scholarly journals Time Series Analysis for Predicting Hydroelectric Power Production: The Ecuador Case

2019 ◽  
Vol 11 (23) ◽  
pp. 6539 ◽  
Author(s):  
Julio Barzola-Monteses ◽  
Mónica Mite-León ◽  
Mayken Espinoza-Andaluz ◽  
Juan Gómez-Romero ◽  
Waldo Fajardo
Keyword(s):  
Time Series ◽  
Power Production ◽  
Hydroelectric Power ◽  
Power Sources ◽  
Regression Methods ◽  
Production Values ◽  
Starting Point ◽  
Electrical Faults ◽  
Electrical Generation ◽  
Variable Precipitation

Electrical generation in Ecuador mainly comes from hydroelectric and thermo-fossil sources, with the former amounting to almost half of the national production. Even though hydroelectric power sources are highly stable, there is a threat of droughts and floods affecting Ecuadorian water reservoirs and producing electrical faults, as highlighted by the 2009 Ecuador electricity crisis. Therefore, predicting the behavior of the hydroelectric system is crucial to develop appropriate planning strategies and a good starting point for energy policy decisions. In this paper, we developed a time series predictive model of hydroelectric power production in Ecuador. To this aim, we used production and precipitation data from 2000 to 2015 and compared the Box-Jenkins (ARIMA) and the Box-Tiao (ARIMAX) regression methods. The results showed that the best model is the ARIMAX (1,1,1) (1,0,0)12, which considers an exogenous variable precipitation in the Napo River basin and can accurately predict monthly production values up to a year in advance. This model can provide valuable insights to Ecuadorian energy managers and policymakers.

Functional Analysis and Exergoeconomic Evaluation for the Combined Production of Electromechanical Power and Useful Heat of a Cogeneration Power Plant

2011 ◽  
Author(s):  
Washington Orlando Irrazabal Bohorquez ◽  
Joa˜o Roberto Barbosa
Keyword(s):  
Power Plant ◽  
Electricity Market ◽  
Sugar Cane ◽  
Power Plants ◽  
Hydroelectric Power Plant ◽  
Sugar Cane Bagasse ◽  
Fuel Oil ◽  
Hydroelectric Power ◽  
The Us ◽  
Electrical Generation

In the Ecuadorian electrical market, several sugar plants, which significantly participate in the local electricity market, are producing their own energy and commercializing the surplus to the electrical market. This study evaluates the integral use of the sugar cane bagasse for productive process on a Cogeneration Power Plant in an Ecuadorian Sugar Company [8]. The electrical generation based on biomass requires a great initial investment. The cost is around US$ 800/kW installed, twice the US$ 400/kW initial investment of conventional thermoelectric power plant and almost equal to the US$ 1,000/kW initial cost of hydroelectric power plant [5]. A thermoeconomic study was carried out on the production of electricity and the sales of the surplus of 27 MWe average produced by the power plant. An operational analysis was made using instantaneous values from the estimated curves of demand and generation of electricity. From the results, it was concluded that the generated electricity costs are 0.0443 US$/kWh, while the costs of the electricity from Fossil Power Plants (burning fuel oil, diesel fuel and natural gas) are in the range 0.03–0.15 US$/kWh and from Hydroelectric Plants are about 0.02 US$/kWh. Cogeneration power plants burning sugar cane bagasse could contribute to the mitigation of climatic change. This specific case study shows the reduction of the prospective emissions of greenhouse gases, around 55,188 ton of CO2 equivalent yearly for this cogeneration power plant.

scholarly journals Determination of the Starting Point in Time Series for Trend Detection Based on Overlapping Trend

2016 ◽  
Vol 16 (6) ◽  
pp. 98-110
Author(s):  
Gao Xuedong ◽  
Gu Kan
Keyword(s):  
Time Series ◽  
Piecewise Linear ◽  
Negative Influence ◽  
Trend Detection ◽  
Computational Accuracy ◽  
Starting Point ◽  
Time Series Studies ◽  
Definition Of ◽  
Stage Characteristic

Abstract The traditional time series studies consider the time series as a whole while carrying on the trend detection; therefore not enough attention is paid to the stage characteristic. On the other hand, the piecewise linear fitting type methods for trend detection are lacking consideration of the possibility that the same node belongs to multiple trends. The above two methods are affected by the start position of the sequence. In this paper, the concept of overlapping trend is proposed, and the definition of milestone nodes is given on its base; these way not only the recognition of overlapping trend is realized, but also the negative influence of the starting point of sequence is effectively reduced. The experimental results show that the computational accuracy is not affected by the improved algorithm and the time cost is greatly reduced when dealing with the processing tasks on dynamic growing data sequence.

scholarly journals On the emergence of large clusters of acoustic power sources at the onset of thermoacoustic instability in a turbulent combustor

2019 ◽  
Vol 874 ◽  
pp. 455-482 ◽  
Author(s):  
Abin Krishnan ◽  
R. I. Sujith ◽  
Norbert Marwan ◽  
Jürgen Kurths
Keyword(s):  
High Speed ◽  
Power Production ◽  
Acoustic Power ◽  
Spatiotemporal Dynamics ◽  
Combustion Noise ◽  
Pressure Oscillations ◽  
Power Sources ◽  
Thermoacoustic Instability ◽  
Stable Combustion ◽  
Large Clusters

In turbulent combustors, the transition from stable combustion (i.e. combustion noise) to thermoacoustic instability occurs via intermittency. During stable combustion, the acoustic power production happens in a spatially incoherent manner. In contrast, during thermoacoustic instability, the acoustic power production happens in a spatially coherent manner. In the present study, we investigate the spatiotemporal dynamics of acoustic power sources during the intermittency route to thermoacoustic instability using complex network theory. To that end, we perform simultaneous acoustic pressure measurement, high-speed chemiluminescence imaging and particle image velocimetry in a backward-facing step combustor with a bluff body stabilized flame at different equivalence ratios. We examine the spatiotemporal dynamics of acoustic power sources by constructing time-varying spatial networks during the different dynamical states of combustor operation. We show that as the turbulent combustor transits from combustion noise to thermoacoustic instability via intermittency, small fragments of acoustic power sources, observed during combustion noise, nucleate, coalesce and grow in size to form large clusters at the onset of thermoacoustic instability. This nucleation, coalescence and growth of small clusters of acoustic power sources occurs during the growth of pressure oscillations during intermittency. In contrast, during the decay of pressure oscillations during intermittency, these large clusters of acoustic power sources disintegrate into small ones. We use network measures such as the link density, the number of components and the size of the largest component to quantify the spatiotemporal dynamics of acoustic power sources as the turbulent combustor transits from combustion noise to thermoacoustic instability via intermittency.

Wavelet-based trend analysis of hydrological processes at different timescales

2015 ◽  
Vol 6 (3) ◽  
pp. 414-435 ◽  
Author(s):  
Vahid Nourani ◽  
Nasrin Nezamdoost ◽  
Maryam Samadi ◽  
Farnaz Daneshvar Vousoughi
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Stream Flow ◽  
Discrete Wavelet ◽  
Precipitation Data ◽  
Short Term ◽  
Mk Test ◽  
Starting Point ◽  
Annual Time Series ◽  
Annual Time

This study analyzes involved trends in stream flow and precipitation data at monthly, seasonal and annual timescales observed at six precipitation and four stream flow stations of Tampa Bay using non-parametric Mann–Kendall (MK) and discrete wavelet transform (DWT) methods. The MK test and sequential MK analysis were applied to different combinations of DWT after removing the effect of significant lag-1 serial correlation to calculate components responsible for trend of the time series. Also, the sequential MK test was used to find the starting point of changes in annual time series. The results showed that negative trend is prevalent in the case study; generally, short-term periods were important in the involved trend at original time series. Thus, the precipitation data at three scales showed short-term periods of 2 months, 6 months and 2 years in monthly, seasonal and annual scales, respectively. In the greatest stream-flow time series at three timescales, wavelet-based detail at level 2 plus the approximations time series was conceded as the dominant periodic component. Finally, the results of Sen's trend analysis, applied to the original annual time series, also confirmed the results of the proposed wavelet-based MK test in most cases.

New Empirical Estimates of Rent Seeking: An Update of Sobel – Garrett [2002]

2009 ◽  
Vol 27 (2) ◽  
pp. 125-136 ◽  
Author(s):  
Joshua C. Hall ◽  
Justin M. Ross
Keyword(s):  
United States ◽  
Time Series ◽  
The United States ◽  
Rent Seeking ◽  
Empirical Estimates ◽  
Starting Point

Abstract The SIC sectors for direct, indirect, and in kind rent seeking activity have been identified and verified empirically in Sobel - Garrett [2002] by comparing capital counties to noncapital counties. We convert these industries from SIC to NAICS codes and provide measures of direct, indirect, and in-kind rent seeking for the year 2005. In addition, we extend their work by switching from counties to Metropolitan and Micropolitan Statistical Areas, which are defined as economically integrated counties. Our measures are consistent with theirs and provide a starting point for creating a time series of rent-seeking activity in the United States.

scholarly journals How different sources of climate databases influence assessment of growth response in dendroclimatic analyses – case study from Lapland

2015 ◽  
Vol 6 (2) ◽  
pp. 1535-1555
Author(s):  
R. Sitko ◽  
J. Vido ◽  
J. Škvarenina ◽  
V. Pichler ◽  
L. Scheer ◽  
...  
Keyword(s):  
Time Series ◽  
Growth Response ◽  
Radial Increment ◽  
Seasonal Temperature ◽  
Boreal Zone ◽  
Starting Point ◽  
Precipitation Station ◽  
Different Sources ◽  
Zone Temperature

Abstract. The paper deals with the comparison of the time series from different climate databases. We compared the measured data with the modelled data of monthly and seasonal temperature means and precipitation totals. Reliable and as long as possible time series of such data represent the basic starting point of dendroclimatic analyses. We evaluated the differences in the growth response of spruce derived using different databases of the stated climatic characteristics. The stem cores used to derive the cross-correlation function were taken from Hårås locality situated in the boreal zone of the Swedish part of Lapland. We compared the measured records from the nearest meteorological stations situated 18 and 40 km away from the locality with the interpolated values from CRU TS 3.21 climate database and with the reconstructed 502-year-long database. The spatial resolution of the modelled databases was 0.5° × 0.5° of latitude and longitude. We found a systematic error of different magnitudes in the modelled values, and we also quantified a random error and the overall accuracy of the data. The temperature model underestimated the data in comparison with the measured values, while the precipitation model overestimated the data. We also found that the radial increments of spruce correlated more strongly with the temperature than with the precipitation. Hence, in the conditions of the boreal zone, temperature is a more important factor affecting tree-ring formation. We found significantly higher correlations between the radial increment and the modelled precipitation data than with the data measured at the precipitation station situated 18 km from the locality of interest.

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