An analysis of smart meter technologies for efficient energy management in households and organizations

Abstract

Digitization of the energy industry is the key to a successful energy transition. To this end, all consumers and generators should be able to communicate permanently with each other so that the energy system as a whole functions safely and efficiently. Smart meter technology can make a contribution to this. Unfortunately, the rollout selected in Germany initially affects only about 11% of all consumers. The objective of this paper is therefore to determine the current status of this technology in companies and to pursue the research question of which factors influence acceptance and use. For this purpose, an extensive literature search with more than 50 keywords was conducted in scientific databases. After reviewing and cleaning the literature, 47 papers were selected for the literature review and considered in detail. The literature review was conducted using eight evaluation criteria: Origin and year of publication, identification of trends with Big Data and AI (artificial intelligence), type of organization, type of data, collection method, number of participants, type of data collection, and analysis method. In order to evaluate the main statements and results of the considered works, we also performed a Strengths–Weaknesses–Opportunities–Threats Analysis (SWOT).Our analysis showed that: (1) The studies only address households as end-users, no companies are considered as end-users in relation to smart meter technology. (2) Technical aspects and barriers were often chosen as research focus and content, and secondary data were mostly used. (3) Studies examining soft factors such as acceptance criteria in general and for decision making are rare and also focused purely on residential customers. (4) Of the studies that collected primary data as part of their research, 71% used the survey method of a questionnaire survey. Further research should investigate company acceptance criteria, as this can increase implementation and make better predictions about the technology.