences. This paper shows the results achieved, by the proposed solution, in an office building case study. The promising results demonstrate the possibility of minimizing energy costs while maximizing the users’ comfort. © 2021, The Author(s).

关键词： Air quality

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A Consumer Trustworthiness Rate for Participation in Demand Response Programs

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IFAC-PapersOnLine 2020年第2期53卷 12596-12601页

作者： Cátia Silva Pedro Faria Zita Vale GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal Polytechnic of Porto Porto Portugal

Local energy communities with information from the real-time market may improve the market operation but also increase the complexity of the management problem thanks to the uncertainty associated with the actual response of these resources. For instance, consumers with price knowledge may change their power consumption to lower-cost periods. The authors present a model to deal with uncertainty from the Aggregator perspective: apply reliability rates to each consumer according to their actual response in events of Demand Response (DR). The consumers with higher rates are chosen to participate in the local flexibility markets. To compute the final rate, three different independent rates are used: Historical rate with past information, Cut-rate from the response in the actual period and the Last Day Rate which is the final reliability rate from the previous day. In the present paper, the influence of each independent rate, through the weight used, is studied.

关键词： Demand Response Uncertainty Aggregator Smart Grids Optimization

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Key Performance Indicators to Support the Participation in Demand Response Programs:A Testing Framework for End Users

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IFAC-PapersOnLine 2020年第2期53卷 12602-12607页

作者： Débora de São José Pedro Faria Cátia Silva Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Porto Portugal Polytechnic of Porto Porto Portugal

With the new challenges and complexity in power electricity management, demand response programs can be a way to reduce stress and strengthen power grids. However, as demand response implies end users to intentionally change their consuming patterns to adapt to grids needs, some decision-making support tools are necessary. The present paper proposes an energy management and controlling tool to assist electricity end users to make their decision to change consumption pattern in a DR scenario while using key performance indicators. The tool was tested using a group of 20 end users and showed a consistent result throughout all the elements in the sample.

关键词： System Management Monitoring Key Performance Indicators KPI Demand Response

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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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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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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 engineering (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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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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A Novel Framework for Multiagent knowledge-Based Federated Learning Systems 21st

A Novel Framework for Multiagent Knowledge-Based Federated L...

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

作者： Ribeiro, Bruno Gomes, Luis Barbarroxa, Rafael 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

Multiagent systems promote a decentralized and distributed approach that enable the division of complex problems into smaller parts. The use of multiagent systems also enables the representation of physical entities, such as persons, pursuing their own goals in an active and proactive society. Currently developments are promoting the idea of having machine learning models in agents to enable intelligent decisions in agents-side. However, machine learning, required assess to large datasets that cannot be available locally to individual agents, demanding the sharing of data or the use of public available datasets to training models for a given agent. To address this issue, this paper proposes the use of federated learning to enable the existence of a collaborative learning model that respects the data privacy, security, and ownership and can be in compliance with the European General Data Protection Regulation (EU GDPR). This paper proposes a novel framework called Python-based framework for agent-based communities powered by federated learning (PEAK FL) that will provide all the necessary tools to build powerful federated learning solutions based on agent communities. This framework provides the users the ability to implement and test hybrid solutions (multiagent-based federated learning systems) in a simple-to-use way, removing the unnecessary boilerplates. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Multi agent systems

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