Short-term load and wind power forecasting using neural network-based prediction intervals

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Electricity load and price forecasting with influential factors in a deregulated power industry

With the emergence of smart power grid and distributed generation technologies in recent years, there is need to introduce new advanced models for forecasting. Electricity load and price forecasts are two primary factors needed in a deregulated power industry. The performances of the demand response programs are likely to be deteriorated in the absence of accurate load and price forecasting. Electricity generation companies, system operators, and consumers are highly reliant on the accuracy of the forecasting models. However, historical prices from the financial market, weekly price/load information, historical loads and day type are some of the explanatory factors that affect the accuracy of the forecasting. In this paper, a neural network (NN) model that considers different influential factors as feedback to the model is presented. This model is implemented with historical data from the ISO New England. It is observed during experiments that price forecasting is more complicated and hence less accurate than the load forecasting.

Evaluation of FRP concrete compression member under repeated load and harsh environment

Strengthening and rehabilitation have been increasingly applied in many structures to improve their capacity and serviceability. Fiber Reinforced Polymer (FRP) materials are universally known for their ability to improve the load capacity of damaged structural elements because of their high linear-elastic behavior. However, enhancing the capacity of structural elements that are exposed to repeated load coupled with harsh environment is an area that requires further investigation. This research focused on experimental analysis of the behavior and response of confined and unconfined concrete compression members (300mm x 150mm) under repeated load while exposed to 1440 cycles of seawater splash zone in United Arab Emirates (UAE). Confining concrete compression members with Carbon Fiber Reinforced Polymer (CFRP) and Glass Fiber Reinforced Polymer (GFRP) sheets have increased the load capacity compared to the control sample at room temperature by 110% and 84%, respectively. Results showed that the average value of compressive strength for the confined concrete exposed to sea water splash zone conditions for CFRP and GFRP specimens has decreased by 33% and 23%, respectively, compared to the confined concrete in the room temperature. However, GFRP specimens showed higher performance in compressive strength under sea water splash zone than those of the CFRP specimens. Different mode of failures such as delamination, de-bonding and combination of such modes were observed and related to various exposure factors and mechanical properties.

Effect of compression load and temperature on thermomechanical tests for gutta-percha and Resilon (R)

Tanomaru-Filho M, Silveira GF, Reis JMSN, Bonetti-Filho I, Guerreiro-Tanomaru JM. Effect of compression load and temperature on thermomechanical tests for gutta-percha and Resilon (R). International Endodontic Journal, 44, 1019-1023, 2011.Aim To analyse a method used to evaluate the thermomechanical properties of gutta-percha and Resilon at different temperatures and compression loads.Methodology Two hundred and seventy specimens measuring 10 mm in diameter and 1.5 mm in height were made from the following materials: conventional gutta-percha (GCO). thermoplastic gutta-percha (GTP) and Resilon (R) cones (RE). After 24 h, the specimens were placed in water at 50 degrees C. 60 degrees C or 70 degrees C for 60 s. After that, specimens were placed between two glass slabs, and loads weighing 1.0, 3.0 or 5.0 kg were applied. Images of the specimens were digitized before and after the test and analysed using imaging software to determine their initial and final areas. The thermomechanical property of each material was determined by the difference between the initial and final areas of the specimens. Data were subjected to ANOVA and SNK tests at 5% significance. To verify a possible correlation between the results of the materials, linear regression coefficients (r) were calculated.Results Data showed higher flow area values for RE under all compression loads at 70 degrees C and under the 5.0 kg load at 60 degrees C (P < 0.05). Regarding gutta-percha, GTP showed higher flow under loads weighing 3.0 and 5.0 kg. at 60 and 70 degrees C (P < 0.05). GCO presented higher flow at 70 degrees C with a load of 5.0 kg. Regression analyses showed a poor linear correlation amongst the results of the materials under the different experimental conditions.Conclusion Gutta-percha and Resilon (R) cones require different compression loads and temperatures for evaluation of their thermomechanical properties. For all materials, the greatest flow occurred at 70 degrees C under a load of 5.0 kg: therefore. these parameters may be adopted when evaluating endodontic tilling materials.

In Vitro Study of Fracture Load and Fracture Pattern of Ceramic Crowns: A Finite Element and Fractography Analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Effects of research and extension on agricultural growth and equity in Brazil.

Studies the effects of investment in research and extension on total agricultural production and on production of individual crops. Some distributional effects are briefly discussed. Due to the lack of data, the first part of the analysis is restricted to the State of Sao Paulo, and the second part covers the entire country.-from Author

Investigation of the relationship between load and loss factors for a Brazilian electric utility

With the considerable increase of the losses in electric utilities of developing countries, such as Brazil, there is an investigation for loss calculation methodologies, considering both technical (inherent of the system) and non-technical (usually associated to the electricity theft) losses. In general, all distribution networks know the load factor, obtained by measuring parameters directly from the network. However, the loss factor, important for the energy loss cost calculation, can only be obtained in a laborious way. Consequently, several formulas have been developed for obtaining the loss factor. Generally, it is used the expression that relates both factors, through the use of a coefficient k. Last reviews introduce a range of factor k within 0.04 - 0.30. In this work, an analysis with real life load curves is presented, determining new values for the coefficient k in a Brazilian electric utility. © 2006 IEEE.

Characterization of the temperature, load and damage effects using piezoelectric transducer patches based on fuzzy clustering

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in a structure. One of the critical challenges for practical implementation of SHM system is the ability to detect damage under changing environmental conditions. This paper aims to characterize the temperature, load and damage effects in the sensor measurements obtained with piezoelectric transducer (PZT) patches. Data sets are collected on thin aluminum specimens under different environmental conditions and artificially induced damage states. The fuzzy clustering algorithm is used to organize the sensor measurements into a set of clusters, which can attribute the variation in sensor data due to temperature, load or any induced damage.

Application of Conservative Power Theory to load and line characterization and revenue metering

This paper proposes a set of performance factors for load characterization and revenue metering. They are based on the Conservative Power Theory, and each of them relates to a specific load non-ideality (unbalance, reactivity, distortion). The performance factors are capable to characterize the load under different operating conditions, considering also the effect of non-negligible line impedances and supply voltage deterioration. © 2012 IEEE.

Analysis of efficiency and rationality in a sugar-alcohol mill using hyperboloid a-load and potency

Brazil is the world's largest producer of sugar cane and which in the state of São Paulo concentrate the greatest amount of sugar cane field of the country. The sugar-alcohol sector has the capacity to produce sufficient thermal and electrical energy to be used in their process of production and commercialize of surplus in electricity distribution network. Therefore it is necessary to evaluate the energy efficiency and rationality within the mill. Accordingly this research proposed analyze the sugar-alcohol mill's sectors globally and individually, located in the west center of the São Paulo state, using the valuation methodology employed by the Agência Nacional de Energia Elétrica (ANEEL) in the industries that do not have systems of cogeneration. In this analysis, the hyperboloids of load and potency were applied based on the indexes of potency factor and load factor that allow estimate the efficiency and rationality. © 2013 IEEE.

Immunization of Wistar female rats with 255-Gy-irradiated Toxoplasma gondii: Preventing parasite load and maternofoetal transmission

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Resistance training with excessive training load and insufficient recovery alters skeletal muscle mass-related protein expression

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)