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IEEE Power and Energy Society General Meeting

作者： Joao Soares Nuno Borges Bruno Canizes Zita Vale GECAD - Knowledge Engineering and Decision-Support Research Centre Polytechnic of Porto (ISEP/IPP)

ISBN: (纸本)9781467380416

This paper presents a framework and methodology to estimate the possible states of Electric Vehicles (EVs) regarding their location and periods of connection in the grid. A Monte Carlo Simulation (MCS) is implemented to estimate the probability of occurrence of these states. The framework assumes the availability of Information and Communication Technology (ICT) technology and previous data records to obtain the probabilistic states. A case study is presented using a fleet of 15 EVs considering a smart grid environment. A high accuracy was obtained with 1 million iterations in MCS.

关键词： Big Data Electric Vehicles Monte Carlo Simulation Smart Grid

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VPP Energy Resources Management considering Emissions: The case of northern Portugal 2020 to 2050

VPP Energy Resources Management considering Emissions: The c...

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IEEE Symposium Series on Computational Intelligence

作者： Joao Soares Nuno Borges Cristina Lobo Zita Vale GECAD - Knowledge Engineering and Decision-Support Research Centre Polytechnic of Porto (ISEP/IPP)

ISBN: (纸本)9781479975617

In SGs context, Distributed Generation (DG) based on renewable sources represents an alternative paradigm of energy supply and the opportunity for significant reduction in CO_2 emissions. However, strict emissions regulations might impact profit seeking Virtual Power Plants (VPP) operation. This paper addresses energy management at distribution level and evaluates if electricity emissions are worth to be considered in different time horizons. A realistic case study is developed for a chosen area of the northern region of Portugal, namely one part of the distribution grid from Vila Real managed by a VPP, with estimated penetration of Electric Vehicles (EV), several Distributed Generation (DG), Demand Response (DR) and Energy Storage Systems (ESS). The considered characteristics of the case study took into account several studies and the forecasts made in the literature. For 2030 it is expected an average CO_2 grid emission of 50 kgCO_2/MWh in Portugal. The repository-based multi-objective Particle Swarm Optimization (MOPSO) is used to tackle the developed optimization problem. Three scenarios are evaluated for the profit seeking VPP in 2020, 2030 and 2050 perspectives.

关键词： Energy Resources Management Multi-objective Particle Swarm Optimization Virtual Power Plant Smart Grid

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Characterize a step using machine learning

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2015年第11期10卷 69-84页

作者： Anacleto, Ricardo Figueiredo, Lino Almeida, Ana Novais, Paulo Meireles, António GECAD - Knowledge Engineering and Decision Support Research Center School of Engineering - Polytechnic of Porto Porto Portugal DI/CCTC - Computer Science and Technology Center University of Minho Braga Portugal

Most of pedestrian inertial navigation system estimates displacement based on the integration of inertial sensors measurements. However, due to low-cost sensors and pedestrian dead reckoning inherent characteristics these systems provide huge location estimation errors. To suppress some of these limitations we propose a pedestrian inertial navigation system based on low-cost sensors and on information fusion and learning techniques. The proposed system introduces a step characterization module that characterizes the step according to the activity that the pedestrian is performing. This module performs three characterizations: terrain, direction and length. Thus, in this work are presented and evaluated several machine learning approaches that perform the terrain characterization. The inclusion of this machine learning module led to a significantly better performance of the pedestrian inertial navigation system. © 2015 SERSC.

关键词： Inertial navigation systems

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Simulation and control of consumption and generation of hardware resources in microgrid real-time digital simulator

Simulation and control of consumption and generation of hard...

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IEEE PES Conference on Innovative Smart Grid Technologies (ISGT Latin America)

作者： Omid Abrishambaf Luis Gomes Pedro Faria Zita Vale Polytechnic of Porto (IPP) GECAD - Knowledge Engineering and Decision Support Research Centre Porto Portugal

The appearance of new concepts in power systems, such as, smart grids and microgrids brings several advantages. This includes the use of distributed generation and the execution of demand response programs. However, their implementation can also bring management and stability problems. The system presented in this paper allows the real-time simulation of microgrids using real generation and consumption resources. The proposed system can follow real profiles and reply them into the simulation by using real loads and wind generation. The focus is given to the control of the resources in each desired consumption and generation requirement. The case studies use a real consumption profile of a residential house, small commerce facility and a real profile of a home-scale wind turbine. The use of real loads gives a more reliable simulation.

关键词： Load modeling Real-time systems Wind turbines Smart grids Hardware Microgrids Relays

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Demand Response in Electric Vehicles Management Optimal Use of End-User Contracts

Demand Response in Electric Vehicles Management Optimal Use ...

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Mexican International Conference on Artificial Intelligence, MICAI

作者： João Soares Zita Vale Hugo Morais Nuno Borges GECAD - Knowledge Engineering and Decision-Support Research Centre Polytechnic of Porto (ISEP/ IPP) Porto Portugal

Demand Response (DR) has gained attention in the past few years. With the mass introduction of Electric Vehicles (EVs) the opportunity for DR programs can grow even more. This paper concentrates on a specific type of DR, namely evaluating different scenarios with respect to end-user EVs tariffs. The effects of different tariffs are compared in several scenarios in terms of the Virtual Power Plant (VPP) operation costs and also the EVs' perspective, i.e. considering the optimal use of end-user contracts. To solve the Mixed Integer Non-Linear Problem (MINLP) a modernized optimization approach is used by combining a deterministic method in the first stage, relaxing the problem to a Mixed Integer Linear Problem (MILP) with the use of a computational intelligence method in the second stage, namely Particle Swarm Optimization (PSO). The case study presents different price scenarios, namely, singletariff, bi-tariff, tri-tariff, tetra-tariff, and Real-Time Pricing (RTP). The network used for this application is a 33-bus distribution network with high penetration of renewables and a fleet of 30 electric buses.

关键词： Energy resources Contracts Power generation Vehicles Load management Optimization Pricing

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Hour-ahead Energy Resource Management in University Campus Microgrid

Hour-ahead Energy Resource Management in University Campus M...

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IEEE Eindhoven PowerTech Conference

作者： M. Silva F. Fernandes H. Morais S. Ramos Z. Vale GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal Department of Electrical Engineering Technical University of Denmark (DTU) Lyngby Denmark

The management of intermittent energy resources by a microgrid operator (MGO) are a key aspect of future smart grids. A microgrid allows act as a single controllable entity and can operate in both grid-connected or in islanded mode. The present paper proposes a platform to be used by MGO regarding the energy resource management in smart grids and considering day-ahead and hour-ahead time-horizons. This method considers that the energy resources are managed by a MGO that establishes contracts with their client. The operator is able to manage the consumption and generation resources, also including demand response programs, obtaining profits from selling electricity to the main network. The model uses full AC power flow and the energy buying and selling from/to the main network. The case study considers the internal low voltage distribution network of a real university campus, and the projection of distributed energy resources based on the evolution scenario for the year 2050.

关键词： Day-ahead scheduling Distributed Energy Resources Hour-ahead scheduling Microgrid operator

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Energy resource management under the influence of the weekend transition considering an intensive use of electric vehicles

Energy resource management under the influence of the weeken...

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Clemson University Power Systems Conference (PSC)

作者： T. Sousa H. Morais T. Pinto Z. Vale GECAD –Knowledge Engineering and Decision Support Research Center IPP –Polytechnic Institute of Porto Porto Portugal Department of Electrical Engineering Technical University of Denmark (DTU) Lyngby Denmark

Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with their owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps. The full AC power flow calculation included in the model takes into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33-bus distribution network and V2G is used to illustrate the good performance of the proposed method.

关键词： Batteries Load modeling Discharges (electric) Energy resources Optimal scheduling Scheduling Electric vehicles

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A survey on smart meeting rooms and open issues

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International Journal of Smart Home 2015年第9期9卷 13-20页

作者： Freitas, Carlos Filipe Barroso, João Ramos, Carlos GECAD - Knowledge Engineering and Decision Support Research Center ISEP - Institute of Engineering Polytechnic of Porto Porto Portugal UTAD - Universidade de Trás os Montes e Alto Douto Vila Real Portugal

decision Making is one of the most important activities of the human being. Nowadays decisions imply to consider many different points of view, so decisions are commonly taken by formal or informal groups of persons. Groups exchange ideas or engage in a process of argumentation and counter-argumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. Smart Meeting Rooms (SMR) are the election spaces where groups can perform these activities in a local or distributed setting. SMR definition has evolved and in this article we present its evolution side by side with several projects that have been developed during the last decade. We also present the features and evaluation methods present in literature and we make a discussion on the open issues. © 2015 SERSC.

关键词： Problem solving

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Analysis of strategic wind power participation in energy market using MASCEM simulator

Analysis of strategic wind power participation in energy mar...

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

作者： Tiago Soares Gabriel Santos Tiago Pinto Hugo Morais Pierre Pinson Zita Vale Department of Electrical Engineering Technical University of Denmark (DTU) Akademivej Kgs. Lyngby Denmark GECAD - Knowledge Engineering and Decision Support Research Center IPP — Polytechnic Institute of Porto Porto Portugal

In recent years the reassessment of remuneration schemes for renewable sources in several European countries has motivated the increase of wind power generation participation in electricity markets. Moreover, the continuous growth of wind power generation, as well as the evolution of wind turbines technology, suggests that wind power plants may participate in both energy and ancillary services markets with strategic behavior to improve their benefits. Thus, wind power generation with strategic behavior may have impact on market equilibrium and pricing. This paper evaluates the impact of a proportional offering strategy for wind power plants to participate in both energy and ancillary services markets. MASCEM (Multi-Agent System for Competitive Electricity Markets) is used to simulate and validate the impact of wind power plants in market equilibrium. A case study based on real and recent data for the Iberian market and its specific rules is simulated in MASCEM.

关键词： Wind power generation Electricity supply industry Wind Green products Context Remuneration Power systems

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Day-ahead distributed energy resource scheduling using differential search algorithm

Day-ahead distributed energy resource scheduling using diffe...

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

作者： J. Soares C. Lobo M. Silva Z. Vale H. Morais GECAD - Knowledge Engineering and Decision-Support Research Center Polytechnic of Porto (ISEP/IPP) Porto Portugal Department of Electrical Engineering Technical University of Denmark (DTU) Kgs. Lyngby DK Denmark

The number of dispersed energy resources is growing every day, such as the use of more distributed generators. This paper deals with energy resource scheduling model in future smart grids. The methodology can be used by virtual power players (VPPs) considering day-ahead time horizon. This method considers that energy resources are managed by a VPP which establishes contracts with their owners. The full AC power flow calculation included in the model takes into account network constraints. This paper presents an application of differential search algorithm (DSA) for solving the day-ahead scheduling. DSA method is used to minimize the operation costs for the VPP providing in satisfactory execution time. Two scenarios are presented using a 33-bus distribution network, large wind farm and several distributed energy resources to illustrate the proposed methodology. These scenarios consider a contingency on the large wind farm and different forecasts regarding load demand.

关键词： Optimization Wind farms Scheduling Generators Load management Power generation

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