System dynamics modeling of households' electricity consumption and cost-income ratio: A case study of Latvia

被引：23

作者：

Bariss U. ^{[1
]}

Bazbauers G. ^{[1
]}

Blumberga A. ^{[1
]}

Blumberga D. ^{[1
]}

机构：

[1] Institute of Energy Systems and Environment, Riga Technical University, Azenes iela 12/1, Riga

来源：

Environmental and Climate Technologies | 2017年 / 20卷 / 01期

关键词：

Consumer behavior; Electricity; Energy efficiency; Households; System dynamics;

D O I：

10.1515/rtuect-2017-0009

中图分类号：

学科分类号：

摘要：

Increased energy efficiency of the building sector is high on the list of priorities for energy policy since better energy efficiency would help to reduce impact on climate change and increase security of energy supply. One aim of the present study was to find a relative effect of growth of demand for energy services due to changes in income, energy consumption per unit of demand due to technological development, changes in electricity price and household income on household electricity consumption in Latvia. The method applied included system dynamics modeling and data from a household survey regarding the relationship between electricity saving activities and the electricity cost-income ratio. The results revealed that, in direct contrast to the expected, a potential reduction of the electricity consumption is rather insensitive to electricity price and electricity cost-income ratio, and that the efficiency of technologies could be the main drivers for future electricity savings. The results suggest that support to advancement of technologies and faster replacement of inefficient ones rather than influencing the energy price could be effective energy policy measures. The model, developed in the study could be used in similar assessments in other countries. ©2017 Uldis Bariss, Gatis Bazbauers, Andra Blumberga, Dagnija Blumberga.

引用

页码：36 / 50

页数：14

共 24 条

[1]

Directive 2012/27/EU of the European Parliament and of the Council of 25 October 2012 on energy efficiency, Off. J. Eur. Union Dir., pp. 1-56, (2015)

[2]

Funds I., Schemes E.O., Clean Energy for All the New Energy Efficiency Measures, (2016)

[3]

Unit E., Siemens A., European Green City Index, (2009)

[4]

Mills B., Schleich J., Household transitions to energy efficient lighting, Energy Econ., 46, pp. 151-160, (2014)

[5]

Reveiu A., Smeureanu I., Dardala M., Kanala R., Modelling domestic lighting energy consumption in Romania by integrating consumers behavior, Procedia Comput. Sci., 52, pp. 812-818, (2015)

[6]

Manjunath M., Singh P., Mandal A., Parihar G.S., Consumer behaviour towards electricity - A field study, Energy Procedia, 54, pp. 541-548, (2014)

[7]

Frederiks E.R., Stenner K., Hobman E.V., Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour, Renew. Sustain. Energy Rev., 41, pp. 1385-1394, (2015)

[8]

Schultz P.W., Estrada M., Schmitt J., Sokoloski R., Silva-Send N., Using in-home displays to provide smart meter feedback about household electricity consumption: A randomized control trial comparing kilowatts, cost, and social norms, Energy, 90, pp. 351-358, (2015)

[9]

Poznaka L., Laicane I., Blumberga D., Blumberga A., Rosa M., Analysis of electricity user behavior: Case study based on results from extended household survey, Energy Procedia, 72, pp. 79-86, (2015)

[10]

Timma L., Bariss U., Dandens A., Blumberga A., Blumberga D., Framework for the assessment of household electricity saving by integrating behavioural aspects, Energy Procedia, 95, pp. 517-521, (2016)

← 1 2 3 →