Rodrigo F. Calili

Long Term Electricity Forecast: A Systematic Review☆

Abstract Energy planning and management have always represented a great challenge for most countries all over the world. Since the beginning of industrial revolution, one of the main bottlenecks to economy growth was energy availability, not just due to electricity shortage but also to the scarcity of other energy resources. So the necessity to construct methodologies and procedures to predict electricity needs became prominent and a major issue both for academics, government and electricity companies. Based on the methodologies and framework constructed, it is possible to define what actions should be taken to fulfill the electricity demanded by the society. The objective of the article represents the first step towards understanding and analyzing the state of art of models applied to electricity long-term forecasts, which is to define and apply a concise methodology to make a systematic review on academic articles from indexed journals.

AVALIAÇÃO METROLÓGICA DA CURVA ANALÍTICA PARA DETERMINAÇÃO DO TEOR DE ENXOFRE EM BAIXÍSSIMAS CONCENTRAÇÕES EM ÓLEO DIESEL S-10

The increasing search for a reduction in air emissions has provided a challenging analytical scenario. This paper discusses metrologically, the best practices relating to analytical curves for the determination of very low concentrations of sulfur content in diesel S-10 by monochromatic wavelength dispersive X-ray fluorescence spectrometry (MWDXRF). For weighted linear regression, a new strategy to correlate the weights with the output variable is proposed, which is lacking in the literature. The analytical curve 0-500 mg kg-1, built in compliance with international standards, featured heteroscedastic behavior. The results showed that weighted linear regression is the most suitable choice for assessing concentrations at the beginning of an analytical curve, such as 10 mg kg-1 (product specification limit) rather than simple linear regression which holds that the measured results must be closest to the centroid of the regression line. Finally, it was observed that, when a shorter analytical curve is built, it loses both in accuracy and in precision for very low concentrations, as compared to t simple and weighted linear regression.

Confidence interval for the 100p-th percentile for measurement error distributions

In metrology, one is usually comparing what indicates an instrument versus what it should be indicated by a reference pattern, resulting in the so called measurement errors. Most errors follow a normal distribution. If one wants to have some confidence about how small is such an error, the traditional confidence intervals for the unknown parameters are computed. This article illustrates, via simulation, the effectiveness of three intervals for estimating the 100p-th percentile in a normal distribution, namely, the Traditional (T), the Normal Asymptotic (NA), and the Lawless (LA) intervals. Various samples of different sizes are drawn from a zero mean normal distribution, which resembles the measurement error distributions. For each one of them the 95% confidence interval is estimated by using the three approaches. From the simulation, it is possible to conclude that T and LA intervals are better than NA as they produce shorter length and wider coverage.

Modeling the impact of energy efficiency in the electricity consumption of the Brazilian tertiary sector

Studies of the impact of energy efficiency on the electricity consumption of the Brazilian tertiary sector are still few. Recent official studies extrapolate energy conservation figures to provide estimations. In this work, a techno-economic bottom-up model is applied to simulate long-term electricity consumption of the Brazilian tertiary sector under four energy efficiency scenarios. The approach considers drivers of the tertiary consumption and diffusion of energy services in the modeling. The concept of energy efficiency measures (EEMs) is used to model individual options that improve energy services. The model is validated considering observed tertiary consumption by region. Considering the proposed EEMs, the results show that lighting plays an important role on energy saving when EEMs diffuse autonomously. Considering cost-effectiveness, ventilation & air-conditioning contributes most to energy savings. This work shows that, despite data unavailability, it is possible to build a consistent model for Brazilian tertiary sector by adjusting model parameters.

Comparison of calibration curve fitting methods in the determination of H2S mass fractions in natural gas by GC-SCD

ABSTRACT This paper discusses metrologically the best practice regarding the calibration curves applied to H2S mass fractions determination in natural gas by gas chromatography with sulfur chemiluminescence detection (GC-SCD). Three calibration curves were constructed by performing GC-SCD analysis of different H2S gas standard concentrations (from 3 mg kg−1 up to 500 mg kg−1). These experimental curves are better fitted by an unweighted quadratic calibration curve considering ANOVA approach compared to ASTM D5504-12. Despite this, the obtained results show that these two different calibration curve approaches (ASTM and ANOVA) lead to comparable results. Hence, there are no significant statistical differences between these two approaches based on the hypothesis test applied. However, the quadratic calibration curve presents measurement uncertainties of H2S mass fractions much lower than the ASTM approach.

Long-term scenarios development for the electricity tariffs in Brazil

Brazil has one of the largest electricity market in South America. As in many other countries, Brazilian electricity sector groups consumers in five classes, as follows: Residential, Industrial, Commercial, Public Sector and Rural. The end-user electricity tariffs are calculated taking into account generation, transmission and distribution costs, including also taxes and other charges. The article main objective was to conceive long-term electricity tariffs scenarios for Brazilians Southeast region testing top-down models to do so. In the article, statistical and computational intelligence methodologies were tested and the method with the best one scenarios simulation was performed.