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IEEE Power and Energy Society General Meeting

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

Electricity markets are evolving into a local trading setting, which makes it for unexperienced players to achieve good agreements and obtain profits. One of the solutions to deal with this issue is to provide players with decision support solutions capable of identifying opponents' negotiation profiles, so that negotiation strategies can be adapted to those profiles in order to reach the best possible results from negotiations. This paper presents an approach that classifies opponents' proposals during a negotiation, to determine which is the typical negotiation profile in which the opponent most relates. The classification process is performed using an artificial neural network approach, and it is able to adapt at each new proposal during the negotiation process, by re-classifying the opponents' negotiation profile according to the most recent actions. In this way, effective decision support is provided to market players, enabling them to adapt the negotiation strategy throughout the negotiations.

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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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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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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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An Agent-based IoT System for intelligent Energy Monitoring in Buildings

An Agent-based IoT System for Intelligent Energy Monitoring ...

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IEEE Vehicular Technology Conference

作者： Luis Gomes Filipe Sousa Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering - Polytechnic of Porto (ISEP/IPP) Porto Portugal

The new power system paradigm demands a more active end-consumer participation in smart grids environment. To achieve this participation, new demand side management solutions should be developed and analyzed. Moreover, the massive dissemination of internet of things devices inside buildings are a reality in nowadays. This paper proposes a multi-agent system for microgrid representation that integrates internet of thing devices to boost the energy management in today's buildings. The paper will present the proposed multi-agent system as well as an environmental awareness smart plug. The case study in this paper will present the data acquisition from a real building using a combination of market internet of things smart plugs, the proposed environmental awareness smart plug and a load emulator.

关键词： Plugs Buildings Energy management Protocols Microgrids intelligent sensors

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A New Hybrid-Adaptive Differential Evolution for a Smart Grid Application Under Uncertainty

A New Hybrid-Adaptive Differential Evolution for a Smart Gri...

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Congress on Evolutionary Computation

作者： Fernando Lezama Joao Soares Ricardo Faia Tiago Pinto Zita Vale GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation Development School of Engineering Porto Portugal BISITE Research Center University of Salamanca Salamanca Spain

Power systems are showing a dynamic evolution in the last few years, caused in part by the adoption of smart grid technologies. The integration of new elements that represent a source of uncertainty, such as renewables generation, electric vehicles, variable loads and electricity markets, poses a higher degree of complexity causing that traditional mathematical formulations struggle in finding efficient solutions to problems in the smart grid context. In some situations, where traditional approaches fail, computational intelligence has demonstrated being a very powerful tool for solving optimization problems. In this paper, we analyze the application of Differential Evolution (DE) to address an energy resource management problem under uncertain environments. We perform a systematic parameter tuning to determine the best set of parameters of four state-of-the-art DE strategies. Having knowledge of the sensitivity of DE to the parameter selection, self-adaptive parameter control DE algorithms are also implemented, showing that competitive results can be achieved without the application of parameter tuning methodologies. Finally, a new hybrid-adaptive DE algorithm, HyDE, which uses a new “DE/target - to - perturbed_best/1” strategy and an adaptive control parameter mechanism, is proposed to solve the problem. Results show that DE strategies with fixed parameters, despite very sensitive to the setting, can find better solutions than some adaptive DE versions. Overall, our HyDE algorithm excelled all the other tested algorithms, proving its effectiveness solving a smart grid application under uncertainty.

关键词： Uncertainty Smart grids Mathematical model Complexity theory Optimization Energy resources Weather forecasting

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Scalable computational framework using intelligent optimization: Microgrids dispatch and electricity market joint simulation

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IFAC-PapersOnLine 2017年第1期50卷 3362-3367页

作者： Soares J. Pinto T. Sousa F. Borges N. Vale Z. Michiorri A. GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation Development Polytechnic of Porto (IPP) Porto Portugal MINES Paristech France

Worldwide microgrid capacity is expected to reach 7 GW and a market value of $35 billion dollars in the next few years. The decentralization of the generation dispatch role and different ownership models concerning microgrids, will contribute to increase the complexity of the future power systems. Analyzing new policies and strategies as well as evaluating those impacts is only possible with the use of sophisticated simulation tools. This paper presents a scalable computational simulation to address microgrid dispatch and the impact in the electricity market. Computational intelligence techniques are integrated to improve the effectiveness of the simulation tool. These techniques include CPLEX; differential search algorithm and quantum particle swarm optimization. Each microgrid player is able to solve a day-ahead scheduling problem and submit bids to the electricity market agent (spot market), which calculates the market clearing price. The developed case study with a large number of players totaling about 150,000 consumers suggest the relevance of the developed computational framework. © 2017

关键词： agent-based demand response market microgrid simulation stochastic optimization

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Intensive summer course in robotics – Robotcraft

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Applied computing and Informatics 2018年第1-2期16卷 155-179页

作者： Ferreira, N.M. Fonseca Araujo, André Couceiro, M.S. Portugal, David Department of Electrical Engineering (DEE) Engineering Institute of Coimbra (ISEC) Polytechnic of Coimbra (IPC) Rua Pedro Nunes – Quinta da Nora Coimbra Portugal GECAD - Knowledge Research Group on Intelligent Engineering and Computing for Advanced Innovation Development of the Engineering Institute of Porto (ISEP) Polytechnic Institute of Porto (IPP) Porto Portugal INESC TEC – Institute for Systems and Computer Engineering Technology and Science Porto Portugal Ingeniarius Lda Coimbra Portugal

This paper describes a two-month summer intensive course designed to introduce participants with a hands-on technical craft on robotics and to acquire experience in the low-level details of embedded systems. Attendants started this course with a brief introduction to robotics;learned to draw, design and create a personalized 3D structure for their mobile robotic platform and developed skills in embedded systems. They were familiarize with the practices used in robotics, learning to connect all sensors and actuator, developing a typical application on differential kinematic using Arduino, exploring ROS features under Raspberry Pi environment and Arduino – Raspberry Pi communication. Different paradigms and some real applications and programming were addressed on the topic of Artificial Intelligence. Throughout the course, participants were introduced to programming languages (including Python and C++), advanced programming concepts such as ROS, basic API development, system concepts such as I2C and UART serial interfaces, PWM motor control and sensor fusion to improve robotic navigation and localization. This paper describes not just the concept, layout and methodology used on RobotCraft 2017 but also presents the participants knowledge background and their overall opinions, leading to focus on lessons learned and suggestions for future editions. © 2018, N.M. Fonseca Ferreira, André Araujo, M.S. Couceiro and David Portugal.

关键词： International trends in educational robotics Project-based learning ROS

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A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties

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IFAC-PapersOnLine 2017年第1期50卷 3350-3355页

作者： Borges N. Soares J. Vale Z. GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (ISEP/IPP) Rua Dr. Almeida 431 Porto 4200-072 Portugal

This paper presents a Particle Swarm Optimization (PSO) methodology to solve the problem of day-ahead microgrid (MG) dispatch with high penetration of Distributed Generation (DG) and considering uncertainties. The proposed methodology has the objective to satisfy demand aiming at obtaining the maximum profit, corresponding to the difference between the income and costs of the MG. This methodology considers the uncertainties associated with the production of electricity by the photovoltaic and wind sources. This uncertainty is modeled with the use of a robust approach in PSO. A case study is presented using a 21-bus MG from a real university campus in Portugal, and the projection of distributed energy resources based on the evolution scenario for the year 2050 managed by an aggregator. © 2017

关键词： Energy Resources Management Microgrids Particle Swarm Optimization Robust Optimization

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Multi-objective Particle Swarm Optimization to Solve Energy Scheduling with Vehicle-to-Grid in Office Buildings Considering Uncertainties

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IFAC-PapersOnLine 2017年第1期50卷 3356-3361页

作者： Borges N. Soares J. Vale Z. GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (ISEP/IPP) Rua Dr. Almeida 431 Porto 4200-072 Portugal

This paper presents a Multi-Objective Particle Swarm Optimization (MOPSO) methodology to solve the problem of energy resource management in buildings with a penetration of Distributed Generation (DG) and Electric Vehicles (EVs). The proposed methodology consists in a multi-objective function, in which it is intended to maximize the profit and minimize CO 2 emissions. This methodology considers the uncertainties associated with the production of electricity by the photovoltaic and wind energy sources. This uncertainty is modeled with the use of a robust optimization approach in the metaheuristic. A case study is presented using a real building facility from Portugal, in order to verify the feasibility of the implemented robust MOPSO. © 2017

关键词： Electric Vehicles Energy Resources Management Multi-Objective Optimization Robust Optimization Uncertainty

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