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.

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 Analytical Treatment of Forecasts of Electric Energy Consumption in Latvia

2014 ◽  
Vol 51 (3) ◽  
pp. 3-14
Author(s):  
M. Balodis ◽  
V. Gavars ◽  
J. Andersons
Keyword(s):  
Energy Consumption ◽  
Structural Changes ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Time Span ◽  
Analytical Treatment ◽  
East European ◽  
Electric Energy Consumption ◽  
West Central ◽  
Specific Electricity Consumption

Abstract In the paper, the changes in electric energy consumption are analyzed as associated with structural changes in the Latvian economy of postsocialistic period. To the analysis, a particular approach is applied, which consists in comparison of the basic and specific electricity consumption indices in West-, Central-, and East-European states for the time span of 1990-2010, with differences and tendencies of changes revealed. Tendencies of the type are determined for the electric energy consumption in Latvia, and recommendations are given for the use of such indices in the relevant forecasts.

scholarly journals Analysis of Trams’ Consumption Depending on the Type of Traffic Light Used

2019 ◽  
Vol 18 (6) ◽  
pp. 490-494
Author(s):  
A. Czerepicki ◽  
A. Górka ◽  
J. Szustek
Keyword(s):  
Energy Consumption ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Fixed Time ◽  
Urban Transport ◽  
Traffic Light ◽  
Traffic Lights ◽  
Electric Energy Consumption ◽  
Traffic Light Control ◽  
The Impact

In the XXI century, when environmental awareness is growing and the impact of human activity on the planet is more and more noticeable, striving to minimize energy consumption seems to be a necessary direction in the development of technology. This development cannot take place without an initial understanding and describing the relationships influencing specific technologies. It also needs empirical verification of assumed theories. Modern trams play an important role in the functioning of urban transport. Being one of the oldest modes of environmentally friendly transport, in European capitals they are currently perceived as one of the most convenient means of transport. This is due, among other things, to the high velocity of transport along the route. The energy consumed by trams indirectly depends on the driving characteristics, i. e. speed, acceleration and stops on the route, which are also caused by stopping at traffic light controlled junctions. This paper presents the results of an experiment showing the change in the level of electric energy consumption depending on the applied method of traffic light control. This article presents the conditions influencing the power consumption in trams, describes the possible strategies of traffic lights control and their consequences for other traffic participants. The research was carried out in real conditions in everyday traffic, measuring the level of electricity consumption in case of both fixed-time and actuated signaling with full priority for trams. On the examined section there were both modern asynchronous-drive as well as traditional resistor-drive vehicles. The conclusions drawn from the survey confirm the validity of introducing modern solutions and may be useful for estimating investment costs.

scholarly journals Assessment of the impact of the main technological characteristics of wells on the power consumption of pumps

2021 ◽  
Vol 939 (1) ◽  
pp. 012019
Author(s):  
S Khushiev ◽  
O Ishnazarov ◽  
J Izzatillaev ◽  
S Juraev ◽  
Sh Karakulov
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Hydrodynamic Resistance ◽  
Electric Energy Consumption ◽  
Technological Characteristics ◽  
Binding Function ◽  
Pump Aggregate ◽  
The Impact

Abstract The issue of assessing the impact of the main technological characteristics of wells on the power consumption of pumps is one of the important issues. Based on the analysis of the data obtained in the article, the electric energy consumption of the well pump device the rotational speed of the pump (co); the density of the solution (liquid) (p); the pressure generated by the pump (H); the performance of the pump aggregate (q); depth of the well (H); hydrodynamic resistance (dp); Also, on the basis of the STATISTICA program, the calculation work is carried out, the binding function of the pumps is determined to what extent the factor affects the electricity consumption, and is described in the Pareto diagram.

scholarly journals COVID-19 Pandemic Effect on Energy Consumption in State Universities: Michoacan, Mexico Case Study

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7642
Author(s):  
Luis Bernardo López-Sosa ◽  
José Juan Alvarado-Flores ◽  
Teresita del Niño Jesús Marín-Aguilar ◽  
Juan Carlos Corral-Huacuz ◽  
Arturo Aguilera-Mandujano ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Electric Energy ◽  
Electricity Consumption ◽  
State Universities ◽  
Multiple Impacts ◽  
Electric Energy Consumption ◽  
Production And Consumption ◽  
New Energy ◽  
Virtual Class

The COVID-19 pandemic has generated multiple impacts. In particular, in the educational sector, the virtual class modality generated changes in the patterns of energy consumption at the institutional level; the identification of this consumption will allow us to reflect on new energy saving and efficient use strategies. In this research, we present a case study of the effects of the COVID-19 pandemic on electricity consumption in 13 state universities in Michoacán, Mexico. Electric energy consumption has been evaluated before and during the presence of the COVID-19 between 2019 and 2020. The comparative analysis estimated the reduction in energy consumption and its economic and environmental impact. The results show a considerable decrease in electricity consumption, generating an average saving of 76.24 MWh/month, which translates into an annual emission reduction from 2019 to 2020 of approximately 497 TnCO2e, and in economic terms of $ 8,882.25 USD each month. In general, it was identified that consumption patterns in the use of machinery and computer equipment for administrative activities were drastically reduced. If education continues in virtual or hybrid modes, energy consumption schemes will continue to decline and institutions could move towards resilient, affordable, and sustainable models of energy production and consumption.

scholarly journals Analysis of modern approaches for the prediction of electric energy consumption

2020 ◽  
Vol 10 (1) ◽  
pp. 350-361
Author(s):  
Maksat Kalimoldayev ◽  
Aleksey Drozdenko ◽  
Igor Koplyk ◽  
T. Marinich ◽  
Assel Abdildayeva ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Energy Consumption ◽  
Power Systems ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Energy Systems ◽  
Electric Energy Consumption ◽  
Modern Methods ◽  
Main Factors ◽  
Intelligent Information

AbstarctA review of modern methods of forming a mathematical model of power systems and the development of an intelligent information system for monitoring electricity consumption. The main disadvantages and advantages of the existing modeling approaches , as well as their applicability to the energy systems of Ukraine and Kazakhstan,are identified. The main factors that affect the dynamics of energy consumption are identified. A list of the main tasks that need to be implemented in order to develop algorithms for predicting electricity demand for various objects, industries and levels has been developed.

scholarly journals Forecasting consumption of electric energy by using wavelet transform

2021 ◽  
pp. 75-78
Author(s):  
V. I. Skorokhodov ◽  
◽  
O. A. Lysenko ◽  
A. V. Simakov ◽  
S. A. Gorovoy ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Energy Consumption ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Wavelet Function ◽  
Industrial Scale ◽  
Electric Energy Consumption ◽  
Urgent Task ◽  
Variable Nature

Forecasting electricity consumption is an urgent task for generating companies, since it is currently impossible to accumulate electricity on an industrial scale. Also, the forecast is necessary for consumers to carry out technical work and other activities. The purpose of this work is to make a forecast of electric energy consumption using the wavelet transform, and to select the optimal wavelet function for forecasting. Data for forecasting is a schedule of the load of the shop, which plays the role of a household room, warehouse, as well as a working office for personnel who service electrical installations at a production enterprise. Based on the results of the work, the optimal wavelet function is selected. The result of the work is a representation of the trend of electric energy consumption by the object under consideration, i.e. a forecast presented in the form of a graph, and a detailed component of the projected consumption is obtained, which in theory is justified as interference and sharply variable nature of electricity consumption

Measurements of electric energy consumption in a low energy building in Slovak climatic conditions

2012 ◽  
Vol 7 (3) ◽  
pp. 23-32 ◽  
Author(s):  
Miloslav Bagoňa ◽  
Dušan Katunský ◽  
Martin Lopušniak ◽  
Marián Vertaľ
Keyword(s):  
Energy Consumption ◽  
Electric Energy ◽  
Climatic Conditions ◽  
Low Energy ◽  
Electric Energy Consumption
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