Consumer behavior, social influence, and smart grid implementation

Abstract

To achieve the goals of German energy transition especially in renewable energy shares, the smart grid will play a key role in managing the demand able to match more volatile supply and optimizing the entire electricity system. Even though the system transformation is technically feasible, the successful transition cannot live without end users willing to transform their way of using energy. This thesis has explored possible roles of individual consumers in the smart grid implementation and in detail analyzed their influential factors. An online survey was conducted to capture preferences and behaviors of energy consumers during the time period of November 2013 to January 2014. The three roles of private electricity consumers - as consumers consuming electricity through appliances, as citizens holding attitudes towards smart grid applications, and as potential producers of electricity - are targeted. Constructs from the theory of planned behavior were tested by using a sample of 517 German citizens. Structural equation models of individual’s electricity saving behavior, their intention to participate in smart grid applications and investment behavior in solar panels were built. It was found that determinants of attitude, perceived norm, and perceived behavioral control together explain 32%-56% of the variance in the three behaviors. Attitude was found to be the most influential factor of individual electricity saving behavior, as well as of citizens’ intentions to participate in smart grid applications. For solar panel investment, it is perceived behavioral control that has the highest impact on the behavior. As the smart grid concept is not well understood by common people, education program and information campaigns are needed, in which social norm marketing is worth more attention, ascribable to the considerable impact caused by the diffusion of norms through social networks. To examine this social influence effect, empirically founded agent-based models for the above-mentioned three behaviors were created to estimate possible behavior changes brought by social norms at the aggregate level. Simulation results show that a reduction of total consumptions by 20% could be achieved in the virtual community due to behavior conformity induced by identified adopters. The potential impact of social norms on home generation and load shift are also promising.