How information propagation in social networks can improve energy savings based on time of use tariff

Abstract

The expected savings from energy efficiency projects are divided into two, direct savings and indirect savings. Direct savings refer to savings obtained through the personal effort of an individual implemen-ting some energy efficiency measures. Indirect savings are achieved through information transmission of energy efficiency measures from an individual to his/her neighbours. In this paper information trans-mission is seen as human contribution for energy savings through interactions within the social network. This paper formulates a mathematical model that calculates an expected energy cost savings model that consists of direct and indirect savings. Indirect savings are made through social interactions of people in a network over time. Direct savings calculations are based on the Homeflex time of use tariff of South Africa. A case study of thirty-six households is used to illustrate the impact individuals have on the rest of their network in transferring information about the energy efficiency measures they have implemented. The results show that social interactions can improve energy efficiency savings and consequently reduce electricity cost.

Quantitative Analysis of Urban Polycentric Interaction Using Nighttime Light Data: A Case Study of Shanghai, China

“…Also, the urban spatial interaction among cities can measure and reflect the intensity of the relationship between cities. A growing body of literature focuses on regional spatial interaction and attempts to measure and evaluate their structure and characteristics [7][8][9]. Many researchers have explored the spatial interaction between cities [5,10,11] by analyzing the spatial distribution of university students [12] and participation in higher education [13], checking improvement in energy efficiency savings [9], monitoring operational performance [14] and so on.…”

“…A growing body of literature focuses on regional spatial interaction and attempts to measure and evaluate their structure and characteristics [7][8][9]. Many researchers have explored the spatial interaction between cities [5,10,11] by analyzing the spatial distribution of university students [12] and participation in higher education [13], checking improvement in energy efficiency savings [9], monitoring operational performance [14] and so on. It has been argued that urban spatial interaction plays a vital role in urbanization and has a significant impact on urban socio-economic development [15].…”