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IEEE General Meeting Power& Energy Society

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

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

This article proposes a comprehensive framework encompassing energy sharing optimization, pricing schemes for energy transactions, and fairness metrics to validate the profit distribution of members in an energy community. First, a mixed-integer linear programming model is introduced to optimize energy sharing among the members of an energy community. Second, the study provides insights into the impact of four pricing mechanisms on economic fairness within the energy community. Finally, to validate the profit distribution, two fairness metrics assessing the quality of experience and the profit gaps are integrated to ensure economic equity within the energy community. The results shed light on the achieved level of fairness, evaluating the effectiveness of diverse pricing methods and the collaborative energy-sharing dynamics within the energy community.

关键词： Measurement Costs Scalability Buildings Collaboration Pricing Mixed integer linear programming Quality of experience Sustainable development Optimization

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Electric Water Heater Modelling for Direct Load Control Demand Response

Electric Water Heater Modelling for Direct Load Control Dema...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Md Tofael Ahmed Pedro Faria Omid Abrishambaf Zita Vale GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (IPP) Porto Portugal

Home Energy Management System creates the scopes to small household electrical appliances users to participate in the demand response programs. Among several load controllable electrical household appliances water heater is more suitable. Integration of water heater is considered to manage the demand response events that can contribute to smart grid technology. This paper represents a thermodynamic load model for a water heater, which is considered as to be controlled through direct load control for demand response program. The daily electricity consumption and temperature profile of the heater is also considered, the direct load control method is activated to the heater as soon as the energy consumption reaches to 1 kW, with the effects the device is turned off for next one hour. In results, it gained a significant reduction in the electricity consumption for the users without making any discomfort as temperature does not reduce to disruption level. Real time electricity pricing is also compared which implied financial benefit to the consumers. The result exhibit that the method applied to this heater can contribute and participate in the demand response events.

关键词： Water heating Load modeling Resistance heating Home appliances Temperature measurement Load management Smart grids

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A Brief Review on Optimal Network Planning Considering Energy Storage Systems and Uncertainty

A Brief Review on Optimal Network Planning Considering Energ...

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2023 International Conference on Future Energy Solutions, FES 2023

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

ISBN: (纸本)9798350332308

The topic of optimal planning has always been relevant ever since modern-day electricity markets were established. With the increasing awareness for a stable future, environmentally renewable sources of electricity production have seen a major uprise in latest years. Along with its inherent benefits, this increase in penetration of renewable energy sources also causes some unforeseen issues, such as lower network flexibility since most renewable production is intermittent and unpredictable, and harder generation forecasting for the same reasons. Many authors have researched ways to mitigate these issues, and most point to utilizing energy storage systems. Energy storage and uncertainty are not necessarily new topics, but they are now more prominent than ever and a must in recent optimal planning models regarding electricity networks. This paper aims to highlight some contributions made by literature regarding the topic, focusing on models studying energy storage systems, models that consider uncertainty, and models that consider both. © 2023 IEEE.

关键词： Renewable energy resources

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Building Energy Consumption Forecast under Different Anticipations on a Green Computation Perspective

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IFAC-PapersOnLine 2023年第2期56卷 10923-10928页

作者： Daniel Ramos Pedro Faria Luis Gomes Zita Vale Intelligent Systems Associated Laboratory (LASI) Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) Polytechnic of Porto (P.PORTO) Porto Portugal

Electrical buildings are composed by smart grids technologies intended on improving the energy efficiency. Nowadays, forecasting algorithms are crucial to formulate advance decisions resulting in lower energy costs. This paper uses two forecasting algorithms known as artificial neural networks and k-nearest neighbors to obtain accurate energy predictions in a target week with the support of an annual historic with energy and auxiliary sensors devices data. Green computing is also addressed in this paper to value the environmental sustainability of computing devices. This is possible by reducing the computational effort of the GPU device dedicated on forecasting activities. Therefore, the historic and predictions of this paper are contextualized in five minutes periods and hour schedules with energy activity behaviors.

关键词： building energy efficiency forecasting green computing

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Optimizing Energy Costs in Energy Communities: A Monthly Tariff Clustering Approach

Optimizing Energy Costs in Energy Communities: A Monthly Tar...

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International Conference on intelligent Systems Applications to Power Systems (ISAP)

作者： Fernando Lezama Diego Bairrao Filipe Doria Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI - Polytechnic of Porto Porto Portugal

ISBN: (数字)9798331531751

ISBN: (纸本)9798331531768

In collaborative energy communities, optimizing energy costs is a critical aspect of sustainable management. This article explores the potential benefits of applying clustering algorithms to vary retail tariffs monthly, aiming to reduce energy bills for the community as a whole. The article compares a traditional approach of applying the same tariff to all community members throughout the year with a novel approach of dynamically changing tariffs based on monthly clustering results. A case study is conducted, wherein energy bill costs per month are analyzed under different tariff scenarios utilizing k-means clustering. Results indicate that the proposed approach yields promising reductions in energy costs, up to 8.76% (1170.18 EUR) improvement compared to the traditional method. The study contributes valuable insights into the practical application of clustering in energy community management and highlights the potential for significant cost savings through dynamic tariff adjustments.

关键词： Costs Accuracy Heuristic algorithms Switching frequency Tariffs Clustering algorithms Switches Power systems intelligent systems Optimization

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Anomaly Detection in Cyber-Physical Systems: Reconstruction of a Prediction Error Feature Space

Anomaly Detection in Cyber-Physical Systems: Reconstruction ...

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Security of Information and Networks (SIN), International Conference on

作者： Nuno Oliveira Norberto Sousa Jorge Oliveira Isabel Praça Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) Porto School of Engineering (ISEP) Porto Portugal

ISBN: (纸本)9781728192673

Cyber-physical systems are infrastructures that use digital information such as network communications and sensor readings to control entities in the physical world. Many cyber-physical systems in airports, hospitals and nuclear power plants are regarded as critical infrastructures since a disruption of its normal functionality can result in negative consequences for the society. In the last few years, some security solutions for cyber-physical systems based on artificial intelligence have been proposed. Nevertheless, knowledge domain is required to properly setup and train artificial intelligence algorithms. Our work proposes a novel anomaly detection framework based on error space reconstruction, where genetic algorithms are used to perform hyperparameter optimization of machine learning methods. The proposed method achieved an F1-score of 87.89% in the SWaT dataset.

关键词： Support vector machines Machine learning algorithms Machine learning Cyber-physical systems Predictive models Prediction algorithms Security

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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 engineering (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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Participation of a Smart Community of Consumers in Demand Response Programs

Participation of a Smart Community of Consumers in Demand Re...

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Clemson University Power Systems Conference (PSC)

作者： Omid Abrishambaf Pedro Faria Zita Vale GECAD— Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (IPP) Porto Portugal

ISBN: (纸本)9781728103174;9781728103167

The penetration of renewable energy resources and demand response programs causes several management issues, such as network instability. Several research projects are currently investigating and surveying several methods to enhance the network reliability. This paper represents a smart model of community grid that contains a central management unit and several consumers, producers and prosumers. In the proposed model, the community manager is able to control the consumption and generation of the resources by establishing contracts with its members. The community manager utilizes a single period optimization problem for minimizing its operation costs by applying different types of demand response programs and the use of renewable resources. In the case study, an internal low voltage distribution network of a real university campus is considered as the community grid, in order to test and validate the proposed model.

关键词： Contracts Optimization Load management Microgrids Pricing Electricity supply industry Smart cities

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Data mining for remuneration of consumers demand response participation 18th

Data mining for remuneration of consumers demand response pa...

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18th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2020

作者： Ribeiro, Catarina Pinto, Tiago Vale, Zita Baptista, José GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Vila Real Portugal Porto Portugal UTAD – Universidade de Trás-os-Montes e Alto-Douro Vila Real Portugal CPES – INESCTEC Porto Portugal

ISBN: (纸本)9783030519988

With the implementation of micro grids and smart grids, new business models able to cope with the new opportunities are being developed. Virtual Power Players are a player that allows aggregating a diversity of entities, to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players’ benefits. The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. This paper proposes methodologies to develop strategic remuneration of aggregated consumers with demand response participation, this model uses a clustering algorithm, applied on values that were obtained from a scheduling methodology of a real Portuguese distribution network with 937 buses, 20310 consumers and 548 distributed generators. The normalization methods and clustering methodologies were applied to several variables of different consumers, which creates sub-groups of data according to their correlations. The clustering process is evaluated so that the number of data sub-groups that brings the most added value for the decision-making process is found, according to players characteristics. © Springer Nature Switzerland AG 2020.

关键词： Distributed power generation

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