Household and industrial electricity demand in Europe

Cialani, Catia; Mortazavi, Reza

doi:10.1016/j.enpol.2018.07.060

Cited by 64 publications

(47 citation statements)

References 43 publications

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“…The electricity markets in Europe are undergoing considerable economic and technological restructuring (Stoft, 2002;Nillesen et al, 2004;Bojnec and Papler, 2016;Cialani and Mortazavi, 2018;European Commission, 2019). The increasing dependency on electrical energy, along with continued economic growth, has caused electricity consumption to be raised as an important economic and ecological question for our common future at a global level (e.g.…”

Section: The Analysis Of Liberalisation Of the Electricity Market In mentioning

confidence: 99%

The analysis of liberalisation of the electricity market in Slovenia

Bonjec¹,

Papler²

2020

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The purpose of this paper has been to investigate wholesale-to retail-sale electricity supply management in Slovenia. The rapid increase in electricity supply in Slovenia has been determinedby increasing industry, public and household electricity demands. The paper analyses structures and dynamics in wholesale-to-retail supply chain structures and management that are important for purchases of electrical energy by electricity distribution retailers. By using Lorenz’s curve and Gini’s coefficient of concentration, there is found to be a relatively high degree of concentration of wholesale electricity suppliers in the delivery of electrical energy to the retail electricity distribution enterprises. Whereas the number of the wholesale electricity suppliers has increased, the great majority of them hold with relatively small market shares vis-à-vis the large traditional wholesale electricity supplier. The electricity supply by smaller electricity producers is largely based on renewable sources of energy, which also depends on the weather conditions.The empirical evidence suggests that wholesale-to-retail electricity supply structures are shifting slowly from a monopoly market structure towards greater competition with the characteristicsof product differentiation and market segmentation. The regression analysis for the electricity price formation for the retail electricity distribution enterprise confirms the significance of thecosts for the purchased electricity, expenses for wages and for taxes. The multivariate factor analysis confirms the importance of recognition and business trust in the wholesale-to-retail-saleelectricity supply chain management.

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Section: The Analysis Of Liberalisation Of the Electricity Market In mentioning

confidence: 99%

The analysis of liberalisation of the electricity market in Slovenia

Bonjec¹,

Papler²

2020

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“…In the current field of energy research, people have largely focused on the development and use of electrical energy. In the era of power liberalization [7], the task of ensuring power supply has become more and more important. Researchers use different predictive models to conduct research and analysis on power in different countries or regions.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting India’s Electricity Demand Using a Range of Probabilistic Methods

Zhou

2019

Energies

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With serious energy poverty, especially concerning power shortages, the economic development of India has been severely restricted. To some extent, power exploitation can effectively alleviate the shortage of energy in India. Thus, it is significant to balance the relationship between power supply and demand, and further stabilize the two in a reasonable scope. To achieve balance, a prediction of electricity generation in India is required. Thus, in this study, five methods, the metabolism grey model, autoregressive integrated moving average, metabolic grey model-auto regressive integrated moving average model, non-linear metabolic grey model and non-linear metabolic grey model-auto regressive integrated moving average model, are applied. We combine the characteristics of linear and nonlinear models, making a prediction and comparison of Indian power generation. In this way, we enrich methods for prediction research on electrical energy, which avoids large errors in trends of electricity generation due to those accidental factors when a single predictive model is used. In terms of prediction outcomes, the average relative errors from five models above are 1.67%, 1.62%, 0.84%, 1.84%, and 1.37%, respectively, which indicates high accuracy and reference value of these methods. In conclusion, India’s power generation will continue to grow with an average annual growth rate of 5.17% in the next five years (2018–2022).

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“…We reviewed the literature concerning the estimation of the demand function of electricity and found some previous related studies, which are summarized in Table 1. There have been many studies about the demand for energy, which will be explained below in detail [8,12,[14][15][16][17][18][19][20][21][22]. However, there are few studies on the estimation of the industrial electricity demand function.…”

Section: A Brief Literature Reviewmentioning

confidence: 99%

Demand Function for Industrial Electricity: Evidence from South Korean Manufacturing Sector

Kim

Yoo

2019

Sustainability

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Electricity is a crucial input to the industrial production of South Korea. Estimating the demand function for electricity in the manufacturing sector is an important task because electricity consumption in the manufacturing sector accounts for 56.3% of total electricity consumption in South Korea. Thus, this article tries to estimate the demand function for industrial electricity in the manufacturing sector of South Korea using cross-sectional data for analyzing the influence of manufacturing firms’ characteristics. To this end, 946 observations collected from a nationwide survey of manufacturing firms in 2018 are used and analyzed. As a robust approach, the least absolute deviations estimation method is applied to obtaining the demand function. The results show that the price elasticity and the sales amount elasticity of the industrial electricity demand are estimated to be −0.9206 and 0.2568, respectively, which are statistically significant at the 1% level. Furthermore, the economic benefits of industrial electricity consumption are computed to be 1.46 times as great as the price of electricity. The results of this study can be utilized in policy planning, making, and evaluation.

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Household and industrial electricity demand in Europe

Cited by 64 publications

References 43 publications

The analysis of liberalisation of the electricity market in Slovenia

The analysis of liberalisation of the electricity market in Slovenia

Forecasting India’s Electricity Demand Using a Range of Probabilistic Methods

Demand Function for Industrial Electricity: Evidence from South Korean Manufacturing Sector

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