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Demand Response-based Model for an Energy Community Considering Members and Electric Vehicles Participation

Demand Response-based Model for an Energy Community Consider...

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International Conference on Environment and Electrical engineering (EEEIC)

作者： Ruben Barreto Luis Gomes Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI Polytechnic of Porto Porto Portugal

This paper proposes a demand response-based model to manage the energy resources of an energy community, considering the data privacy of the respective community members and electric vehicles. First, through a day-ahead forecasting algorithm, the implemented model identifies possible demand response events to be launched in the energy community. Then, the community members and electric vehicles are ranked to identify which will be selected to participate in the respective demand response event. This selection is based on several metrics created to assess different types of community members' data through clustering algorithms. Furthermore, this model also considers real-time monitoring and evaluation of the demand response event. Finally, the implemented model was tested with energy community data containing 750 possible candidates to participate in the demand response event with their flexibility, where these candidates are households and several different electric vehicles. The results show that the implemented model enables a saving of 13.66 EUR while reducing the CO 2 emissions by 32.34 kg in a single demand response event.

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Shared Intelligence Platform for Collaborative Simulations using Sequences of Algorithms: An Electricity Market participation case study

Shared Intelligence Platform for Collaborative Simulations u...

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IEEE Manchester PowerTech Conference

作者： Eugenia Vinagre Tiago Pinto Isabel Praca Luis Gomes Joao Soares Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering - Polytechnic of Porto (ISEP/IPP)

ISBN: (纸本)9781509042388

SEAS Shared Intelligence (SEAS SI) is a platform for algorithms sharing and execution developed under the scope of Smart Energy Aware Systems (SEAS) project to promote the intelligent management of smart grids and microgrids, by means of the shared usage of algorithms and tools, while ensuring code and intellectual protection. In this paper the platform goals and architecture are described, focusing on the recent achievement regarding the connection of distinct algorithms, which enables the execution of dynamic simulations using sequences of algorithms from distinct sources. A case study based on several SEAS SI available algorithms is presented with the objective of showing the advantages of the SEAS SI capability of supporting simulations based on sequences of algorithms. Namely, electricity market bid values are calculated by a metalearner, which is fed by market price forecasts using different methods, and by their respective forecasting errors. A case study presents some results to validate the presented work, through the simulation of the MIBEL electricity market using MASCEM (Multi-Agent Simulator of Competitive Electricity Markets).

关键词： Collaborative Simulations Electricity Markets Forecasting Metalearning Shared Intelligence

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Defining the Optimal Number of Demand Response Programs and Tariffs Using Clustering Methods

Defining the Optimal Number of Demand Response Programs and ...

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

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

ISBN: (数字)9781728131924

ISBN: (纸本)9781728131931

Nowadays, the data can be considered an asset when properly managed. An entity with the right tool to analyse the amount of data existent and withdraw crucial information will have the power to obliterate the competition. In the Energy sector, with Smart Grid introduction, small resources have more influence in the market through Demand Response and bidirectional communication. However, none of the actual business models is prepared to deal with the uncertainty related to these resources. The authors, in order to find a solution for this complex problem, proposed a methodology which the goal is to minimize operation costs and give fair compensation for resources who participate in the management of local markets. With this fair payment, it is expected continuous participation. Through clustering methods, remuneration groups are created. In the present paper, a study about the optimal number of clusters is performed. The information gives the Aggregator control in results of the following phases, understanding the impact in the remuneration of the resources.

关键词： Remuneration Elbow Distributed power generation Load management Clustering methods Optimal scheduling

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Wang and Mendel's fuzzy rule learning method for energy consumption forecasting considering the influence of environmental temperature

Wang and Mendel's fuzzy rule learning method for energy cons...

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International Global Information Infrastructure Symposium (GIIS)

作者： Aria Jozi Tiago Pinto Isabel Praça Francisco Silva Brígida Teixeira Zita Vale GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development IPP-Polytechnic of Porto Porto Portugal

Reliable consumption forecasts are crucial in several aspects of power and energy systems, e.g. to take advantage of the full potential of flexibility from consumers and to support the management from operators. With this need, several methodologies for electricity forecasting have emerged. However, the study of correlated external variables, such as temperature or luminosity, is still far from adequate. This paper presents the application of the Wang and Mendel's Fuzzy Rule Learning Method (WM) to forecast electricity consumption. The proposed approach includes two distinct strategies, the first one uses only the electricity consumption as the input of the method, and the second strategy considers a combination of the electricity consumption and the environmental temperature as the input, in order to extract value from the correlation between the two variables. A case study that considers the forecast of the energy consumption of a real office building is also presented. Results show that the WM method using the combination of energy consumption data and environmental temperature is able to provide more reliable forecasts for the energy consumption than several other methods experimented before, namely based on artificial neural networks and support vector machines. Additionally, the WM approach that considers the combination of input values achieves better results than the strategy that considers only the consumption history, hence concluding that WM is appropriate to incorporate different information sources.

关键词： Energy consumption Buildings Forecasting Databases Learning systems Weather forecasting

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TOOCC: Enabling Heterogeneous Systems Interoperability in the Study of Energy Systems

TOOCC: Enabling Heterogeneous Systems Interoperability in th...

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IEEE Power and Energy Society General Meeting

作者： Brigida Teixeira Francisco Silva Tiago Pinto Gabriel Santos Isabel Praca Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering - Polytechnic of Porto (ISEP/IPP)

ISBN: (纸本)9781538622131;9781538622124

The environmental impact and the scarcity of limited fossil fuels led to the need of investment in energy based on renewable sources. This has driven Europe to implement several policies that changed the energy market's paradigm, namely the incentive to microgeneration. The penetration of energy sources from intermittent nature has increased the unpredictability of the system, which makes simulation and analysis tools essential in order to provide decision support to entities in this sector. This paper presents the Tools Control Center (TOOCC) as a solution to increase the interoperability between heterogeneous agent-based systems, in the energy field. The proposed approach acts as a facilitator in the interaction between different systems through the usage of ontologies, allowing them to communicate in the same language. To understand the real applicability of this tool, a case study is presented concerning the interaction between several systems, with the purpose of enabling the energy resource scheduling of a microgrid, and the reaction of a house managed by a house management system.

关键词： Tools Ontologies Microgrids Frequency modulation Electricity supply industry Load modeling Proposals

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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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A Novel Approach to Network Traffic Analysis: the HERA tool

A Novel Approach to Network Traffic Analysis: the HERA tool

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IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Daniela Pinto Ivone Amorim Eva Maia Isabel Praça Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) Porto School of Engineering Polytechnic of Porto (ISEP-IPP) Porto Portugal Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) PORTIC – Porto Research Technology & Innovation Center Polytechnic of Porto (IPP) Porto Portugal

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

Cybersecurity threats highlight the need for robust network intrusion detection systems to identify malicious behaviour. These systems rely heavily on large datasets to train machine learning models capable of detecting patterns and predicting threats. In the past two decades, researchers have produced a multitude of datasets, however, some widely utilised recent datasets generated with CICFlowMeter contain inaccuracies. These result in flow generation and feature extraction inconsistencies, leading to skewed results and reduced system effectiveness. Other tools in this context lack ease of use, customizable feature sets, and flow labelling options. In this work, we introduce HERA, a new open-source tool that generates flow files and labelled or unlabelled datasets with user-defined features. Validated and tested with the UNSW-NB15 dataset, HERA demonstrated accurate flow and label generation.

关键词： Data privacy Accuracy Network intrusion detection Telecommunication traffic Machine learning Predictive models Feature extraction Labeling Computer security

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Lighting Consumption Optimization in an Office Building for Demand Response Participation

Lighting Consumption Optimization in an Office Building for ...

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Clemson University Power Systems Conference (PSC)

作者： Mahsa Khorram Pedro Faria Omid Abrishambaf Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development ISEP/IPP – Polytechnic of Porto Porto Portugal

ISBN: (纸本)9781728103174;9781728103167

Due to daily increment of electricity demand all around the world, the use of renewable energy resources and the methods of energy optimization are being important. Since the lighting systems have a pivotal role in the energy consumption of the buildings, the optimization of the lighting system should be effective. Hence, the focus of this paper is to minimize the lights consumption of an office building, while participating in demand response programs. The methodology of this work is proposed as a linear optimization problem that manages the generation of a renewable energy resource, which supplies a part of the energy consumption of the building. The lighting system of the building consists of the several laboratorial and commercial equipment, utilizing different communication interfaces. For the case studies, the amount of the renewable energy generation, total consumption of building, and the consumption of the lights in a real research building are considered.

关键词： Buildings Optimization Power demand Renewable energy sources Smart grids Fluorescent lamps

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Optimization of electricity markets participation with QPSO

Optimization of electricity markets participation with QPSO

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International Conference on European Electricity Market, EEM

作者： Ricardo Faia Tiago Pinto Zita Vale GECAD-Research Group on Intelligent Engineering Computing for Advanced Innovation and Development Polytechnic of Porto (ISEP/IPP) Porto Portugal

All around the world, the electric sector has suffered significant changes. With these alterations, electrical systems have become international, with several countries connected by a system where the management is done in common grounds. With the incorporation of large scale distributed generation, competitiveness in electrical markets has increased as small generators unite in order to be able to compete with large producers. In this game where the main objective is to win, and the premium is money it is necessary to be keen to be able to sell the available electricity at the best possible prices. With the objective of supporting players' decisions, decision support tools play a crucial role. These tools enable market players with suggestions of actions to increase their advantage from market participation. This paper presents a Quantum-based Particle Swarm Optimization (QPSO) methodology to solve the problem of optimal participation in multiple electricity markets.

关键词： Optimization Electricity supply industry Portfolios Particle swarm optimization Biological system modeling Quantum mechanics Contracts

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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 engineering (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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