Differential Impact of COVID-19 on the Energy Consumption of Residential and Business Sectors

As a consequence of the COVID-19 pandemic, some patterns of energy consumption changed in the residential and non-residential sectors. This paper uses data from a local utility company in Florida to quantify the heterogeneous impacts of the pandemic on electricity and natural gas consumption across households from different income levels and across essential and non-essential businesses. We found significant increases in the average residential electricity consumption during the lockdown and subsequent reopening phases, which translate into higher cost for households. We found that natural gas consumption dropped abruptly in the business sector and also important differences between the electricity consumption of essential and non-essential businesses, with the former consuming more and the latter less electricity. © 2023 by the IAEE. All rights reserved.

EL FUTURO DEL PETRÓLEO Y EL GAS NATURAL EN ESCENARIOS GLOBALES DE RÁPIDA DESCARBONIZACIÓN

La acelerada descarbonización de la economía, a la que muchos Gobiernos se han comprometido, implica no solo una reducción en el consumo de hidrocarburos, sino también una transformación profunda de los correspondientes mercados. Este artículo trata de ofrecer una visión organizada de lo aportado sobre este tema por diferentes prospectivas energéticas que gozan de reconocimiento internacional, así como por diferentes fuentes académicas. Este trabajo explora la oferta y la demanda de gas y petróleo en escenarios de rápida y muy rápida descarbonización, buscando aquellas tendencias comunes que ayudan a entender qué papel tienen estos hidrocarburos en ellos. La idea clave de este artículo es que el petróleo y el gas natural seguirán siendo energías clave para el mundo en los próximos treinta años, aunque el consumo de ambos hidrocarburos se reduce a medida que la economía se descarboniza. En este contexto de menor consumo, conviene destacar que el gas natural es un combustible más resiliente en los escenarios de rápida descarbonización, en particular, en la próxima década.Alternate :The current plans for a deep decarbonization of the economy across many different countries implies not only a reduction in hydrocarbon consumption, but also a profound transformation of the corresponding markets. This article offers an organized perspective of the different energy outlooks by internationally recognized institutions as well as from different academic sources. This paper explores oil and gas supply and demand in scenarios of rapid and very rapid decarbonization, looking for common trends that help to understand the role of these energy sources. The key insight of this paper is that oil and natural gas remain as key energy sources over the next 30 years, although consumption of both hydrocarbons declines as the economy decarbonizes. In this context of progressive lower consumption, it is worth noting that natural gas is a more resilient fuel in scenarios of rapid decarbonization, particularly in the next decade.

Model selection with decision support model for US natural gas consumption forecasting

Reliable prediction of natural gas consumption helps make the right decisions ensuring sustainable economic growth. This problem is addressed here by introducing a hybrid mathematical model defined as the Choquet integral-based model. Model selection is based on decision support model to consider the model performance more comprehensively. Different from the previous literature, we focus on the interaction between models when combine models. This paper adds grey accumulation generating operator to Holt-Winters model to capture more information in time series, and the grey wolf optimizer obtains the associated parameters. The proposed model can deal with seasonal (short-term) variability using season auto-regression moving average computation. Besides, it uses the long short term memory neural network to deal with long-term variability. The effectiveness of the developed model is validated on natural gas consumption due to the COVID-19 pandemic in the USA. For this, the model is customized using the publicly available datasets relevant to the USA energy sector. The model shows better robustness and outperforms other similar models since it consider the interaction between models. This means that it ensures reliable perdition, taking the highly uncertain factor (e.g., the COVID-19) into account. © 2023 Elsevier Ltd

Model selection with decision support model for US natural gas consumption forecasting

Reliable prediction of natural gas consumption helps make the right decisions ensuring sustainable economic growth. This problem is addressed here by introducing a hybrid mathematical model defined as the Choquet integral-based model. Model selection is based on decision support model to consider the model performance more comprehensively. Different from the previous literature, we focus on the interaction between models when combine models. This paper adds grey accumulation generating operator to Holt-Winters model to capture more information in time series, and the grey wolf optimizer obtains the associated parameters. The proposed model can deal with seasonal (short-term) variability using season auto-regression moving average computation. Besides, it uses the long short term memory neural network to deal with long-term variability. The effectiveness of the developed model is validated on natural gas consumption due to the COVID-19 pandemic in the USA. For this, the model is customized using the publicly available datasets relevant to the USA energy sector. The model shows better robustness and outperforms other similar models since it consider the interaction between models. This means that it ensures reliable perdition, taking the highly uncertain factor (e.g., the COVID-19) into account.

Future outlook and influencing factors analysis of natural gas consumption in Bangladesh: An economic and policy perspectives

The development of mechanization and technology has triggered the rising energy consumption in various sectors. The study objective is to investigate the relationship between gas consumption share, energy intensity, economic structure share, per capita gross domestic value, and population at the sectorial level from 1994 to 2020. This study analyzes the factors in three ways: first, the study applies decomposition analysis between key factors. Second, an appropriate decoupling method is applied to investigate the impacting factors to check the driving factors affecting the decoupling using the logarithmic mean Divisia index method. Third, based on aggregated and sectorial variations, the ratio decomposition of each sector is estimated. The results show that the economic activity effect is the main driving factor in raising gas consumption, which increased by 15.11 crore Tk./million during 1994–2020. The energy intensity trend declined by 14.87 Mtoe/crore Tk., which shows an imperative role in natural gas consumption efficiency for production and in economy. The economic structure share provided a record decline by 52.79 crores Tk. during the COVID-19 situation while a significant increase in gas consumption was found until 2013, which could be significant under decomposition changes. Three decoupling states such as expansive negative decoupling, expansive coupling and weak decoupling were found in which the decoupling relationship was gradually a dominated by a weak decoupling. The sectorial index provides a maximum of weak decoupling in which energy-saving technology gap change was found in power, captive power, industry, tea estate, compressed natural gas, and fertilizer sectors. Finally, the scenarios analyzed that natural gas consumption estimates maximum gross domestic product and conserves more energy in the future. Briefly, the decoupling process and its leading factors were obvious among nine major sectors.

Response of Natural Gas Consumption to Temperature and Projection under SSP Scenarios during Winter in Beijing

The present study investigates the response of natural gas consumption to temperature on the basis of observations during heating season (middle November–middle March) for the period 2002–2021 in Beijing, China, and then estimates temperature-related changes in the gas consumption under future scenarios by using climate model simulations from the Coupled Model Intercomparison Project Phase 6. Observational evidence suggests that the daily natural gas consumption normalized by gross domestic product is linearly correlated with the daily average temperature during heating season in the past two decades in Beijing. Hence, a linear regression model is built to estimate temperature-related changes in the natural gas consumption under future scenarios. Corresponding to a rising trend in the temperature, the natural gas consumption shows a decrease trend during 2015–2100 under both the SSP245 and the SSP585 scenarios. In particular, the temperature would increase rapidly from early 2040s to the end of 21st century under the SSP585 scenario, leading to an obvious reduction in the natural gas consumption for heating in Beijing. Relative to that in the present day (1995–2014), the natural gas consumption would show a reduction of approximately 9% (±4%) at the end of 21st century (2091–2100) under the SSP245 scenario and approximately 22% (±7%) under the SSP585 scenario.

Forecasting China's energy demand post-COVID-19 pandemic: Insights from energy type differences and regional differences

As the first country to restart the economy after the COVID-19 pandemic, China's fast-growing energy consumption has brought huge challenges to the energy system. In this context, ensuring a stable energy supply requires accurate estimates of energy consumption for China's post-Covid-19 pandemic economic recovery. To this end, this study uses multiple panel regression model to explore the relationship between energy consumption and economic growth from the perspective of energy sources (total energy, coal, oil, natural gas) and regional difference. The data from 30 provinces in China from 2000 to 2017 were selected. Our findings indicate that China economic growth has led to the largest increase for oil consumption, followed by natural gas consumption, and finally coal consumption. That is, China economic growth has led to the largest increase for oil consumption, followed by natural gas consumption, and finally coal consumption. In addition, the coefficients of regional energy consumption equations are heterogeneous. Among them, energy consumption growth in provinces with high energy consumption is most affected by economic growth, followed by provinces with low energy consumption, and finally provinces with middle energy consumption. © 2022 The Author(s)

Prediction and analysis of natural gas consumption in chongqing with a grey prediction model group in the context of COVID-19.

In this paper, a grey prediction model group is employed to quantitatively study the impact of COVID-19 on natural gas consumption in Chongqing, China. First, a grey prediction model group suitable for the prediction of Chongqing's natural gas consumption is introduced, which consists of GM(1,1), TWGM(1,1), and the newly-developed ODGM(1,1). Then, the model group is constructed to predict Chongqing's natural gas consumption in 2020. Finally, compare the predicted results of the model group with the actual consumption and quantitatively analyze the impact of the epidemic on natural gas in Chongqing. It is found that the impact of the epidemic on the consumption of natural gas in the first quarter of the year is very small, but relatively bigger in the second and third quarters. The study is of positive significance to maintain the supply and demand balance of natural gas consumption in Chongqing in the background of COVID-19; and it enriches and develops the theoretical system of grey prediction models.

The natural gas consumption and mortality nexus: A mediation analysis

Boosting natural gas consumption can contribute to a healthy China. To examine the link between natural gas consumption and mortality, this study utilizes a balanced panel dataset including 30 Chinese provinces from 2001 to 2019. The fully modified ordinary least squares (FMOLS) method is employed to reveal the long-term cointegration, and the Dumitrescu and Hurlin (D-H) test is further applied to explore the causal relations. Moreover, this study estimates the mediation effects of particulate matter (PM 2.5) emissions on mortality. The empirical results indicate that climbing natural gas consumption can effectively reduce the mortality rate. At the national level, a 1% increase in natural gas consumption leads to a 0.02% decrease in the mortality rate. In addition, the causality analysis uncovers the existence of significant regional heterogeneity. An increase in natural gas consumption will exert a stronger impact in curbing mortality in high gross domestic product (High-GDP) or high natural gas consumption (High-NG) regions. In addition to directly affecting mortality, natural gas consumption also has an indirect impact through the mediation effects of PM 2.5 emissions. Finally, implications for policy and practice are put forward for the Chinese government pertaining to build a healthy China and advance the natural gas industry. • The nexus between natural gas consumption and mortality in China is investigated for 2001–2019. • Natural gas consumption negatively affects mortality rates. • Bidirectional causality link between natural gas consumption and mortality rate is detected. • Natural gas consumption not only directly affects mortality but also indirectly affect mortality by influencing PM 2.5 emissions. [ FROM AUTHOR] Copyright of Energy is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)