scholarly journals A Stochastic Estimation Framework for Yearly Evolution of Worldwide Electricity Consumption

Forecasting ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 256-266
Author(s):  
Qasem Abu Al-Haija
Keyword(s):  
Energy Demand ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Ar Model ◽  
Electric Energy Consumption ◽  
Electricity Use ◽  
Prediction Scheme ◽  
The World ◽  
Electrical Engineers ◽  
Regression Error

The determination of electric energy consumption is remarked as one of the most vital objectives for electrical engineers as it is highly essential in determining the actual energy demand made on the existing electricity supply. Therefore, it is important to find out about the increasing trend in electric energy demands and use all over the world. In this work, we present a prediction scheme for the progression of worldwide aggregates of cumulative electricity consumption using the time series of the records released annually for the net electricity use throughout the world. Consequently, we make use of an autoregressive (AR) model by retaining the best possible autoregression order recording the highest regression accuracy and the lowest standardized regression error. The resultant regression scheme was proficiently employed to regress and forecast the evolution of next-decade data for the net consumption of electricity worldwide from 1980 to 2019 (in billion kilowatt-hours). The experimental outcomes exhibited that the highest accuracy in regressing and forecasting the global consumption of electricity is 95.7%. The prediction results disclose a linearly growing trend in the amount of electricity issued annually over the past four decades’ observation for the global net electricity consumption dataset.

scholarly journals Prospects of the Russian Coal Industry in the Conditions of Transition to a New Energy Pattern

2020 ◽  
Vol 9 (4) ◽  
pp. 1831-1835
Keyword(s):  
Energy Production ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Coal Industry ◽  
Electric Energy Consumption ◽  
The World ◽  
New Energy ◽  
Forecast Models ◽  
To Come ◽  
Competitive Products

The article analyzes the prospects for changes in the volume of exports of Russian coal due to the reduction of its consumption for energy production by the importing countries. The importance of Russian power generating coal for the energy supply to the world as a whole and to individual importing regions in particular is shown. It is justified that a radical and abrupt refusal to use coal as an energy source in the next few years would hardly be possible because the per capita and the total electric energy consumption has been growing all over the world. To a large extent, this is due to the increase in the number of data centers around the world, which centers do not yet have enough “green” sources of energy to ensure the uninterrupted operation thereof. Therefore, coal exports from Russia to the European countries, China and DPRK will continue to grow in the years to come; this is confirmed by the forecast models built by the authors, which models consider changes in the coal and electricity consumption by major importers. By the time the conditions are ensured for the majority of countries in the world to abandon coal as a source of electricity in order to stop air pollution, Russia will need to find opportunities for its alternative use, an example of which would be the creation and development of production of competitive products of the coal chemical industry.

scholarly journals INCOME ELASTICITY OF ELECTRIC ENERGY CONSUMPTION FOR DIFFERENT ECONOMIC SECTORS IN COUNTRIES OF THE WORLD

2020 ◽  
Vol 7 (3) ◽  
pp. 170-188
Author(s):  
Andre Assis de Salles ◽  
Ana Beatriz Carvalho Werlang ◽  
Illana Geller ◽  
Gabriel Rocha de Almeida Cunha
Keyword(s):  
Economic Development ◽  
Energy Consumption ◽  
Linear Regression ◽  
Energy Demand ◽  
Income Elasticity ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Linear Regression Models ◽  
Economic Sectors ◽  
The World

The causal relationship between energy demand and GDP has been the subject of intense research over the past three decades. The present work seeks to analyze the energy consumption evolution of different countries of the world and the relation of the same with the level of economic development, represented by income. For this purpose, an annual database containing gross domestic product and electricity consumption of 143 countries in the period between 1990 and 2014 was prepared. Thus, linear regression models and autoregressive vector models were used to explain the electricity consumption of countries and groups of countries. The results indicated that there is no standard elasticity behavior for most countries with similar levels of economic development. Despite this, a good performance was observed in the simple linear regression for aggregate data in groups of countries, which indicates the possibility of performing a reliable aggregate planning. Keywords: Electricity Demand, Energy Consumption, Income, GDP, Elasticity.

scholarly journals Parallel Evolutionary Biclustering of Short-term Electric Energy Consumption

2021 ◽  
Author(s):  
Diego P. Pinto-Roa ◽  
Hernán Medina ◽  
Federico Román ◽  
Miguel García-Torres ◽  
Federico Divina ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Search Space ◽  
Consumption Pattern ◽  
Electric Energy Consumption ◽  
System A ◽  
Time Period ◽  
Computation Scheme ◽  
Significant Patterns

The discovery and description of patterns in electric energy consumption time series is fundamental for timely management of the system. A bicluster describes a subset of observation points in a time period in which a consumption pattern occurs as abrupt changes or instabilities homogeneously. Nevertheless, the pattern detection complexity increases with the number of observation points and samples of the study period. In this context, current bi-clustering techniques may not detect significant patterns given the increased search space. This study develops a parallel evolutionary computation scheme to find biclusters in electric energy. Numerical simulations show the benefits of the proposed approach, discovering significantly more electricity consumption patterns compared to a state-of-the-art non-parallel competitive algorithm.

scholarly journals Electric energy consumption of milking process on some Finnish dairy farms

2017 ◽  
Vol 26 (3) ◽  
Author(s):  
Mari Rajaniemi ◽  
Tapani Jokiniemi ◽  
Laura Alakukku ◽  
Jukka Ahokas
Keyword(s):  
Energy Consumption ◽  
Energy Savings ◽  
Electric Energy ◽  
Cooling Water ◽  
Electricity Consumption ◽  
Dairy Farms ◽  
Energy Costs ◽  
Heating Systems ◽  
Electric Energy Consumption ◽  
Energy Saving Potential

The aim of this study was to examine the electric energy consumption of milking process on dairy farms and to evaluate the methods to improve the energy efficiency. The electricity consumption of the milking process was measured on three dairy farms in Southern Finland, and it varied between 37–62 Wh kg-1 milk.  The largest energy saving potential was identified in milk cooling and the heating of cleaning water. Even simple methods, such as placing the condenser of the refrigeration system outside, may reduce the energy consumption of milk cooling by 30%. Efficient milk pre-cooling can reduce the energy consumption of the whole milking process by more than 25%. Even larger energy savings are possible with a sophisticated milk cooling – water heating systems. It was concluded that there is a significant potential to reduce the energy consumption and energy costs of the milking process, and thus to improve the profitability and sustainability of the sector at the same time.

scholarly journals Solar PV for Water Pumping and Irrigation

2015 ◽  
Vol 11 (1) ◽  
pp. 9-28
Author(s):  
I. Patay ◽  
M. Montvajszki
Keyword(s):  
Solar Energy ◽  
Energy Demand ◽  
Electric Energy ◽  
High Energy ◽  
Energy Costs ◽  
Solar Pv ◽  
Irrigation Period ◽  
Water Pumping ◽  
Pump Station ◽  
The World

Water pumping for irrigation has a relatively high energy demand, depending on the applied irrigation method. At the same time, there is a considerable energy from the sun during the irrigation period. The solar PV (photovoltaic) technology may be suitable to ensure electric energy for pumping in many cases in agriculture, where the electric network is not available or reduction of the energy costs is wanted. There are some pilot plants for water pumping on the base of solar energy in the world and the spreading of these solar technologies is predictable. The solar energy based pumping process can be approached both in theoretical and experimental ways. In this paper, both the theoretical questions of the solar based pumping process and the experimental results of a model testing pump station powered by PV panels are shown.

MATHEMATICAL MODELS FOR MONITORING AND CONTROL OF ELECTRIC ENERGY CONSUMPTION WITH ACCOUNT OF THE SEASONAL FACTOR

2017 ◽  
Vol 11 (5) ◽  
pp. 133-140 ◽  
Author(s):  
Сергей Лавренченко ◽  
Sergey Lavrenchenko ◽  
Людмила Згонник ◽  
Lyudmila Zgonnik ◽  
Инна Гладская ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Daily Basis ◽  
Monitoring And Control ◽  
Theoretical Level ◽  
Electric Energy Consumption ◽  
Energy Meter ◽  
Seasonal Factor

The article proposes a method for predicting the daily energy consumption level for every day of a whole year, taking into account the season-al factor, based on only twelve actual power consumption data by the months of the year. Then a mathematical model is developed for moni-toring and controlling the level of electricity consumption on a daily basis, taking into account the seasonal factor. The model is consistent with a common model for the length of daylight (in hours). In addition, on the basis of this model, a method of monitoring and diagnostics of electricity consumption is presented, which will allow users to monitor the level of power consumption and be timely notified of any deviations from the theoretical level. Finally, this method gives rise to the operational principle for a proposed device, a smart energy meter, for detecting suspicious deviations from the theoretical level. The device will help timely detect over-consumption (or under-consumption) of electricity in order to take preventive measures. The proposed method consists of the following steps: (1) choice of a function to model the level of electricity consumption (theoretical calculated level), (2) choice of a tubular control neighborhood of the graph of the model function, (3) choice of a criterion on when the smart energy meter should notify the user of an unexpected deviation from the theoretical level in the case of exit from the tubular control neighborhood.

scholarly journals Bagging Ensemble of Multilayer Perceptrons for Missing Electricity Consumption Data Imputation

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1772 ◽  
Author(s):  
Seungwon Jung ◽  
Jihoon Moon ◽  
Sungwoo Park ◽  
Seungmin Rho ◽  
Sung Wook Baik ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Missing Values ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Multilayer Perceptrons ◽  
Imputation Methods ◽  
Electric Energy Consumption ◽  
Consumption Data ◽  
Bagging Ensemble

For efficient and effective energy management, accurate energy consumption forecasting is required in energy management systems (EMSs). Recently, several artificial intelligence-based techniques have been proposed for accurate electric load forecasting; moreover, perfect energy consumption data are critical for the prediction. However, owing to diverse reasons, such as device malfunctions and signal transmission errors, missing data are frequently observed in the actual data. Previously, many imputation methods have been proposed to compensate for missing values; however, these methods have achieved limited success in imputing electric energy consumption data because the period of data missing is long and the dependency on historical data is high. In this study, we propose a novel missing-value imputation scheme for electricity consumption data. The proposed scheme uses a bagging ensemble of multilayer perceptrons (MLPs), called softmax ensemble network, wherein the ensemble weight of each MLP is determined by a softmax function. This ensemble network learns electric energy consumption data with explanatory variables and imputes missing values in this data. To evaluate the performance of our scheme, we performed diverse experiments on real electric energy consumption data and confirmed that the proposed scheme can deliver superior performance compared to other imputation methods.

scholarly journals The Impact of the COVID-19 Pandemic on Electricity Consumption and Economic Growth in Romania

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2394
Author(s):  
Georgeta Soava ◽  
Anca Mehedintu ◽  
Mihaela Sterpu ◽  
Eugenia Grecu
Keyword(s):  
Economic Growth ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Negative Impact ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Electric Energy Consumption ◽  
The One ◽  
The Impact

This paper analyzes the impact of the COVID-19 pandemic on economic growth and electricity consumption and investigates the hypothesis of the influence of this consumption on the gross domestic product (GDP) for Romania. Using time series on monthly electricity consumption and quarterly GDP and a multi-linear regression model, we performed an analysis of the evolution of these indicators for 2007–2020, a comparison between their behavior during the financial crisis vs. COVID-19 crisis, and empirically explore the relationships between GDP and electricity consumption or some of its components. The results of the analysis confirm that the shock of declining activity due to the COVID-19 pandemic had a severe negative impact on electric energy consumption and GDP in the first half of 2020, followed by a slight recovery. By using a linear regression model, long-term relationships between GDP and domestic and non-household electricity consumptions were found. The empirically estimated elasticity coefficients confirm the more important impact of non-household electricity consumption on GDP compared to the one of domestic electricity consumption. In the context of the COVID-19 pandemic, the results of the study could be useful for optimizing energy and economic growth policies at the national and European levels.

scholarly journals An Analysis of Electricity Consumption Patterns in the Water and Wastewater Sectors in South East England, UK

2019 ◽  
Author(s):  
Aman Majid ◽  
Iliana Cardenes ◽  
Conrad Zorn ◽  
Tom Russell ◽  
Keith Colquhoun ◽  
...  
Keyword(s):  
Energy Use ◽  
Energy Intensity ◽  
Electricity Consumption ◽  
Water Flooding ◽  
Published Data ◽  
Electricity Use ◽  
The World ◽  
Water And Wastewater ◽  
South East England ◽  
The Uk

The water and wastewater sectors are energy-intensive, and so a growing number of utility companies are seeking to identify opportunities to reduce energy use. Though England’s water sector is of international interest, in particular due to the early experience with privatisation, for the time being very little published data on energy usage exists. We analyse telemetry data from Thames Water Utilities Ltd. (TWUL), which is the largest water and wastewater company in the UK and serves one of the largest mega-cities in the world, London. In our analysis, we (1) break down sectoral energy use into their components, (2) present a statistical method to analyse the long-term trends in use, as well as the seasonality and irregular effects in the data, (3) derive energy-intensity (kWh m3) figures for the system, and (4) compare the energy-intensity of the network against other regions in the world. Our results show that electricity use grew during the period 2009 to 2014 due to capacity expansions to deal with growing water demand and storm water flooding. The energy-intensity of the system is within the range of reported figures for systems in other OECD countries. Plans to improve the efficiency of the system could yield benefits in lower the energy-intensity, but the overall energy saving would be temporary as external pressures from population and climate change are driving up water and energy use.

scholarly journals Study on Household Energy Usage Patterns in Urban and Rural Areas of Nepal

2020 ◽  
Vol 15 (3) ◽  
pp. 402-410
Author(s):  
Dinesh Kumar Shahi ◽  
Hom Bahadur Rijal ◽  
Masanori Shukuya
Keyword(s):  
Rural Area ◽  
Rural Areas ◽  
Urban Areas ◽  
Energy Demand ◽  
Energy Use ◽  
Family Income ◽  
Electricity Consumption ◽  
Income Level ◽  
Electricity Production ◽  
Electricity Use

In the last decades, the household’s energy demand has increased significantly in various countries including Nepal. In the case ofNepal, 94% of energy use is in the domestic sector. There is a possibility of a huge increase in electricity production, but we are stillsuffering from load shedding due to the high electricity demand. Electricity use is an important factor for the quality of life anddevelopment of a nation. There is not a sufficient number of researches done about electricity consumption in different climaticregions of Nepal which are analyzed by the income level of residents. This study gives descriptive information on the household’senergy uses patterns and investigates the electricity use rate, using electrical appliances in households. This study also identifies themajor source of energy use and awareness of energy use. The data were collected from 442 households in three regions in the winterseason of 2018. Kalikot is a rural area, Chitwan is a semi-urban, and Kathmandu is an urban area. We have collected electricity bills,family income, and family size, electricity using appliances, expenditure for energy and energy use for heating/cooling, cooking, andlighting. The electricity was used only for lighting purposes in the rural area, but other electrical appliances were used in semi-urbanand urban areas. The amount of electricity use has not affected by household income level in the rural area, but it has affected in semi-urban and urban areas. The level of education affects the use of the LED significantly. This study would be helpful to know theelectricity use patterns which is useful for energy saving and energy management of the rural and urban areas of Nepal.

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