A Behavioral Economics Approach to Residential Electricity Consumption

Abstract

Consumer behavior is complex and is difficult to represent in traditional economic theories of decision-making. This paper focuses on the development of an agent-based approach to analyze people's behavior in consuming electricity using a behavioral economics framework, where the consumer is the main agent of power systems. This approach may bring useful insights for distribution companies and regulatory agencies, helping to shift thinking to a more user-centric approach. The emergent properties of electricity consumption are modeled by the means of consumer's heuristics, taking into account the electricity price, consumer's satisfaction level, willingness to invest in new technologies, social interactions, and marketing strategies by the power utility. Analysis on the emergent behavior of this approach through simulation studies showed that it is indeed valuable, as does not require in-depth data of all details on human behavior. However, it contributes to the understanding of relations among various objects involved in electricity consumption.

Impact Analysis of Customized Feedback Interventions on Residential Electricity Load Consumption Behavior for Demand Response

“…For example, low understanding of or interest in the provided feedback information could bring barriers [13]. The response to the feedback differs from person to person, which is related to the understanding level of information and individual performance [24]. Thus, taking the characteristics of various households into consideration when designing the feedback programs may increase the effects of information feedback.…”

User-Aware Electricity Price Optimization for the Competitive Market

“…Consumption and cost awareness have an important role for the effectiveness of demand response schemes. However, many customers do not understand how to lower electricity costs and call for a device that displays the current power output [18], and consumer behavior is complex and difficult to represent in traditional economic theories of decision-making [19]. The work in [20] shows how real-time price elasticity provides important information on the demand response of consumers and provides a quantification of the real-time relationship between total peak demand and spot market prices by finding a low real-time price elasticity.…”

The State of the Art in Smart Grid Domain: A Network Modeling Approach

“…Some of the key examples are as following. For example it is applied for demand response in (Kim, Zhang, Van Der Schaar, & Lee, 2016;Siebert, Sbicca, Aoki, & Lambert-Torres, 2017), smart home management (Dusparic, Harris, Marinescu, Cahill, & Clarke, 2013;G. Wang et al, 2017), electric vehicle chagrining and discharging (Golpayegani, Dusparic, Taylor, & Clarke, 2016;Jannati & Nazarpour, 2017;Yao, Lim, & Tsai, 2017).…”