scholarly journals What is Currently Driving the Growth of China’s Household Electricity Consumption? A Clustering and Decomposition Analysis

2019 ◽  
Vol 11 (17) ◽  
pp. 4648
Author(s):  
Ming Meng ◽  
Shucheng Wu ◽  
Jin Zhou ◽  
Xinfang Wang
Keyword(s):  
Rebound Effect ◽  
Decomposition Analysis ◽  
Electricity Consumption ◽  
Electric Power System ◽  
Electricity Price ◽  
Policy Implications ◽  
Driving Factor ◽  
Consumption Growth ◽  
Effective Measure ◽  
Climate Conditions

The rapid growth of household electricity consumption is threatening the sustainable development of China’s economy and environment because of its impacts on the operation efficiency of the electric power system. To recognize the driving factors of the consumption growth and offer policy implications, based on the consumption-related data of 2015 and 2016, this research used the rank sum ratio (RSR) method to divide China’s 30 provinces into 5 groups and a logarithmic mean Divisia index (LMDI) algorithm to decompose the composition growth of each group into the quantitative contribution of each driving factor. The following conclusions were drawn from the empirical analysis. (1) The Yangtze basin is the most vigorous region of consumption growth and should be principally monitored. (2) Climate conditions have a remarkable impact on consumption growth and should be a key consideration when making differentiated household electricity policies. (3) The rebound effect has already appeared in a few of the most developed regions. Electricity price is an effective measure in dealing with this effect. (4) The improvement of the income level is the most important driving factor for consumption growth. (5) For provinces with high growth vitality, the change in the burden level of electricity expenditure prompts consumption growth. However, for provinces with low growth vitality, the situations are opposite. (6) The impacts of electricity price and population on consumption growth are negligible.

scholarly journals LMDI decomposition analysis of total electricity consumption growth in Hunan province

2021 ◽  
Vol 260 ◽  
pp. 02008
Author(s):  
Bizheng Hu ◽  
Jing Liao ◽  
Xingwen Tu ◽  
Xiao Zhou
Keyword(s):  
Growth Rate ◽  
Decomposition Analysis ◽  
Electricity Consumption ◽  
Hunan Province ◽  
Consumption Growth ◽  
Intensity Effect ◽  
Residential Sector ◽  
Gdp Growth Rate ◽  
Abnormal Phenomenon ◽  
Consumption Intensity

In the past decade, as an important driving force of economic growth, the China’s electricity consumption growth rate has been decoupled from GDP growth rate. The economic reasons behind this abnormal phenomenon are worthy of further study. Based on the LMDI method, this paper built a model to decompose the total electricity consumption in Hunan province from 2010 to 2017 from the industrial and residential perspective. The results showed that: integrally, scale effect was the main driving factor of electricity consumption growth, intensity effect was the main inhibiting factor, and structure effect had no obvious influence; there are significant differences between the results of industrial and residential sectors, for the industry, the productive consumption intensity effect was the most significant factor that inhibited the growth of electricity consumption, while all the effects of residential sector were shown as promotion, and the increase of electricity consumption in the residential sector played a key role in the growth rate of electricity consumption in Hunan province.

scholarly journals What has driven the growth of Brazil´s residential electricity consumption during the last 19 years? An index decomposition analysis

2021 ◽  
Vol 21 (2) ◽  
pp. 7-39
Author(s):  
Karla Cristina de Freitas Jorge Abrahão ◽  
Roberta Vieira Gonçalves de Souza
Keyword(s):  
Low Income ◽  
Decomposition Analysis ◽  
Electricity Consumption ◽  
Energy Policies ◽  
Consumption Growth ◽  
Efficiency Measures ◽  
Index Decomposition ◽  
Residential Electricity ◽  
Residential Electricity Consumption ◽  
Low Income Households

Abstract Residential electricity consumption in Brazil has been growing during the last few decades, creating a potential opportunity to expand energy efficiency measures. However, the dimension of the sector and its closed relationship with the economic, cultural, and demographic processes causes a certain complexity in the understanding of patterns of consumption, creating additional challenges to energy policies. This study analyzed and decomposed the Brazilian residential electricity consumption between the years of 2000 and 2018, by driving factors through the LMDI-I method and IDA index, on regional level. All the data were obtained by official sources in the country. The main results obtained were: (i) the increase of household numbers was found to be one of the main drivers of consumption growth; (ii) household income showed no control over consumption in hot climate regions, except in low- income households; (iii) tariff showed to impose restrictions on consumption, also mainly in low-income households. Unprecedentedly, the results showed that the electricity consumption in Brazil varies with population age, with a trend of consumption growth up to the age 59, and a sharp reduction from the age of 60. The study presents opportunities to be contemplated in research and in energy policies.

scholarly journals The Electricity Rebound Effect: Empirical Evidence From the Chinese Chemical Industry

2022 ◽  
Vol 9 ◽  
Author(s):  
Houyin Long ◽  
Hong Zeng ◽  
Xinyi Lin
Keyword(s):  
Chemical Industry ◽  
Electricity Market ◽  
Rebound Effect ◽  
Electricity Price ◽  
Policy Implications ◽  
Chinese Government ◽  
Cost Information ◽  
Cost Share ◽  
Electricity Cost ◽  
The Government

The Chinese government has adopted many policies to save energy and electricity in the chemical industry by improving technology and reforming its electricity market. The improved electricity efficiency and the electricity reform may indirectly reduce expected energy and electricity savings by decreasing the effective electricity price and the marginal cost of electricity services. To analyze the above issues, this paper employs the Morishima Elasticity of Substitution of the electricity cost share equation which is estimated by the DOLS method. The results show that: 1) There exists a rebound effect in the Chinese chemical industry, but it is quite large because the electricity price is being controlled by the government; 2) the reform of the electricity market reduces the rebound effect to 73.85%, as electricity price begins to reflect cost information to some extent; 3) there is still a lot of space for the reform to improve, and the rebound effect could be reduced further once the electricity price is adjusted to transfer the market information more correctly. In order to succeed in saving electricity and decreasing the rebound effect in the chemical industry, the policy implications are provided from perspectives of the improved energy efficiency and electricity pricing mechanism.

scholarly journals LMDI Decomposition Analysis of E-Waste Generation in the ASEAN

2021 ◽  
Vol 18 (23) ◽  
pp. 12863
Author(s):  
Gobong Choi ◽  
Taeyoon Kim ◽  
Minchul Kim
Keyword(s):  
Economic Growth ◽  
Electronic Waste ◽  
Lao Pdr ◽  
Decomposition Analysis ◽  
The Philippines ◽  
Policy Implications ◽  
Driving Factor ◽  
Asean Member ◽  
Brunei Darussalam ◽  
Asean Countries

The economies of ASEAN member states are growing rapidly, and electrical and electronic waste (E-waste) generated from them are also showing a rapid increase. In this context, this study conducted an LMDI decomposition analysis on the amount of E-waste generated in ASEAN member countries from 2015 to 2019 and decomposed it into E-waste intensity, economic growth, and population effects. Then, based on analysis results, policy implications are suggested to improve their E-waste management. According to the analysis results, ASEAN countries can be classified into three groups. The first group includes Indonesia, the Philippines, Singapore, Thailand; economic growth was the main driving factor of E-waste increase in these countries. However, E-waste had also decreased due to the effect of E-waste intensity. The second group includes countries where economic growth was not the only driving factor for E-waste increase, but also where E-waste had increased due to the effect of E-waste intensity. These countries include Cambodia, Malaysia, and Viet Nam. Finally, the third group consists of countries where the effect of E-waste intensity is the main driving factor, including Brunei Darussalam, Lao PDR, and Myanmar. This research shows that ASEAN countries need policies that can effectively deal with the threat of E-waste as a result of high economic growth and policies that can improve intensity by reducing the generation of E-waste.

scholarly journals How to Effectively Control Energy Consumption Growth in China’s 29 Provinces: A Paradigm of Multi-Regional Analysis Based on EAALMDI Method

2021 ◽  
Vol 13 (3) ◽  
pp. 1093
Author(s):  
Yunlong Zhao ◽  
Geng Kong ◽  
Chin Hao Chong ◽  
Linwei Ma ◽  
Zheng Li ◽  
...  
Keyword(s):  
Energy Consumption ◽  
High Resolution ◽  
Energy Policy ◽  
Policy Making ◽  
Regional Analysis ◽  
Policy Implications ◽  
Consumption Growth ◽  
High Resolution Analysis ◽  
Resolution Analysis ◽  
Consumption Control

Controlling energy consumption to reduce greenhouse gas emissions has become a global consensus in response to the challenge of climate change. Most studies have focused on energy consumption control in a single region; however, high-resolution analysis of energy consumption and personalized energy policy-making, for multiple regions with differentiated development, have become a complicated challenge. Using the logarithmic mean Divisia index I (LMDI) decomposition method based on energy allocation analysis (EAA), this paper aims to establish a standard paradigm for a high-resolution analysis of multi-regional energy consumption and provide suggestions for energy policy-making, taking 29 provinces of China as the sample. The process involved three steps: (1) determination of regional priorities of energy consumption control by EAA, (2) revealing regional disparity among the driving forces of energy consumption growth by LMDI, and (3) deriving policy implications by comparing the obtained results with existing policies. The results indicated that 29 provinces can be divided into four groups, with different priorities of energy consumption control according to the patterns of coal flows. Most provinces have increasing levels of energy consumption, driven by increasing per capita GDP and improving living standards, while its growth is restrained by decreasing end-use energy intensity, improving energy supply efficiency, and optimization of industrial structures. However, some provinces are not following these trends to the same degree. This indicates that policy-makers must pay more attention to the different driving mechanisms of energy consumption growth among provinces.

scholarly journals Temperature Effects on Electricity and Gas Consumption: Empirical Evidence from Mexico and Projections under Future Climate Conditions

2020 ◽  
Vol 13 (1) ◽  
pp. 305
Author(s):  
W.J. Wouter Botzen ◽  
Tim Nees ◽  
Francisco Estrada
Keyword(s):  
Climate Change ◽  
Energy Consumption ◽  
Fixed Effects ◽  
Electricity Consumption ◽  
Energy Transition ◽  
Net Energy ◽  
Economic Costs ◽  
Climate Conditions ◽  
Linear Relationships ◽  
Gas Consumption

Fixed effects panel models are used to estimate how the electricity and gas consumption of various sectors and residents relate to temperature in Mexico, while controlling for the effects of income, manufacturing output per capita, electricity and gas prices and household size. We find non-linear relationships between energy consumption and temperature, which are heterogeneous per state. Electricity consumption increases with temperature, and this effect is stronger in warm states. Liquified petroleum gas consumption declines with temperature, and this effect is slightly stronger in cold states. Extrapolations of electricity and gas consumption under a high warming scenario reveal that electricity consumption by the end of the century for Mexico increases by 12%, while gas consumption declines with 10%, resulting in substantial net economic costs of 43 billion pesos per year. The increase in net energy consumption implies greater efforts to comply with the mitigation commitments of Mexico and requires a much faster energy transition and substantial improvements in energy efficiency. The results suggest that challenges posed by climate change also provide important opportunities for advancing social sustainability goals and the 2030 Agenda for Sustainable Development. This study is part of Mexico’s Sixth National Communication to the United Nations Framework Convention on Climate Change.

scholarly journals Experimental Analysis of GBM to Expand the Time Horizon of Irish Electricity Price Forecasts

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7587
Author(s):  
Conor Lynch ◽  
Christian O’Leary ◽  
Preetham Govind Kolar Sundareshan ◽  
Yavuz Akin
Keyword(s):  
Electricity Market ◽  
Electricity Consumption ◽  
Cost Effective ◽  
Absolute Error ◽  
Electricity Price ◽  
Gradient Boosting ◽  
Avant Garde ◽  
Electricity Price Forecasting ◽  
Gradient Boosting Machine ◽  
Extreme Gradient Boosting

In response to the inherent challenges of generating cost-effective electricity consumption schedules for dynamic systems, this paper espouses the use of GBM or Gradient Boosting Machine-based models for electricity price forecasting. These models are applied to data streams from the Irish electricity market and achieve favorable results, relative to the current state-of-the-art. Presently, electricity prices are published 10 h in advance of the trade day of interest. Using the forecasting methodology outlined in this paper, an estimation of these prices can be made available one day in advance of the official price publication, thus extending the time available to plan electricity utilization from the grid to be as cost effectively as possible. Extreme Gradient Boosting Machine (XGBM) models achieved a Mean Absolute Error (MAE) of 9.93 for data from 30 September 2018 to 12 December 2019 which is an 11.4% improvement on the avant-garde. LGBM models achieve a MAE score 9.58 on more recent data: the full year of 2020.

scholarly journals Electricity Price Distributions in Future Renewables-Dominant Power Grids and Policy Implications

2021 ◽  
Author(s):  
Dharik Mallapragada ◽  
Cristian Junge ◽  
Cathy Xun Wang ◽  
Johannes Pfeifenberger ◽  
Paul Joskow ◽  
...  
Keyword(s):  
Electricity Price ◽  
Power Grids ◽  
Policy Implications
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