scholarly journals Residential and industrial electricity consumption in Taiwan: Weather or macroeconomic condition (or both)

2022 ◽  
Vol 39 ◽  
pp. 100795
Author(s):  
De-Chih Liu
Keyword(s):  
Electricity Consumption ◽  
Macroeconomic Condition

Ray of Hope: Hopelessness Increases Electricity Consumption for Lighting

2014 ◽  
Author(s):  
Ping Dong ◽  
Xun (Irene) Huang ◽  
Chen-Bo Zhong
Keyword(s):  
Electricity Consumption

Thermal/electric energy generation and CO2 production for greenhouse facilities

2019 ◽  
Vol 2 (3) ◽  
pp. 141-151
Author(s):  
O. E. Gnezdova ◽  
E. S. Chugunkova
Keyword(s):  
Carbon Dioxide ◽  
Power Distribution ◽  
Power Plants ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Vegetable Crops ◽  
Carbon Dioxide Injection ◽  
Electricity Rates ◽  
Traditional Patterns ◽  
Generation Power

Introduction: greenhouses need microclimate control systems to grow agricultural crops. The method of carbon dioxide injection, which is currently used by agricultural companies, causes particular problems. Co-generation power plants may boost the greenhouse efficiency, as they are capable of producing electric energy, heat and cold, as well as carbon dioxide designated for greenhouse plants.Methods: the co-authors provide their estimates of the future gas/electricity rates growth in the short term; they have made a breakdown of the costs of greenhouse products, and they have also compiled the diagrams describing electricity consumption in case of traditional and non-traditional patterns of power supply; they also provide a power distribution pattern typical for greenhouse businesses, as well as the structure and the principle of operation of a co-generation unit used by a greenhouse facility.Results and discussion: the co-authors highlight the strengths of co-generation units used by greenhouse facilities. They have also identified the biological features of carbon dioxide generation and consumption, and they have listed the consequences of using carbon dioxide to enrich vegetable crops.Conclusion: the co-authors have formulated the expediency of using co-generation power plants as part of power generation facilities that serve greenhouses.

Electricity consumption and economic growth in ASEAN

2017 ◽  
Vol 5 (2) ◽  
pp. 16
Author(s):  
Ahmad Ghazali Ismail ◽  
Arlinah Abd Rashid ◽  
Azlina Hanif
Keyword(s):  
Economic Growth ◽  
Energy Use ◽  
Electricity Consumption ◽  
Panel Estimation ◽  
Real Gdp ◽  
Long Run ◽  
Bidirectional Relationship ◽  
Short Run ◽  
Using Data ◽  
The Relationship

The relationship and causality direction between electricity consumption and economic growth is an important issue in the fields of energy economics and policies towards energy use. Extensive literatures has discussed the issue, but the array of findings provides anything but consensus on either the existence of relations or direction of causality between the variables. This study extends research in this area by studying the long-run and causal relations between economic growth, electricity consumption, labour and capital based on the neo-classical one sector aggregate production technology mode using data of electricity consumption and real GDP for ASEAN from the year 1983 to 2012. The analysis is conducted using advanced panel estimation approaches and found no causality in the short run while in the long-run, the results indicate that there are bidirectional relationship among variables. This study provides supplementary evidences of relationship between electricity consumption and economic growth in ASEAN.

Study of the operation of an artificial neural network that works in the electric network in order to prevent emergency conditions.

2020 ◽  
Vol 14 (1) ◽  
pp. 48-54
Author(s):  
D. Ostrenko ◽  
Keyword(s):  
Neural Networks ◽  
Learning Algorithm ◽  
Electricity Consumption ◽  
Electrical Energy ◽  
Energy System ◽  
Electrical Networks ◽  
Electric Networks ◽  
Electric Network ◽  
Time Dynamics ◽  
Emergency Situations

Emergency modes in electrical networks, arising for various reasons, lead to a break in the transmission of electrical energy on the way from the generating facility to the consumer. In most cases, such time breaks are unacceptable (the degree depends on the class of the consumer). Therefore, an effective solution is to both deal with the consequences, use emergency input of the reserve, and prevent these emergency situations by predicting events in the electric network. After analyzing the source [1], it was concluded that there are several methods for performing the forecast of emergency situations in electric networks. It can be: technical analysis, operational data processing (or online analytical processing), nonlinear regression methods. However, it is neural networks that have received the greatest application for solving these tasks. In this paper, we analyze existing neural networks used to predict processes in electrical systems, analyze the learning algorithm, and propose a new method for using neural networks to predict in electrical networks. Prognostication in electrical engineering plays a key role in shaping the balance of electricity in the grid, influencing the choice of mode parameters and estimated electrical loads. The balance of generation of electricity is the basis of technological stability of the energy system, its violation affects the quality of electricity (there are frequency and voltage jumps in the network), which reduces the efficiency of the equipment. Also, the correct forecast allows to ensure the optimal load distribution between the objects of the grid. According to the experience of [2], different methods are usually used for forecasting electricity consumption and building customer profiles, usually based on the analysis of the time dynamics of electricity consumption and its factors, the identification of statistical relationships between features and the construction of models.

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