A Model for Predicting Unregulated Energy Usage

被引：0

作者：

Frimpong, Emmanuel Asuming ^{[1
]}

Twumasi, Elvis ^{[2
]}

机构：

[1] Kwame Nkrumah Univ Sci & Technol, Dept Elect & Elect Engn, Kumasi, Ghana

[2] Univ Educ, Dept Elect & Elect Engn, Winneba, Ghana

来源：

2020 IEEE PES & IAS POWERAFRICA CONFERENCE | 2020年

关键词：

Energy consumption; Plug load; Unregulated energy load; PLUG LOADS; OFFICE BUILDINGS; CONSUMPTION; ALGORITHM;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The paper presents a technique for estimating the energy consumption of unregulated energy loads in offices. It uses the optimum power and optimum usage period in three modes of device usage, for the estimation. The usage modes are active mode, low active (idle) mode and off mode. The optimum powers and usage times are inserted into a mathematical equation to give the estimated energy consumption. The optimum values were optioned, using the non-dominated sorting genetic algorithm II (NSGA II), from a range of measured values. The approach was tested using energy consumption data for unregulated energy loads in an office of the Kwame Nkrumah University of Science and Technology, Kumasi. The results obtained show that the model has a high degree of accuracy.

引用

页数：5

共 18 条

[1] Short-term electric load forecasting based on Kalman filtering algorithm with moving window weather and load model [J].

Al-Hamadi, HM ;

Soliman, SA .

ELECTRIC POWER SYSTEMS RESEARCH, 2004, 68 (01) :47-59

[2]

[Anonymous], ENERGENIE MIHO001 GA

[3]

[Anonymous], 2014, P 11 INT C MOB UB SY

[4]

[Anonymous], ENERGENIE MIHO005 AD

[5]

[Anonymous], ENERGENIE MIHO032 MO

[6]

Cheung H.Y., 2012, LBNL6192E

[7] A fast and elitist multiobjective genetic algorithm: NSGA-II [J].

Deb, K ;

Pratap, A ;

Agarwal, S ;

Meyarivan, T .

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197

[8] Plug load energy analysis: The role of plug loads in LEED certification and energy modeling [J].

Fuertes, Gwen ;

Schiavon, Stefano .

ENERGY AND BUILDINGS, 2014, 76 :328-335

[9] Experimental Analysis of the Input Variables' Relevance to Forecast Next Day's Aggregated Electric Demand Using Neural Networks [J].

Hernandez, Luis ;

Baladron, Carlos ;

Aguiar, Javier M. ;

Calavia, Lorena ;

Carro, Belen ;

Sanchez-Esguevillas, Antonio ;

Garcia, Pablo ;

Lloret, Jaime .

ENERGIES, 2013, 6 (06) :2927-2948

[10] Climatic and internal factors affecting future UK office heating and cooling energy consumptions [J].

Jenkins, D. ;

Liu, Y. ;

Peacock, A. D. .

ENERGY AND BUILDINGS, 2008, 40 (05) :874-881

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