O impacto energético e as emissões de CO2 dos veículos eléctricos em Portugal

Para a diminuição da dependência energética de Portugal face às importações de energia, a Estratégia Nacional para a Energia 2020 (ENE 2020) define uma aposta na produção de energia a partir de fontes renováveis, na promoção da eficiência energética tanto nos edifícios como nos transportes com vista a reduzir as emissões de gases com efeito de estufa. No campo da eficiência energética, o ENE 2020 pretende obter uma poupança energética de 9,8% face a valores de 2008, traduzindo-se em perto de 1800 milhões de tep já em 2015. Uma das medidas passa pela aposta na mobilidade eléctrica, onde se prevê que os veículos eléctricos possam contribuir significativamente para a redução do consumo de combustível e por conseguinte, para a redução das emissões de CO2 para a atmosfera. No entanto, esta redução está condicionada pelas fontes de energia utilizadas para o abastecimento das baterias. Neste estudo foram determinados os consumos de combustível e as emissões de CO2 de um veículo de combustão interna adimensional representativo do parque automóvel. É também estimada a previsão de crescimento do parque automóvel num cenário "Business-as-Usual", através dos métodos de previsão tecnológica para o horizonte 2010-2030, bem como cenários de penetração de veículos eléctricos para o mesmo período com base no método de Fisher- Pry. É ainda analisado o impacto que a introdução dos veículos eléctricos tem ao nível dos consumos de combustível, das emissões de dióxido de carbono e qual o impacto que tal medida terá na rede eléctrica, nomeadamente no diagrama de carga e no nível de emissões de CO2 do Sistema Electroprodutor Nacional. Por fim, é avaliado o impacto dos veículos eléctricos no diagrama de carga diário português, com base em vários perfis de carga das baterias. A introdução de veículos eléctricos em Portugal terá pouca expressão dado que, no melhor dos cenários haverão somente cerca de 85 mil unidades em circulação, no ano de 2030. Ao nível do consumo de combustíveis rodoviários, os veículos eléctricos poderão vir a reduzir o consumo de gasolina até 0,52% e até 0,27% no consumo de diesel, entre 2010 e 2030, contribuindo ligeiramente uma menor dependência energética externa. Ao nível do consumo eléctrico, o abastecimento das baterias dos veículos eléctricos representará até 0,5% do consumo eléctrico total, sendo que parte desse abastecimento será garantido através de centrais de ciclo combinado a gás natural. Apesar da maior utilização deste tipo de centrais térmicas para produção de energia, tanto para abastecimento das viaturas eléctricas, como para o consumo em geral, verifica-se que em 2030, o nível de emissões do sistema electroprodutor será cerca de 46% inferior aos níveis registados em 2010, prevendo-se que atinja as 0,163gCO2/kWh produzido pelo Sistema Electroprodutor Nacional devido à maior quota de produção das fontes de energia renovável, como o vento, a hídrica ou a solar.

Aumento de energia renovável na Ilha da Madeira: proposta integrada para o setor dos transportes e da geração de energia elétrica

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Impacto económico, energético e ambiental da produção renovável na Ilha Terceira

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Distributed MPC for Thermal Comfort and Load Allocation with Energy Auction

This paper presents a distributed predictive control methodology for indoor thermal comfort that optimizes the consumption of a limited shared energy resource using an integrated demand-side management approach that involves a power price auction and an appliance loads allocation scheme. The control objective for each subsystem (house or building) aims to minimize the energy cost while maintaining the indoor temperature inside comfort limits. In a distributed coordinated multi-agent ecosystem, each house or building control agent achieves its objectives while sharing, among them, the available energy through the introduction of particular coupling constraints in their underlying optimization problem. Coordination is maintained by a daily green energy auction bring in a demand-side management approach. Also the implemented distributed MPC algorithm is described and validated with simulation studies.

Metaheuristic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Metaheuristhic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.

Is the electric vehicle a solution for the wind power integration in the portuguese power system?

The integration of Plug-in electric vehicles in the transportation sector has a great potential to reduce oil dependency, the GHG emissions and to contribute for the integration of renewable sources into the electricity generation mix. Portugal has a high share of wind energy, and curtailment may occur, especially during the off-peak hours with high levels of hydro generation. In this context, the electric vehicles, seen as a distributed storage system, can help to reduce the potential wind curtailments and, therefore, increase the integration of wind power into the power system. In order to assess the energy and environmental benefits of this integration, a methodology based on a unit commitment and economic dispatch is adapted and implemented. From this methodology, the thermal generation costs, the CO2 emissions and the potential wind generation curtailment are computed. Simulation results show that a 10% penetration of electric vehicles in the Portuguese fleet would increase electrical load by 3% and reduce wind curtailment by only 26%. This results from the fact that the additional generation required to supply the electric vehicles is mostly thermal. The computed CO2 emissions of the EV are 92 g CO2/kWh which become closer to those of some new ICE engines.

Personalized public transportation information

Thesis to obtain the Master of Science Degree in Computer Science and Engineering