Research Interests:
Research Interests:
This work discusses the solution of a Large-scale global optimization problem named Security Constrained Optimal Power Flow (SCOPF) using a method based on Cross Entropy (CE) and Evolutionary Particle Swarm Optimization (EPSO). The... more
This work discusses the solution of a Large-scale global optimization problem named Security Constrained Optimal Power Flow (SCOPF) using a method based on Cross Entropy (CE) and Evolutionary Particle Swarm Optimization (EPSO). The obtained solution is compared to the Entropy Enhanced Covariance Matrix Adaptation Evolution Strategy (EE-CMAES) and Shrinking Net Algorithm (SNA). Experiments show the approach reaches competitive results.
Research Interests:
Research Interests:
Research Interests:
The Unit Commitment (UC) problem consists on the day-ahead scheduling of thermal generation units. The scheduling process is based on a forecast for the demand, which adds uncertainty to the decision of starting or shutting down units.... more
The Unit Commitment (UC) problem consists on the day-ahead scheduling of thermal generation units. The scheduling process is based on a forecast for the demand, which adds uncertainty to the decision of starting or shutting down units. With the increasing penetration of renewable energy sources, namely wind power, the level of uncertainty is such that deterministic UC approaches that rely uniquely on point forecasts are no longer appropriate. The UC approach reported in this paper considers a stochastic formulation and includes constraints for the technical limits of thermal generation units, like ramp-rates and minimum and maximum power output, and also for the power flow equations by integrating the DC model in the optimization process. The objective is to assess the ability of the stochastic UC approach to decrease the expected value of load shedding and wind power loss when compared to the deterministic UC approach. A case study based on IEEE-RTS 79 system, which has 24 buses and 32 thermal generation units, for two different penetrations of wind power and a 24-hour horizon is carried out. The computational performance of the methodology proposed is also discussed to show that considerable performance gains without compromising the robustness of the stochastic UC approach can be achieved.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
This paper presents a model for supporting the investment planning decision-making from the perspective of an independent energy provider that wants to integrate Battery Energy Storage Systems (BESS) in distribution networks. For... more
This paper presents a model for supporting the investment planning decision-making from the perspective of an independent energy provider that wants to integrate Battery Energy Storage Systems (BESS) in distribution networks. For supporting the decision, a conditional set of economically viable optimal solutions for the business model of buying and selling energy is identified in order to allow other decision criteria (e.g. loss reduction, reliability, ancillary services, etc.) to be evaluated to enhance the economic benefits as the result of the synergy between different applications of BESS. For this, a novel approach optimization model based on the metaheuristic Differential Evolutionary Particle Swarm optimization (DEEPSO) and the Group Method Data Handling (GMDH) neural network is proposed for sizing, location, and BESS operation schedule. Experimental results indicate that after identifying the breakeven cost of the business model, a good conditional decision set can be obtained for assessing then other business alternatives.
Research Interests:
Research Interests:
When the COVID-19 pandemic hits Portugal in early March 2020, medical doctors, engineers and researchers, with the encouragement of the Northern Region Health Administration, teamed up to develop and build, locally and in a short time, a... more
When the COVID-19 pandemic hits Portugal in early March 2020, medical doctors, engineers and researchers, with the encouragement of the Northern Region Health Administration, teamed up to develop and build, locally and in a short time, a ventilator that might eventually be used in extreme emergency situations in the hospitals of northern Portugal. This letter tells you the story of Pneuma, a low-cost emergency ventilator designed and built under harsh isolation constraints, that gave birth to derivative designs in Brazil and Morocco, has been industrialized with 200 units being produced and is now looking forward to the certification as a medical device that will possibly support a go-to-market launch. Open intellectual property (IP), multidisciplinarity teamwork, fast prototyping and product engineering have shortened to a few months an otherwise quite longer idea-to-product route, clearly demonstrating that when scientific and engineering knowledge hold hands great challenges can ...
Research Interests:
Research Interests:
This paper reports the use of Artificial Neural Networks (ANN) for fast and accurate evaluation of the transient stability degree for each contingency in a multimachine power system, using only real time monitorable system values. The... more
This paper reports the use of Artificial Neural Networks (ANN) for fast and accurate evaluation of the transient stability degree for each contingency in a multimachine power system, using only real time monitorable system values. The output of an ANN provides an emulation of the transient stability energy margin. Preventive control measures can be suggested through generation load redispatch, by getting the sensitivities of the energy margin directly from a trained ANN. The approach was tested with several contingencies in the CIGRE test system, giving better results than other methods so far reported in the literature.
Research Interests:
Neuralnetworks havebroadapplicability to realpowersystemproblems. Oneoftheareasinpower systemwithhugeinterest inappliance ofneural networks is loadforecasting. Inthispapertheneuralnetworks were trained andtested using15-minute... more
Neuralnetworks havebroadapplicability to realpowersystemproblems. Oneoftheareasinpower systemwithhugeinterest inappliance ofneural networks is loadforecasting. Inthispapertheneuralnetworks were trained andtested using15-minute loaddatacollected in Portugal bytheelectric powercompanyEDP during a44 dayperiod. Theartificial neural networks showedasagood nonlinear approximator, giving promising results. Themain objective ofthepresented work isto interest power companiesin the Regionfor possible practical implementations. Keywordsartificial neural networks, loaddiagram, short termloadforecast
Research Interests:
Research Interests:
Research Interests:
Research Interests:
A estimacao de estado se constitui na parte mais importante de aplicativos computacionais avancados responsaveis por monitorar, controlar e otimizar o desempenho de redes eletricas. Seu principal objetivo esta em fornecer um conjunto de... more
A estimacao de estado se constitui na parte mais importante de aplicativos computacionais avancados responsaveis por monitorar, controlar e otimizar o desempenho de redes eletricas. Seu principal objetivo esta em fornecer um conjunto de dados de tempo real, completo e confiavel, para ser usado em sistemas de gerenciamento de energia. Para a estimacao de estado, observabilidade representa a faculdade de ver (em certo grau) o estado operativo atual do sistema. Assim sendo, torna-se vital avaliar esta capacidade, especialmente em termos quantitativos. Neste trabalho, propoe-se uma avaliacao probabilistica da capa-cidade de observacao da funcao estimacao de estado. Indicadores que expressam o risco de a estimacao de estado ser incapaz de observar a rede como um todo e processar erros grosseiros adequadamente sao concebidos. Eventos criticos que podem degradar o desempenho desta ferramenta sao caracterizados e representados por meio de um modelo probabilistico simples. Apresenta-se tambem uma abordagem baseada na simulacao de Monte Carlo para o calculo dos indicadores propostos. Resultados numericos de estudos de simulacao conduzidos no sistema IEEE 30-barras ilustram a metodologia proposta.
Research Interests: Physics and Humanities
Research Interests:
Research Interests:
Research Interests:
In this paper we present a complete methodology to perform state estimation studies in distribution networks. Due to the peculiarities of these networks the traditional state estimation concept was enlarged in different ways. It includes... more
In this paper we present a complete methodology to perform state estimation studies in distribution networks. Due to the peculiarities of these networks the traditional state estimation concept was enlarged in different ways. It includes a load allocation study, as a way to cope with the reduced number of real time measurements in SCADA database. The algorithm estimates binary values of topology variables, due to incomplete or erroneous topology information in the control center and it is able to include data modeled by fuzzy numbers as a way to include fuzzy results of the load allocation procedure or fuzzy assessments from experts. Finally, the paper describes a methodology developed to tune the weights to be used in the state estimation based on a Takagi-Sugeno fuzzy inference system. The paper includes a case study based in the IEEE 24 bus system to highlight and illustrate its application in a variety of situations
Research Interests:
Research Interests:
Research Interests:
A fuzzy AC load flow model is presented in which fuzzy data are used to obtain possibility distributions of voltages, active and reactive flows and losses, currents, and generated powers. These distributions are compared with the ones... more
A fuzzy AC load flow model is presented in which fuzzy data are used to obtain possibility distributions of voltages, active and reactive flows and losses, currents, and generated powers. These distributions are compared with the ones obtained through a Monte Carlo based simulation in order to evaluate the errors inherent to the fuzzy AC load flow
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Strong adoption dynamics of private passenger electric vehicles (EV) will require adjustments in the operation and planning of electrical distribution grids. This work proposes a novel approach to assess the impact of electric vehicle... more
Strong adoption dynamics of private passenger electric vehicles (EV) will require adjustments in the operation and planning of electrical distribution grids. This work proposes a novel approach to assess the impact of electric vehicle charging while considering EV adoption dynamics and commuting patterns. The proposed model uses Geographic Information Systems (GIS) and is applied to a real-world case study. Results suggest that clustering of EV charging will occur and underline the relevance of accurate spatial and temporal charging pattern estimations for distribution grid planning. Overloading of distribution network elements was observed even under light EV penetration rates.
Research Interests:
ABSTRACT
Research Interests:
Research Interests:
Many studies addressing the effect of wi nd power integration strategies on the system adequacy assessment have been made, only concerning the genera tion point of view and usually disregarding the effect o f the transmission network. On... more
Many studies addressing the effect of wi nd power integration strategies on the system adequacy assessment have been made, only concerning the genera tion point of view and usually disregarding the effect o f the transmission network. On the other hand, studies co nsidering the transmission network usually have ignored the effect of wind power integration strategies, focusi ng only on capturing the time dependent nature of this type of renewable energy source. Therefore, this work prese nts a chronological Monte Carlo simulation approach that assesses the system adequacy of composite systems (ge neration and transmission) considering non-dispatchable and dispatchable renewable energy production (wind and hydro, respectively). Case studies involving the IEE-RTS 79 and modified versions of this system are present ed and discussed as didactic examples.
Research Interests:
Research Interests:
The uptake of electric vehicles (EV) will require important modifications in traditional grid planning and load forecasting techniques. Existing literature suggests that the integration of EVs will be more adversarial to elements of the... more
The uptake of electric vehicles (EV) will require important modifications in traditional grid planning and load forecasting techniques. Existing literature suggests that the integration of EVs will be more adversarial to elements of the existing electricity infrastructure in terms of power supply (kW) than energy (kWh) delivery. While several studies analyzed the grid impact of electric vehicle fleets, few consider the adoption process itself which may lead to strong spatial variations of the utilization of charging infrastructure. The presented approach extends spatial load forecasting, introducing diffusion theory elements to analyze spatio-temporal clustering of EV charging demand. Using open-access census and grid data, this work develops a deterministic framework to forecast spatial patterns of EV charging applied to a real-world environment. Outcomes suggest substantial spatial clustering of EV adoption patterns, showing substation overrating for EV penetration rates of 25% and above with 7.4kW charging power.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Optimization problems in electric power systems under high levels of uncertainty have been solved using stochastic programming methods for years. This is especially the case for medium-term problems and systems with a large share of hydro... more
Optimization problems in electric power systems under high levels of uncertainty have been solved using stochastic programming methods for years. This is especially the case for medium-term problems and systems with a large share of hydro storages. The increased uncertainty in power system operation coming from volatile renewables has made the stochastic techniques interesting in shorter time frames as well. In the stochastic models the uncertainty is typically included by a discretized set of scenarios. This increases the computational burden significantly so a common approach is to preprocess and reduce the number of scenarios. Scenario reduction methods have been shown to function relatively well in expected value stochastic optimization. However, such setting of stochastic optimization is often criticized as being risk-prone so other risk-averse models exist. The evolutionary computation algorithms' flexibility permits the implementation of these risk models with relative simplicity. In this paper, a population-based evolutionary computation algorithm is applied to unit commitment problem under uncertainty and the paper illustrates several approaches to including risk policies in an evolutionary algorithm fitness function and illustrates its flexibility along with the link between scenario reduction similarity metric and risk policy.
Research Interests:
Research Interests: Economics, Environmental policy, Power System, European Union, Energy Consumption, and 15 moreElectricity Market, Federal Government, Electricity Consumption, Greenhouse Gas Emissions, Power System Operation, Electric Power System, Energy Storage, Economic Dispatch, Greenhouse gases, Energy efficient, Electric Power, Large Scale, Feed In Tariff, Energy Source, and Department of Energy
Research Interests: Engineering, Computer Science, Electricity Market, Event Detection, Quantile Regression, and 15 morePower Transmission, Uncertainty Estimation, Power System Operation, Kernel Density Estimation, Market Power, Gaussian distribution, Probabilistic Method, Training Algorithm, Electric Power, Indexation, Probability Density Function, Stochastic Algorithm, Statistical Approach, Information Theoretic Learning, and Kernel density
Research Interests:
Research Interests:
Research Interests:
... Mapa do Campus. Experiences in State Estimation Models for Distribution Systems Including Fuzzy Measures. Artigo em Livro de Actas de Conferência Internacional. Autores: Vladimiro Miranda Jorge Pereira João Tomé Saraiva. Idioma:... more
... Mapa do Campus. Experiences in State Estimation Models for Distribution Systems Including Fuzzy Measures. Artigo em Livro de Actas de Conferência Internacional. Autores: Vladimiro Miranda Jorge Pereira João Tomé Saraiva. Idioma: Português. Ano: 1995. ...