scholarly journals System analysis of power consumption by nonferrous metallurgy enterprises on the basis of rank modeling of individual technocenosis castes

2018 ◽  
Vol 226 ◽  
pp. 04018 ◽  
Author(s):  
Roman V. Klyuev ◽  
Igor I. Bosikov ◽  
Oksana A. Gavrina ◽  
Vladimir Ch. Revazov
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Ferrous Metallurgy ◽  
Relative Error ◽  
System Analysis ◽  
Electricity Consumption ◽  
Automated System ◽  
Electric Power Consumption ◽  
Process Equipment ◽  
Industrial Enterprises

To increase energy efficiency at non-ferrous metallurgy enterprises, an integrated system approach for estimation of electricity consumption is needed. The paper presents the results of a rank analysis of the power consumption of individual castes of process equipment on the basis of an integrated energy survey of the enterprise. A methodology for constructing mathematical models for calculating and predicting electric power consumption for all castes of the ranked H-distribution of technocenosis has been developed. For the first time, according to the established regularity of the H-distribution, a mathematical model for predicting power consumption has been developed, including a quantitative analysis of the energy characteristics of consumers by individual castes of technocenosis. A retrospective check of the relative error in the prediction of electricity consumption showed that for the model it does not exceed 2%, which is significantly lower than the relative error of the prediction for a number of models of other types. The received model is recommended for use in the automated system of dispatching control of power consumption for the purposes of short-term forecasting of electric power consumption at industrial enterprises of non-ferrous metallurgy.

scholarly journals Estimating Rural Electric Power Consumption Using NPP-VIIRS Night-Time Light, Toponym and POI Data in Ethnic Minority Areas of China

2020 ◽  
Vol 12 (17) ◽  
pp. 2836
Author(s):  
Fei Zhao ◽  
Jieyu Ding ◽  
Sujin Zhang ◽  
Guize Luan ◽  
Lu Song ◽  
...  
Keyword(s):  
Power Consumption ◽  
Ethnic Minority ◽  
Electric Power ◽  
Rural Areas ◽  
Infrared Imaging ◽  
Electricity Consumption ◽  
Electric Power Consumption ◽  
Average Error ◽  
Night Time ◽  
Spatial Differences

Aiming at the problem that the estimation of electric power consumption (EPC) by using night-time light (NTL) data is mostly concentrated in large areas, a method for estimating EPC in rural areas is proposed. Rural electric power consumption (REPC) is a key indicator of the national socio-economic development. Despite an improved quality of life in rural areas, there is still a big gap between electricity consumption between rural residents and urban residents in China. The experiment takes REPC as the research target, selects Dehong (DH) Dai Jingpo Autonomous Prefecture of Yunnan Province as an example, and uses the NTL data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) carried by the Suomi National Polar-orbiting Partnership (NPP) Satellite from 2012 to 2017, toponym and points-of-interest (POI) data as the main data source. By performing kernel density estimation to extract the urban center and rural area boundaries in the prefecture, and combining the county-level boundary data and electric power data, a linear regression model of the total rural NTL intensity and REPC is estimated. Finally, according to the model, the EPC in ethnic minority rural areas is estimated at a 1-km spatial resolution. The results show that the NPP-REPC model can simulate REPC within a small average error (17.8%). Additionally, there are distinct spatial differences of REPC in ethnic minority areas.

INFLUENCE OF CAPACITANCE, DISTANCE FROM ARCS TO WALLS ON THE EFFICIENCY OF ARCS AND ELECTRICITY CONSUMPTION IN EAF

2020 ◽  
pp. 72-81
Author(s):  
A.N. Makarov ◽  
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Electricity Consumption ◽  
Slag Layer ◽  
Specific Consumption ◽  
Electric Power Consumption ◽  
Heavy Duty

The influence of the distance from the arc to the walls in the entire nomenclature row of arc steelmaking furnaces with a capacity of 0.5 to 120 tons on the efficiency of the arcs and the specific consumption of electricity in the furnaces was investigated. In low-tonnage EAF, the arcs are close to the walls and the efficiency of the arcs is small and amounts to 30…35 %, and the specific electric power consumption for melting is 650 kWh/t. In heavy-duty EAF, the arcs are located far from the walls, the arc efficiency is 46…49 % in the absence of a slag layer, and the specific electric power consumption for melting is 375…385 kWh/t.

scholarly journals Analysis of the Effects of the Home Energy Management System from an Open Innovation Perspective

2018 ◽  
Vol 4 (3) ◽  
pp. 31 ◽  
Author(s):  
EungSuk Park ◽  
BoRam Kim ◽  
SooHyun Park ◽  
Daecheol Kim
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Real Time ◽  
Energy Management ◽  
Management System ◽  
Electricity Consumption ◽  
Electric Power Consumption ◽  
Energy Management System ◽  
Home Energy Management ◽  
Home Energy Management System

The Home Energy Management System (HEMS) is a system for the efficient electric power consumption of each household. It can provide real-time electricity cost information according to electricity consumption, and households can immediately control their consumption of electricity. In this study, we analyzed the effects of the HEMS on the stability of demand for electric power. To do this, we analyzed the causal relationship between the amounts of electric power generation and consumption, from the system dynamics perspective. From the analysis, we found that in the current structure, the fluctuation of the quantity of demand became large due to the time delay in households recognizing the electric bill and adjusting their electric power consumption. However, when the HEMS was introduced, it could be seen that electric power demand remained stable since consumers could see their electricity bill in real-time and could manage their electricity consumption by themselves.

scholarly journals A novel classification regression method for gridded electric power consumption estimation in China

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Mulin Chen ◽  
Hongyan Cai ◽  
Xiaohuan Yang ◽  
Cui Jin
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Infrared Imaging ◽  
Electricity Consumption ◽  
Ordinary Least Squares ◽  
Regression Method ◽  
Electric Power Consumption ◽  
Percentage Error ◽  
Spatially Explicit ◽  
Nighttime Light

Abstract Spatially explicit information on electric power consumption (EPC) is crucial for effective electricity allocation and utilization. Many studies have estimated fine-scale spatial EPC based on remotely sensed nighttime light (NTL). However, the spatial non-stationary relationship between EPC and NTL at prefectural level tends to be overlooked in existing literature. In this study, a classification regression method to estimate the gridded EPC in China based on imaging NTL via a Visible Infrared Imaging Radiometer Suite (VIIRS) was described. In addition, owing to some inherent omissions in the VIIRS NTL data, the study has employed the cubic Hermite interpolation to produce a more appropriate NTL dataset for estimation. The proposed method was compared with ordinary least squares (OLS) and geographically weighted regression (GWR) approaches. The results showed that our proposed method outperformed OLS and GWR in relative error (RE) and mean absolute percentage error (MAPE). The desirable results benefited mainly from a reasonable classification scheme that fully considered the spatial non-stationary relationship between EPC and NTL. Thus, the analysis suggested that the proposed classification regression method would enhance the accuracy of the gridded EPC estimation and provide a valuable reference predictive model for electricity consumption.

scholarly journals Rancang Bangun Alat Kontrol dan Monitoring Konsumsi Listrik Lampu Penerangan Jalan Umum Berbasis Mikrokontroler ATMega 2560

2018 ◽  
Vol 17 (3) ◽  
pp. 427
Author(s):  
Surya Puja Anggara ◽  
A.A Ngurah Amrita ◽  
Duman Care Khrisne
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Electrical Power ◽  
Electricity Consumption ◽  
Electric Power Consumption ◽  
User Needs ◽  
Street Lighting ◽  
Road Users ◽  
Electrical Power Consumption ◽  
Sd Card

Abstract—Public street lighting (LPJU) is a road infrastructure that is very important for road users at night. The constraints faced by User managers in an area in LPJU management are the problem of maintenance, monitoring, electricity consumption, and limited workforce. In an effort to overcome this problem, this study designed a tool in the LPJU system that can control LPJU ignition according to user needs by combining the timer and light sensor functions, and can monitor electricity consumption by calculating the power consumption or kWh meter and recording data on accumulation of electric power consumption every day at 06.00 WITA automatically stored on the micro SD Card. The accumulated data last recorded for 1 (one) month at the beginning of each month at 08.00 WITA will be sent using SMS services to users periodically. In addition, the user can monitor at any time with the "lapor" SMS format, the monitoring data sent in the form of the last electrical power consumption used by LPJU at that time.

Software including the functions of automated analysis of electric power consumption in pipeline oil transportation

2011 ◽  
Vol 8 (1) ◽  
pp. 233-238
Author(s):  
R.M. Bogdanov ◽  
S.V. Lukin
Keyword(s):  
Power Consumption ◽  
Electric Power ◽  
Data Model ◽  
Automated Analysis ◽  
Petroleum Products ◽  
Electric Power Consumption ◽  
Scientific Center ◽  
Relational Data Model ◽  
Oil Transportation ◽  
Academy Of Sciences

Oil and petroleum products transportation is characterized by a significant cost of electric power. Correct oil and petroleum products accounting and forecasting requires knowledge of many factors. The software for norms of electric power consumption analysis for the planned period was developed at the Ufa Scientific Center of the Russian Academy of Sciences. Based on the principles of the relational data model, a schematic diagram/arrangement for the main oil transportation objects was developed, which allows to hold the initial data and calculated parameters in a structured manner.

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