scholarly journals Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yubin Cai ◽  
Xin Ma ◽  
Wenqing Wu ◽  
Yanqiao Deng

Natural gas is one of the main energy resources for electricity generation. Reliable forecasting is vital to make sensible policies. A randomly optimized fractional grey system model is developed in this work to forecast the natural gas consumption in the power sector of the United States. The nonhomogeneous grey model with fractional-order accumulation is introduced along with discussions between other existing grey models. A random search optimization scheme is then introduced to optimize the nonlinear parameter of the grey model. And the complete forecasting scheme is built based on the rolling mechanism. The case study is executed based on the updated data set of natural gas consumption of the power sector in the United States. The comparison of results is analyzed from different step sizes, different grey system models, and benchmark models. They all show that the proposed method has significant advantages over the other existing methods, which indicates the proposed method has high potential in short-term forecasting for natural gas consumption of the power sector in United States.

2014 ◽  
Vol 707 ◽  
pp. 514-519
Author(s):  
Xin Min Zhang ◽  
Kuang Cen ◽  
Wan Li Xing

Gas consumption exist great regional difference, price and income are the main factors affecting consumption .Global gas consumption has slow growth, but the price in 2008 there was a twist. We analyze the global natural gas consumption and price points using the data from the BP. The level of economic development and natural gas reserves determine the differences in the levels of consumption. In order to eliminate the impact per unit, the regression model uses the data in the log. This paper studied the influence factors of natural gas consumption in North America using of consumer income elasticity and price elasticity. The results show that the gas consumption have a low income elasticity and price elasticity is higher .Law of "S" shape can explain the income elasticity is low, the reason is that the stage of economic development. Price elasticity is higher lies in the different between Canada and the United States, the United States is a net importer of natural gas, and Canada is a net exporter. Keywords: Consumption Flexibility; Natural Gas Demand; income; price


2007 ◽  
Vol 46 (11) ◽  
pp. 1993-2013 ◽  
Author(s):  
Reed P. Timmer ◽  
Peter J. Lamb

Abstract The increased U.S. natural gas price volatility since the mid-to-late-1980s deregulation generally is attributed to the deregulated market being more sensitive to temperature-related residential demand. This study therefore quantifies relations between winter (November–February; December–February) temperature and residential gas consumption for the United States east of the Rocky Mountains for 1989–2000, by region and on monthly and seasonal time scales. State-level monthly gas consumption data are aggregated for nine multistate subregions of three Petroleum Administration for Defense Districts of the U.S. Department of Energy. Two temperature indices [days below percentile (DBP) and heating degree-days (HDD)] are developed using the Richman–Lamb fine-resolution (∼1° latitude–longitude) set of daily maximum and minimum temperatures for 1949–2000. Temperature parameters/values that maximize DBP/HDD correlations with gas consumption are identified. Maximum DBP and HDD correlations with gas consumption consistently are largest in the Great Lakes–Ohio Valley region on both monthly (from +0.89 to +0.91) and seasonal (from +0.93 to +0.97) time scales, for which they are based on daily maximum temperature. Such correlations are markedly lower on both time scales (from +0.62 to +0.80) in New England, where gas is less important than heating oil, and on the monthly scale (from +0.55 to +0.75) across the South because of low January correlations. For the South, maximum correlations are for daily DBP and HDD indices based on mean or minimum temperature. The percentiles having the highest DBP index correlations with gas consumption are slightly higher for northern regions than across the South. This is because lower (higher) relative (absolute) temperature thresholds are reached in warmer regions before home heating occurs. However, these optimum percentiles for all regions are bordered broadly by surrounding percentiles for which the correlations are almost as high as the maximum. This consistency establishes the robustness of the temperature–gas consumption relations obtained. The reference temperatures giving the highest HDD correlations with gas consumption are lower for the colder northern regions than farther south where the temperature range is truncated. However, all HDD reference temperatures greater than +10°C (+15°C) yield similar such correlations for northern (southern) regions, further confirming the robustness of the findings. This robustness, coupled with the very high correlation magnitudes obtained, suggests that potentially strong gas consumption predictability would follow from accurate seasonal temperature forecasts.


Significance US natural gas prices have surged over the past six weeks thanks to falling supply, strong demand from the power sector and rising exports. The uptick in prices has provided a glimmer of hope to gas producers in the United States, hard hit by a prolonged slump in prices. Impacts Declining gas production and rising demand will mean increased pipeline imports from Canada over the coming months. Mexico will pay higher prices for US natural gas imports as the Henry Hub benchmark, potentially hitting demand. US producers that have more gas-producing assets in their portfolio will benefit from rising prices.


2013 ◽  
Vol 671-674 ◽  
pp. 3-9 ◽  
Author(s):  
Cheng Hua Wang ◽  
Mei Na Zhang

An improved grey system model GM(1,1) was proposed in this paper, considered that the large difference between predicted results and measured load-settlement relationship results of bored piles, in which the prediction results were given by the original theory. The complete and incomplete load-settlement curves from pile loading tests were fitted and predicated by the improved grey model. The results calculated with empirical equations or methods in technical code for building pile foundations were compared with those predicted with the improved grey model. Analysis of a case study showed that the results predicted by the improved grey theory model GM(1,1) had higher precision, which demostrated that this improved theory was of significance in engineering practice.


2021 ◽  
Vol 7 ◽  
pp. 788-797
Author(s):  
Chong Liu ◽  
Wen-Ze Wu ◽  
Wanli Xie ◽  
Tao Zhang ◽  
Jun Zhang

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Chengli Zheng ◽  
Wen-Ze Wu ◽  
Jianming Jiang ◽  
Qi Li

As is known, natural gas consumption has been acted as an extremely important role in energy market of China, and this paper is to present a novel grey model which is based on the optimized nonhomogeneous grey model (ONGM (1,1)) in order to accurately predict natural gas consumption. This study begins with proving that prediction results are independent of the first entry of original series using the product theory of determinant; on this basis, it is a reliable approach by inserting an arbitrary number in front of the first entry of original series to extract messages, which has been proved that it is an appreciable approach to increase prediction accuracy of the traditional grey model in the earlier literature. An empirical example often appeared in testing for prediction accuracy of the grey model is utilized to demonstrate the effectiveness of the proposed model; the numerical results indicate that the proposed model has a better prediction performance than other commonly used grey models. Finally, the proposed model is applied to predict China’s natural gas consumption from 2019 to 2023 in order to provide some valuable information for energy sectors and related enterprises.


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