Scheduling distributed energy resources in an isolated grid - an artificial neural network approach

Power Systems (PS), have been affected by substantial penetration of Distributed Generation (DG) and the operation in competitive environments. The future PS will have to deal with large-scale integration of DG and other distributed energy resources (DER), such as storage means, and provide to market agents the means to ensure a flexible and secure operation. Virtual power players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. This paper proposes an artificial neural network (ANN) based methodology to support VPP resource schedule. The trained network is able to achieve good schedule results requiring modest computational means. A real data test case is presented.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Antibiotic resistance in enterobacteriaceae isolated from Portuguese deli meats

This study aimed to identify the presence of β-lactam-resistant bacteria in different types of Portuguese deli meats. The numbers of ampicillin resistant bacteria varied from negative in 25 g to 1.0 × 108colony-forming units/g. Within 78 randomly selected β-lactam-resistant bacteria, 24 different resistant phenotypes were found and 35.9% were multidrug resistant (MDR). The majority (87.2%) of the isolates identified belonged to the Enterobacteriaceae family. The presence of the blaTEM gene was detected in 23 out of 67 isolates (34.3%) and 16 of them presented MDR phenotypes. Four Klebsiella oxytoca isolates (6%) harbored a gene for the CTX-M/OXY-type enzyme. The direct sequencing of their purified amplicons confirmed the presence of three types of blaOXYgenes (blaOXY-1, blaOXY-2 and blaOXY-5). These results suggest that without good hygienic practices, deli meats may act as a vehicle of transfer of β-lactam-resistant bacteria to the gastrointestinal tract of consumers.

In vitro transference and molecular characterization of bla TEM genes in bacteria isolated from Portuguese ready-to-eat foods

The principal aim of this study was to investigate the possibility of transference to Escherichia coli of β-lactam resistance genes found in bacteria isolated from ready-to-eat (RTE) Portuguese traditional food. From previous screenings, 128 β-lactam resistant isolates (from different types of cheese and of delicatessen meats), largely from the Enterobacteriaceae family were selected and 31.3% of them proved to transfer resistance determinants in transconjugation assays. Multiplex PCR in donor and transconjugant isolates did not detect bla CTX, bla SHV and bla OXY, but bla TEM was present in 85% of them, while two new TEMs (TEM-179 and TEM-180) were identified in two isolates. The sequencing of these amplicons showed identity between donor and transconjugant genes indicating in vitro plasmid DNA transfer. These results suggest that if there is an exchange of genes in natural conditions, the consumption of RTE foods, particularly with high levels of Enterobacteriaceae, can contribute to the spread of antibiotic resistance.

Diversity and characterisation of coagulasenegative staphylococci isolated from healthy individuals in Portugal

In the past few years the interest in coagulase-negative staphylococci (CoNS) has significantly increased in human medicine. CoNS are common commensal colonisers of the human skin, although now also recognised as major nosocomial pathogens. Over the last decades, several studies have been carried out in order to understand the pathogenicity mechanisms of CoNS. The well known determinants in the pathogenesis of CoNS infections are their ability to form biofilms and an exceptional resistance to several antibiotics. Nevertheless, there is a lack of studies regarding the commensal lifestyle of these microorganisms. Additionally, it is now hypothesised that commensal bacteria might be a reservoir of pathogenic determinants. Therefore, the work described throughout this thesis was aimed to perform a phenotypic and genotypic characterisation of different CoNS species isolated from healthy Portuguese individuals. A total of 61 CoNS isolates, comprising 7 different species, were obtained and characterised at the level of biofilm formation and antibiotic susceptibility profiles. According to the results, biofilm formation ability and presence of biofilm-associated genes were commonly found features, highlighting their pivotal role in the colonising lifestyle of CoNS. This study also addressed the correlation between phenotypic and genotypic characteristics of biofilm formation, corroborating and raising questions about the importance of some genes in this process. Moreover, it was observed a great proportion of isolates with decreased susceptibility and multiple resistances to some important antibiotics. A significant association between antibiotic resistance and biofilm formation was also demonstrated, and some hypotheses about the nature of such association were provided. Lastly, the expression patterns of two biofilm-associated genes at two distinct biofilm developmental stages were determined, confirming their importance in the accumulative stage of biofilm formation. Overall, the results presented in this thesis indicate that staphylococcal skin flora might be an important reservoir of potentially pathogenic bacteria and, simultaneously, bring to light new perceptions about the molecular basis of staphylococcal biofilm formation, and the nature of the association between antibiotic resistance and biofilm formation.