A comparative study of alternative approaches for common factors identification

Preliminary version

The electric vehicle integration into the power system: an application to the portuguese case

Electric vehicles (EV) offer a great potential to address the integration of renewable energy sources (RES) in the power grid, and thus reduce the dependence on oil as well as the greenhouse gases (GHG) emissions. The high share of wind energy in the Portuguese energy mix expected for 2020 can led to eventual curtailment, especially during the winter when high levels of hydro generation occur. In this paper a methodology based on a unit commitment and economic dispatch is implemented, and a hydro-thermal dispatch is performed in order to evaluate the impact of the EVs integration into the grid. Results show that the considered 10 % penetration of EVs in the Portuguese fleet would increase load in 3 % and would not integrate a significant amount of wind energy because curtailment is already reduced in the absence of EVs. According to the results, the EV is charged mostly with thermal generation and the associated emissions are much higher than if they were calculated based on the generation mix.

Gamma radiation effects on microbial inactivation of two medicinal plants

The consumption of natural products has become a public health problem, since these medicinal teas are prepared using natural plants without an effective hygienic and sanitary control. The aim of this study was to assess the effects of gamma radiation, on the microbial burden of two medicinal plants: Melissa officinalis and Lippia citriodora. Dried samples of the two plants were irradiated at a Co-60 experimental equipment. The applied gamma radiation doses were 1, 3, and 5 kGy at a dose rate of 1.34 kGy/h. Non-irradiated samples followed all the experiments. Bacterial and fungal counts were assessed before and after irradiation by membrane filtration method. Challenging tests with Escherichia coli were performed in order to evaluate the disinfection efficiency of gamma radiation treatment. Characterization of M. officinalis and L. citriadora microbiota indicated an average bioburden value of 102CFU/g. The inactivation studies of the bacterial mesophilic population of both dried plants pointed out to a one log reduction of microbial load after irradiation at 5 kGy. Regarding the fungal population, the initial load of 30 CFU/g was only reduced by 0.5 log by an irradiation dose of 5 kGy. The dynamics with radiation doses of plants microbial population’s phenotypes indicated the prevalence of gram-positive rods for M. officinalis before and after irradiation, and the increase of the frequency of gram-negative rods with irradiation for L. citriadora. Among fungal population of both plants, Mucor, Neoscytalidium, Aspergillus and Alternaria were the most isolated genera. The results obtained in the challenging tests with E. coli on plants pointed out to an inactivation efficiency of 99.5% and 99.9% to a dose of 2 kGy, for M.officinalis and L. citriadora, respectively. The gamma radiation treatment can be a significant tool for the microbial control in medicinal plants.

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.

Renewable energy in Islands: an integrated proposal for electricity generation and transports

The purpose of this article is to analyse and evaluate the economical, energetic and environmental impacts of the increasing penetration of renewable energies and electrical vehicles in isolated systems, such as Terceira Island in Azores and Madeira Island. Given the fact that the islands are extremely dependent on the importation of fossil fuels - not only for the production of energy, but also for the transportation’s sector – it’s intended to analyse how it is possible to reduce that dependency and determine the resultant reduction of pollutant gas emissions. Different settings have been analysed - with and without the penetration of EVs. The Terceira Island is an interesting case study, where EVs charging during off-peak hours could allow an increase in geothermal power, limited by the valley of power demand. The percentage of renewable energy in the electric power mix could reach the 74% in 2030 while at the same time, it is possible to reduce the emissions of pollutant gases in 45% and the purchase of fossil fuels in 44%. In Madeira, apart from wind, solar and small hydro power, there are not so many endogenous resources and the Island’s emission factor cannot be so reduced as in Terceira. Although, it is possible to reduce fossil fuels imports and emissions in 1.8% in 2030 when compared with a BAU scenario with a 14% of the LD fleet composed by EVs.

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.

Renewable energy in Islands: an integrated proposal for electricity generation and transports

The purpose of this article is to analyse and evaluate the economical, energetic and environmental impacts of the increasing penetration of renewable energies and electrical vehicles in isolated systems, such as Terceira Island in Azores and Madeira Island. Given the fact that the islands are extremely dependent on the importation of fossil fuels - not only for the production of energy, but also for the transportation’s sector – it’s intended to analyse how it is possible to reduce that dependency and determine the resultant reduction of pollutant gas emissions. Different settings have been analysed - with and without the penetration of EVs. The Terceira Island is an interesting case study, where EVs charging during off-peak hours could allow an increase in geothermal power, limited by the valley of power demand. The percentage of renewable energy in the electric power mix could reach the 74% in 2030 while at the same time, it is possible to reduce the emissions of pollutant gases in 45% and the purchase of fossil fuels in 44%. In Madeira, apart from wind, solar and small hydro power, there are not so many endogenous resources and the Island’s emission factor cannot be so reduced as in Terceira. Although, it is possible to reduce fossil fuels imports and emissions in 1.8% in 2030 when compared with a BAU scenario with a 14% of the LD fleet composed by EVs.

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.

Corrugated horn antenna for a CosmoGal satellite with reduced dimensions

This paper presents the design methodology for the creation of corrugated horn antennas for the CosmoGal satellite. The mission will collect the radiation of the cosmic microwave background, by a radiometer in three different radio astronomy frequency bands (10.6-10.7GHz; 15.35-15.4GHz; 23.6-24GHz). It is discussed the design of several types of horns, simulated with the CST software. The best result points to a choked Gaussian corrugated horn antenna, with directivity of 23 dBi, side lobes 35 dB below and cross polarization better than -45 dB. Plus, with the advantage of having a small dimension, with a total length of only 7.43λ © 2014 IEEE.

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.

Fabrication of electrochemically reduced graphene oxide/cobalt oxide composite for charge storage electrodes

Electrochemically-reduced graphene oxide (Er-GO) and cobalt oxides (CoOx) were co-electrodeposited by cyclic voltammetry, from an electrolyte containing graphene oxide and cobalt nitrate, directly onto a stainless steel substrate to produce composite electrodes presenting high charge storage capacity. The electrochemical response of the composite films was optimized by studying the parameters applied during the electrodeposition process, namely the number of cycles, scan rate and ratio between GO/Co(NO3)(2) concentrations in the electrolyte. It is shown that, if the appropriate conditions are selected, it is possible to produced binder-free composite electrodes with improved electrochemical properties using a low-cost, facile and scalable technique. The optimized Er-GO/CoOx developed in this work exhibits a specific capacitance of 608 F g(-1) at a current density of 1 A g(-1) and increased reversibility when compared to single CoOx. (C) 2015 Elsevier B.V. All rights reserved.