European and national policies are aimed at reducing greenhouse gases and increasing energy efficiency-also in the household sector. For this purpose, new solutions for private homes based on information and communication technologies (ICT) are being developed and tested. However, up to now, hardly anyone has seen, experienced or lived in an environment that offers the full range of ICT-based energy management solutions. In this study, consumer reactions to a fully furnished and equipped smart home are analysed using focus groups (four groups with a total of 29 participants). The analysis looks at consumer perceptions of and reactions to an energy management system which optimizes electricity consumption based on different ICT solutions. The topics that were demonstrated in practice and then discussed with the participants included variable tariffs, smart metering, smart appliances, and home automation. In general, there were positive group reactions to the smart home environment. Consumers saw many advantages for themselves; especially the chance to save money. However, giving up high levels of flexibility and adapting everyday routines to fit in with electricity tariffs were regarded as difficult. Smart appliances and smart meters were therefore considered to be necessary elements by most participants. Concerns regarding data privacy played a major role in one of the groups.As greenhouse gases (GHG) contribute to global warming, European and national policies are aiming to reduce them. The German government has set the target to become a low- J Consum Policy (2012) 35:23-41

Little is known about consumer preferences on dynamic pricing. Two studies are conducted to analyze this topic. A survey shows that consumers without experience prefer conventional programs. Test residents of a smart home were more open to dynamic pricing. They also prefer well structured programs.

. Those involved Electric Vehicle (EV) users, Liquefied Petroleum Gas (LPG) and Compressed Natural Gas (CNG) vehicle users as well as persons with strong interest in EV and smart home technologies. In order to characterize early adopters the same item-sets concerning attitudes regarding climate change, prices and innovations as well as corresponding socio-demographic characteristics, were used throughout all these studies and have been joined now and analyzed together. Additionally, regression methods have been applied in order to characterize early EV adopters based on a subsample of EV company car users in the French-German context. A binary logit model explaining private EV purchase intention has been developed. According to this model, early private EV adopters are likely to have a higher level of income, to have a household equipped with two or more cars and to travel more than 50 kilometers a day, not necessarily by car. This model additionally shows that possibilities to experience EV (e.g. by test drives) are important leverages to support adoption of EV by private car buyers. Respondents who already decided to privately purchase an EV show significantly lower general price sensitivities than the LPG and CNG vehicle users.

This paper analyses the potential of demand response (DR) in households considering smart appliances and electric vehicles (EV). A model-based analysis allows calculating the technically possible and economically feasible load-shifting potential, while behavioral analysis enables estimating the potential of the model with real-user experiences in a smart home laboratory. The modeling results show that EV are especially suitable for load-shifting activities due to their long parking hours and high power as well as energy demand. Together with smart household appliances (dishwasher, washing machine, tumble dryer) most of the electricity demand can be technically shifted in time. The experimental results strongly support the modeling results -especially with demand automation. However, user acceptance of load-shifting activities depends largely on the design of direct real-time feedback, the comprehensiveness of electricity pricing, and the customer friendliness of smart household appliances.

This study analyses the integration of electric vehicles (EV) into the German power grid including different demand side management (DSM) approaches from a technical, economical and user perspective. For this an overview of the future German electricity market with the focus on EV integration is given. It is shown that for conservative EV penetration rates the effect on the electricity generation is marginal while the shortage in the regional and local electricity grid could be already significant. DSM in combination with smart grids can help to tackle this issue by controlled charging of EVs. One simple concept is to postpone the charging process by offering incentives to vehicle users e. g. with dynamic electricity tariffs. The common Time-of-Use (TOU) tariff defines in advance a dynamic tariff scheme according to the load forecast for the following days. This allows to release the local electricity grid and to increase the share of renewable energies: In times of high electricity generation by renewable energies and low electricity demand the price is low and vice versa. The impact of these dynamic tariffs on the charging process of EVs is shown in a techno-economic analysis for an exemplary urban high voltage grid by an optimising energy model. These strong impacts are however somewhat reduced by the acceptance and the low profits for the single user. At least for the users in a German field trial, environmental aspects played a major role in influencing the charging behaviour -this gives still hope for the future.