987 resultados para Load conformity factors
Resumo:
The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.
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With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.
Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems
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This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.
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With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.
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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.
Resumo:
A supervisory control and data acquisition (SCADA) system is an integrated platform that incorporates several components and it has been applied in the field of power systems and several engineering applications to monitor, operate and control a lot of processes. In the future electrical networks, SCADA systems are essential for an intelligent management of resources like distributed generation and demand response, implemented in the smart grid context. This paper presents a SCADA system for a typical residential house. The application is implemented on MOVICON™11 software. The main objective is to manage the residential consumption, reducing or curtailing loads to keep the power consumption in or below a specified setpoint, imposed by the costumer and the generation availability.
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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.
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Animal confinement tends to increase the overall microbial load in the production environment caused by high amounts of feed and organic residuals (manure and wastewater) present in those environments. The number of animais and the handling and management required to work in these settings also contribute to enhance that microbial ioad. Animal housing typically exposes workers to substantial concentrations of bioaerosols, such as fungi and their metabolites. Therefore, agricultural workers, and especially pig and poultry farmers, are at increased risk of occupational respiratory diseases. Exposure to bioaerosols in poultries and swines may vary depending upon the stage of the animals' growth, density, manure management procedures, litter type and used floor coverage, among others. Gathering temporal information about the quantity and the composition of fungal load is necessary to better understand the relationship between these factors and adverse health symptoms of workers. This study aimed to characterize and compare fungal contamination between these two different settings.
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OBJECTIVE: To assess factors associated with infant feeding practices on the first day at home after hospital discharge. METHODS: A total of 209 women, who had a child aged four months or less and were living in Itapira, Brazil, were interviewed during the National Immunization Campaign Day in 1999. Statistical analysis was performed using the Chi-square test and a logistic regression model was used for verifying an association between dependent and independent variables. RESULTS: Women aged 25.5 years on average and 18.2% were teenagers. Fifty-three percent of the women delivered vaginally and most vaginal deliveries (78.5%) took place in the public hospital. The prevalence of exclusive breastfeeding on the first day at home was 78.1% and 11.6% of the infants were receiving formula at this time. The only factor associated with EBF on the first day at home was being a teenaged-primiparous mother (OR=9.40; 95% CI: 1.24-71.27). This association remained statistically significant even after controlling for type of delivery and hospital where the birth took place. Feeding formula on the first day at home was only significantly associated with the hospital (i.e., birth at the city hospital was a protective factor (OR=0.33; 95% CI: 0.13-0.86), even after controlling for vaginal delivery. CONCLUSIONS: On the first day at home after hospital discharge, teenaged-primiparous mothers were more likely to exclusive breastfeeding as well as those infants born in the municipal public hospital. Further studies are needed from a multidisciplinary approach.
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OBJECTIVE: To determine the intensity of Pediculus capitis infestation (abundance) among Argentinean schoolchildren. Children's sex and social stratum were analyzed as modifiers of the general prevalence and degree of parasitism. METHODS: The study included 1,370 schoolchildren (692 girls, 678 boys) from 26 schools of the province of La Rioja (21 public schools, five private schools). Classic prevalence was obtained as the percentage of children with nits and/or lice. Moreover, five degrees of parasitism were classified: 0) children with no signs of pediculosis; 0+) children with evidence of past infestation; 1) children with a recent infestation and low probability of active parasitism; 2) children with a recent infestation and high probability of active parasitism; 3) children with mobile lice (active pediculosis). RESULTS: The general prevalence was 61.4% (girls: 79%; boys: 44%, p<0.001). Private schools showed lower prevalence than public schools (p=0.02), especially due to the low prevalence in boys. Fifty percent of children were classified in classes 0 and 0+, 22% in class 1; and 28% in grades 2 and 3. The proportion of children in grade 3 was higher in public schools than in private schools. There were significant sexual differences in the intensity of parasitism for grades 2 and 3, where girls' rates exceeded twice those of boys'. CONCLUSIONS: Sex and social stratum are important modifiers of P. capitis general prevalence and degree of infestation. The classification of children by intensity of infestation allowed a more precise delimitation of this condition, which is especially important for disease surveillance and application of control measures.
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OBJECTIVE: To describe the characteristics and associated factors of the smoking habit among older adults. METHODS: A population-based study was carried out comprising 1,606 (92.2%) older adults (>60 years old) living in the Bambuí town, Southeastern Brazil in 1997. Data was obtained by means of interview and socio-demographic factors, health status, physical functioning, use of healthcare services and medication were considered. The multiple multinomial logistic regression was used to assess independent associations between smoking habits (current and former smokers) and the exploratory variables. RESULTS: The prevalence of current and past smoking was 31.4% and 40.2% among men, and 10.3% and 11.2% among women, respectively (p<0.001). Among current smokers, men consumed a larger number of cigarettes per day and started the habit earlier than women. Among men, current smoking presented independent and negative association with age (>80 years) and schooling (>8 years) and positive association with poor health perception and not being married. Among women, independent and negative associations with current smoking were observed for age (75-79 and >80 years) and schooling (4-7 and >8 years). CONCLUSIONS: Smoking was a public health concern among older adults in the studied community, particularly for men. Yet, in a low schooling population, a slightly higher level was a protective factor against smoking for both men and women. Programs for reducing smoking in the elderly population should take these findings into consideration.
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Objective: To assess different factors influencing adiponectinemia in obese and normal-weight women; to identify factors associated with the variation (Δ) in adiponectinemia in obese women following a 6-month weight loss program, according to surgical/non-surgical interventions. Methods: We studied 100 normal-weight women and 112 obese premenopausal women; none of them was on any medical treatment. Women were characterized for anthropometrics, daily macronutrient intake, smoking status, contraceptives use, adiponectin as well as IL-6 and TNF-α serum concentrations. Results: Adiponectinemia was lower in obese women (p < 0.001), revealing an inverse association with waist-to-hip ratio (p < 0.001; r = –0.335). Normal-weight women presented lower adiponectinemia among smokers (p = 0.041); body fat, waist-to-hip ratio, TNF-α levels, carbohydrate intake, and smoking all influence adiponectinemia (r 2 = 0.436). After weight loss interventions, a significant modification in macronutrient intake occurs followed by anthropometrics decrease (chiefly after bariatric procedures) and adiponectinemia increase (similar after surgical and non-surgical interventions). After bariatric intervention, Δ adiponectinemia was inversely correlated to Δ waist circumference and Δ carbohydrate intake (r 2 = 0.706). Conclusion: Anthropometrics, diet, smoking, and TNF-α levels all influence adiponectinemia in normal-weight women, although explaining less than 50% of it. In obese women, anthropometrics modestly explain adiponectinemia. Opposite to non-surgical interventions, after bariatric surgery adiponectinemia increase is largely explained by diet composition and anthropometric changes.
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OBJECTIVE: To examine the prevalence of body dissatisfaction and associated factors in 8- to 11-year-old schoolchildren. METHODS: A cross-sectional study including children aged 8- to 11-years enrolled in public and private schools in Porto Alegre, Southern Brazil, was carried out from August to December, 2001. A total of 901 subjects were selected through cluster sampling. Participants answered a questionnaire aimed at measuring body dissatisfaction and self-esteem and questions about family and social pressures on weight change. Height and weight were measured. The relationship between body dissatisfaction and the variables studied was measured by logistic regression. RESULTS: The prevalence of body dissatisfaction was 82%. Fifty-five percent of the girls wanted a thinner body size, and 28% desired a larger one; the estimates for the boys were 43% and 38%, respectively. Children with the lowest self-esteem (OR=1.80; 95% CI: 1.13-2.89) and who thought their parents (OR=6.10; 95% CI: 2.95-12.60) and friends (OR=1.81; 95% CI: 1.02-3.20) expected them to be thinner showed a higher chance of presenting body dissatisfaction. CONCLUSIONS: Body dissatisfaction was highly prevalent among the evaluated schoolchildren, especially in those with lower self-esteem and who thought their parents and friends expected them to be thinner.
Motivations and management factors of volunteer work in nonprofit organisations: a literature review
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The objective of this paper is to review and discuss the literature about volunteers’ motivations to donate their time to NPOs and the management factors that can influence volunteer work. Firstly, the paper illustrates and compares the different types of motivation followed by a presentation of a typology that organises the volunteers’ motivations into four types: (i) altruism, (ii) belonging, (iii) ego and social recognition and (iv) development and learning. Secondly we discuss the key management factors in volunteering: recruitment, training and rewarding. Finally, we present four gaps in the literature that justify the scope for further research: (i) omission of differences between motivations related to volunteers’ "Attraction" versus "Retention"; (ii) focus of the research on the USA, UK and Australia context; (iii) absence of comparative analyses that relate motivations by NPO types and (iv) comprehension of how management factors (recruitment, training and rewarding) influence volunteers’ satisfaction and retention.
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The objective of this paper is to review and discuss the literature about the management factors that can influence volunteer work. First we present the different management factors. This discussion is followed by the identification of the key management factors in volunteering: recruitment, training and rewarding. Finally, we present two main gaps in the literature that justify the scope for further research: (i) how management factors (recruitment, training and rewarding) influence volunteers’ satisfaction and retention; and (ii) predominance of the investigations in the North American context, followed by English and Australian context.