Electricity Consumption Growth Research Articles

Coal price, economic growth and electricity consumption in China under the background of energy transition

With the increasing share of renewable energy generation in China's electricity consumption and the dramatic fluctuation of coal prices in recent years, the discussion of the relationship between coal prices, economic growth and electricity consumption in China becomes more relevant. This paper collects monthly data from 2016 to 2023, uses industrial value added to represent economic growth, and explore the relationship between the three through a time-varying parameter vector autoregressive (TVP-VAR) model, which shows that: (1) The mutual impact effects among coal prices, economic growth, and electricity consumption vary across short-, medium- and long-term. This finding underscores the importance of considering different time horizons when evaluating the interactive effects of these variables. (2) Compared to 2017 and 2022, the lagged impact effects among the three have undergone certain changes, indicating that the understanding of their relationships should be contextualized within specific developmental phases. (3) The relationship between coal prices, economic growth, and different categories of electricity consumption exhibits heterogeneous characteristics, suggesting that recognition of these relationships should be based on specific types of power generation. This research enhances the understanding of the dynamic relationship between coal prices and the macroeconomy in China at the current stage.

Future Consumption Scenarios of Power Sector in Bangladesh

Future electricity demand is an essential prerequisite for planning the expansion of a power system. The purpose of this paper is to provide a forecast of electricity consumption in Bangladesh. Forecast is done here total as well as sector-wise consumption up to 2040 considering the base year 2009. The time series analysis to find the trend line by the method of Least Squares (LS) is applied in this study. We accumulated data from the annual reports of the Bangladesh Power Development Board for the years 2009 to 2023 and used that for forecasting purposes. For the convenient and policy purposes, the forecast is presented for every five years interval. The findings have significant implications with respect to energy conservation and economic development. As the study differentiated sector-wise projected growth of electricity consumption in Bangladesh, it has implications for the planners related to electricity distribution system. The findings can create awareness among the planners of power system expansion in Bangladesh to meet the continuous future development demand.

Estimation of Regional Electricity Consumption Using National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite Night-Time Light Data with Gradient Boosting Regression Trees

With the rapid development of society and economy, the growth of electricity consumption has become one of the important indicators to measure the level of regional economic development. This paper utilizes NPP-VIIRS nighttime light remote sensing data to model electricity consumption in parts of southern China. Four predictive models were initially selected for evaluation: LR, SVR, MLP, and GBRT. The accuracy of each model was assessed by comparing real power consumption with simulated values. Based on this evaluation, the GBRT model was identified as the most effective and was selected to establish a comprehensive model of electricity consumption. Using the GBRT model, this paper analyzes electricity consumption in the study area across different spatial scales from 2013 to 2022, demonstrating the distribution characteristics of electricity consumption from the pixel level to the city scale and revealing the close relationship between electricity consumption and regional economic development. Additionally, this paper examines trends in electricity consumption across various temporal scales, providing a scientific basis for the optimal allocation of energy and the effective distribution of power resources in the study area. This analysis is of great significance for promoting balanced economic development between regions and enhancing energy efficiency.

THE RELATIONSHIP BETWEEN ELECTRICITY CONSUMPTION, TRADE, AND ECONOMIC GROWTH IN NIGERIA

The study examines the relationship between electricity consumption, trade, and economic growth in Nigeria. The results show that increased electricity consumption positively impacts economic growth in both the short and long run. Foreign direct investment (FDI) also has a positive and significant effect, indicating that higher FDI leads to long-term economic growth. Trade openness was found to contribute to environmental growth. The study recommends that policymakers strengthen the manufacturing sector to better harness the benefits of trade openness and reduce its negative impacts

Electricity consumption and economic growth nexus in Afghanistan: impact, causality, projections, and policy implications

Electricity consumption and economic growth nexus in Afghanistan: impact, causality, projections, and policy implications

Fragmentation of water-coal fuel droplets in the air flow

Relevance. An analysis of the current state of the global energy agenda shows that the problem of anthropogenic impact on the planet’s atmosphere by thermal energy facilities is one of the most important for humanity. At the same time, the growth in electricity consumption stimulates the introduction of ever new power generating capacities. For a long time, it was believed that the solution to this problem was the large-scale introduction of non-traditional renewable energy sources (wind generators and solar panels) into the overall balance of electricity generation. However, it is now becoming obvious that renewable energy sources cannot fully cover all electricity needs. The latter creates incentives for the commissioning of new thermal power plants, usually operating on coal fuel. But the main problem of coal energy – its anthropogenic impact – still remains unresolved. This situation creates the prerequisites for the development of new “clean” coal technologies with a full cycle of sequestration of combustion products. One of the most promising technologies for burning coal with low emissions is the combustion of coal in the composition of coal-water fuel. However, coal-water fuel technology has a number of disadvantages. One of the most significant is the high ignition delays of typical (with a characteristic size of 3–5 mm) droplets of coal-water fuel. One of the most promising methods for solving this problem is spraying coal-water fuel in an ultra-fine state (with a characteristic droplet size of 0.1–1 mm). Aim. Experimental study of the conditions and characteristics of crushing droplets of coal-water fuel in a high-speed air flow. Object. Coal-water fuel prepared on the basis of lean coal. Method. Special experimental stand to establish the main characteristics and conditions of dispersion of coal-water fuel droplets. Results. The results of experimental studies show that for stable fragmentation of typical droplets of coal-water fuel, the speed of the latter (during the spraying process) must be at least 40 m/s.

Economic growth and electricity consumption: Fresh evidence of panel data for LAC

This study reexamines the causal nexus among electricity consumption (EC) and economic growth (EG) for a panel of 31 countries in Latin America and the Caribbean between 1980 and 2021. We find that there are statistically significant feedback impacts among the research variables in the long run. A 1 percent augment in EC raises EG by 0.5 percent and a 1 percent augment in EG produces a 1.54 percent increase in EC which reflects the nature of the latter as a luxury good and implies a tradeoff between economy and environment, since although greater electrical infrastructure drives EG, the latter also increases the EC whose use in a non-responsible manner could lead to environmental degradation through higher CO2 emissions. Therefore, the main policy implication is that, it is necessary to promote EG based on infrastructure focused on sustainable development, ensuring the well-being of present and future generations.

Analyzing Determinants of Spatial Patterns in Total and Industrial Electricity Consumption in Turkey

This research investigates the spatial correlation among per capita electricity consumption, per capita industrial electricity consumption, and economic growth by employing various regression models, including linear regression, geographically weighted regression, and multi-stage geographically weighted regression. The primary goal is to illustrate the presence of spatial effects in the connection between electricity consumption and economic growth. In this context, this study made for Turkey distinguishes itself from previous research by utilizing the multi-stage spatially weighted regression model to examine this relationship. The findings reveal that the multi-scale spatial regression model is the most effective in explaining the relation between economic growth at the provincial level and per capita electricity consumption and per capita industrial electricity consumption. Moreover, the study emphasizes that per capita Gross Domestic Product emerges as the most influential regional economic indicator when assessing its impact on per capita electricity consumption and per capita industrial electricity consumption.

Electricity consumption and economic growth: Evidence from the East African community

This study investigates the dynamic causal relationship between electricity consumption and economic growth in the East African Community (1990–2021). It seeks to interrogate the nature of relationship between electricity consumption and economic growth. The hypothesis used in this study is four folded including growth, conservation, feedback and neutral hypothesis.It uses panel data estimation techniques, particularly the panel dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), and non-linear autoregressive distributed lag (NARDL). The panel augmented Dickey Fuller (ADF)-fisher and Levin, Lin & Chu (LLC), 2003, was used to test the unit root process. Dumitreschu-Hurlin (2012) and pairwise Granger tests were used to test for the direction of causality.The findings indicate growth hypothesis with a unidirectional relationship running from electricity consumption to economic growth. Regional governments must increase their investments in electricity market trading to boost economic growth. Greater benefits from regional cooperation can be realized with increased investment in electricity consumption.This is a novel study of the dynamic causal relationship between electricity consumption and economic growth in the East African Community. It is a ground-breaking inquiry into the possibility of integrating electricity markets and their role in promoting economic growth.

Optimal load scheduling strategy for isolated building-integrated DC microgrid using binary PSO to maximize user comfort and minimize peak-to-average ratio

Due to the growth of electricity consumption in residential and commercial buildings, there is a growing burden on utilities in urban areas. Sustainable buildings are being developed by integrating renewable energy generation to make an eco-friendly environment. An isolated building-integrated (IBI) DC microgrid fed by a hybrid solar PV (photo voltaic) generator-thermo electric generator (TEG) is one viable option for obtaining self-sustainable energy for the building. The battery is an important component in such IBI DC microgrid fed by the hybrid solar PV generator-TEG for providing reliable power to the loads. However, the operation and planning of the IBI DC microgrid are challenging, and therefore it needs a suitable load scheduling strategy. This paper proposes the optimal load scheduling strategy (OLSS) under demand response to schedule the household loads in the building. The proposed OLSS aims to balance two conflictive objectives, user comfort and peak-to-average ratio (PAR), using a binary particle swarm optimization algorithm (BPSO). The proposed OLSS optimizes user comfort and PAR and reduces peak demand and battery usage. It also helps in the optimum utilization of power generated from hybrid solar PV generator-TEG by shifting the loads during sun hours. Reducing battery usage reduces the conversion loss and extends the battery life. To validate the proposed OLSS, the investigations are carried out using the data obtained across different seasons. The results show that the proposed OLSS schedules the household loads with the desired user comfort and reduces PAR by 22 % in future buildings.

Energy Consumption and Economic Growth Nexus in India

This research investigates the intricate relationship between energy consumption and economic growth in India, aiming to understand how changes in energy usage impact economic development. The study delves into the causal link between renewable energy consumption and economic growth, considering factors such as capital and technology. Additionally, it explores the impact of energy consumption on agricultural economic growth, emphasizing the vital role of energy in the agricultural sector. The examination extends to assessing the relationship between electricity consumption and overall economic growth, along with sectoral growth across major Indian states, providing valuable regional insights for tailored energy strategies. Furthermore, the research extends its purview to unravel the nuanced impact of energy consumption on agricultural economic growth. Recognizing the indispensable role of energy in the agricultural sector, the study accentuates the pivotal contribution of energy dynamics to the overall economic landscape. This emphasis underscores the significance of aligning energy policies with the unique needs and challenges of the agricultural domain, crucial for fostering balanced and sustainable economic growth.

Impact of electric vehicle charging demand on power distribution grid congestion

California, a pioneer in EV adoption, has enacted ambitious electric vehicle (EV) policies that will generate a large burden on the state's electric distribution system. We investigate the statewide impact of uncontrolled EV charging on the electric distribution networks at a large scale and high granularity, by employing an EV charging profile projection that combines travel demand model, EV adoption model, and real-world EV charging data. We find a substantial need for infrastructure upgrades in 50% of feeders by 2035, and 67% of feeders by 2045. The distribution system across California must upgrade its capacity by 25 GW by 2045, corresponding to a cost between $6 and $20 billion. While the additional infrastructure cost drives the electricity price up, it is offset by the downward pressure from the growth of total electricity consumption and leads to a reduction in electricity rate between $0.01 and $0.06/kWh by 2045. We also find that overloading conditions are highly diverse spatially, with feeders in residential areas requiring twice as much upgrade compared to commercial areas. Our study provides a framework for evaluating EVs' impact on the distribution grid and indicates the potential to reduce infrastructure upgrade costs by shifting home-charging demand. The imminent challenges confronting California serve as a microcosm of the forthcoming obstacles anticipated worldwide due to the prevailing global trend of EV adoption.

Elicitation of electricity consumption habit formation among new subscribers

In this study, our aim is to explore the formation of electricity consumption habits in Cote d'Ivoire, specifically focusing on new subscribers. The growth of residential electricity consumption globally has been influenced by these habits, which can lead to inertia and inefficient energy usage. Using the unique database of the National Electricity Company, we uncover that electricity consumption habits exhibit a high level of persistence, and this persistence tends to strengthen over time. These findings highlight the need to develop policies that encourage electricity efficiency among new subscribers, to combat energy inefficiency and foster positive consumption habits at the household level.

The Relationship between Electricity Consumption and Economic Growth in BRICS Countries

This study analyzed the Gross Domestic Product (GDP) determinants in Brazil, Russia, India, China, and South Africa (BRICS). The method used in this study is a Fully Modified Ordinary Least Square (FMOLS) panel that can overcome the problem of non-stationary panels and the effect of heterogeneity between countries. The analysis range of this study is from 1992 to 2021, with three independent variables, namely electrical energy consumption, labor force, and gross fixed capital formation (GFCF) or investment. The results showed a significant favorable influence on energy consumption, labor force, and investment in GDP in BRICS countries from 1992-2021. This research resulted in a review of one of the policy recommendations to improve the economy in BRICS countries.

Income, extreme temperature, and residential electricity consumption in the Spanish Provinces

The effect of income and extreme temperatures on the residential electricity consumption in Spain is analyzed. An electricity demand function is estimated by means of ordinary least squares-Driscoll and Kraay, feasible generalized least squares, and quantiles panel data techniques, for the total of the sample, and by coastal climatic zones. The results support the energy-environmental Kuznets curve hypothesis for Spain, the continental, and Mediterranean zones. An N form is found for the Atlantic zone. The results also reflect that increases in temperature above 22∘C and decreases below 15∘C increase electricity consumption, this increase being progressive as temperatures vary. Thus, extreme temperature generates electricity consumption growth. The Mediterranean zone is most sensitive to these temperature changes. The results also show that electricity consumption is more sensitive to cold than to heat. The results suggest an inefficient use of heating and cooling appliances in the areas with the highest electricity consumption.

Electricity Consumption and Economic Growth in Kenya: an ARDL Bound Test Approach

Electricity Consumption and Economic Growth in Kenya: an ARDL Bound Test Approach

Estimation of Energy Storage Requirements in an Independent Power System from an Energy Perspective

Taiwan’s power system operates as an isolated grid, preventing the export of surplus energy. Excess electricity is either stored or discarded (curtailed). This study aims to estimate the energy storage requirement for the day with the most extreme electricity consumption behavior in a year without energy curtailment. Based on the installed capacity and actual power generation of renewable energy sources in 2022, this research estimates the power generation per GW of the installed capacity at full load. Integrating the government’s annual installation capacity plans, this study forecasts the annual power generation of renewable sources. Using the electrical load during the 2023 Spring Festival as a baseline and assuming an annual electricity consumption growth rate of 2%, combined with a minimum gas power output of approximately 6 GW, this study calculates the unused power generation, which represents the pumped-storage hydroelectricity and battery energy storage systems requirements for that day under a no-curtailment scenario. Considering the semi-annual adjustments in installation planning, this study’s code is open-sourced and designed to provide updated results with new planning data input, facilitating ongoing adjustments.

Analysis of Long-Term and Short-Term Relationships between Electricity Consumption and Economic Growth in Industrialized Regions of Russia

The purpose of the proposed study is to identify long-term and short-term cause-and-effect relationships between industrial electricity consumption and economic growth through comparative analysis of two neighboring regions with approximately the same industrial potential - the Sverdlovsk and Chelyabinsk regions. To solve this problem, an econometric approach is used, based on the method of testing the boundaries of autoregressive and distributed lag (ARDL) models, which determines the presence of cointegration between series. The use of this method is indispensable when studying regional problems due to the insufficient length of time series of economic indicators in the region. The variables in the comparative analysis were industrial electricity consumption, industrial production volume, economic growth rate, per capita income, and average annual number of employees. When analyzing the data, it was revealed that significant cointegrated variables for the Sverdlovsk region are the rate of economic growth and electricity consumption. Accordingly, for the Chelyabinsk region these variables are the volume of industrial production, electricity consumption and the average annual number of employees. That is, the electricity consumption of the Sverdlovsk region in the long term does not depend on the volume of industrial production and the number of employees but depends only on the rate of economic growth. In the Chelyabinsk region, accordingly, in the long term, electricity consumption depends on the volume of industrial production, the number of employees and does not depend on growth rates. Thus, the regions that, at first glance, are similar in industrial potential differ in the cause-and-effect relationships between economic growth and industrial electricity consumption. The use of causality tests made it possible to identify long-term and short-term cause-and-effect relationships between variables. The results obtained in this study illustrate the explanatory and predictive capabilities of the econometric approach in the context of analyzing cause-and-effect relationships in the economy of two neighboring regions and its energy system. These results may be important when analyzing electricity consumption and energy saving in the industrial sector of the economy of these areas.

Using Machine-Learning Application to model the Causal Relationship between Electricity Consumption and Economic Growth in Nigeria

Using Machine-Learning Application to model the Causal Relationship between Electricity Consumption and Economic Growth in Nigeria

THE ENVIRONMENTAL EFFECTS OF TOURISM: ANALYZING THE IMPACT OF TOURISM, GLOBAL TRADE, CONSUMPTION EXPENDITURE, ELECTRICITY, AND POPULATION ON ENVIRONMENT IN LEADING GLOBAL TOURIST DESTINATIONS

The study analysed the impact of tourism, trade, consumption expenditure, electricity usage, and population on carbon dioxide emissions (CO2) in leading tourist destinations. The study uses a panel dataset of 32 countries from different continents between 2001 and 2020 and applies the generalized method of moments (GMM) and Quantile Regression approaches. The results suggest that tourism (arrivals and revenues) can reduce environmental degradation, and that CO2 emissions increase due to factors such as GDP per capita, electricity consumption, and population growth. Trade openness can reduce CO2 emissions, and controlling for final consumption also indicates a decrease in CO2 emissions. The study suggests that sustainable tourism practices, responsible consumption, and larger international integration may play a role in mitigating CO2 emissions. Leading tourist destinations should develop sustainable urban areas to accommodate population growth, and embrace eco-friendly technologies, infrastructure, and consumption patterns to promote sustainable economic growth while reducing CO2 emissions.