Watt’s up at Home? Smart Meter Data Analytics from a Consumer-Centric Perspective

Abstract

The key advantage of smart meters over traditional metering devices is their ability to transfer consumption information to remote data processing systems. Besides enabling the automated collection of a customer’s electricity consumption for billing purposes, the data collected by these devices makes the realization of many novel use cases possible. However, the large majority of such services are tailored to improve the power grid’s operation as a whole. For example, forecasts of household energy consumption or photovoltaic production allow for improved power plant generation scheduling. Similarly, the detection of anomalous consumption patterns can indicate electricity theft and serve as a trigger for corresponding investigations. Even though customers can directly influence their electrical energy consumption, the range of use cases to the users’ benefit remains much smaller than those that benefit the grid in general. In this work, we thus review the range of services tailored to the needs of end-customers. By briefly discussing their technological foundations and their potential impact on future developments, we highlight the great potentials of utilizing smart meter data from a user-centric perspective. Several open research challenges in this domain, arising from the shortcomings of state-of-the-art data communication and processing methods, are furthermore given. We expect their investigation to lead to significant advancements in data processing services and ultimately raise the customer experience of operating smart meters.

Energy Transition at Home: A Survey on the Data and Practices That Lead to a Change in Household Energy Behavior

“…Additional critical issues are those concerning the user interface design and interaction modes, goalrelated setting, and the enabling Information and Communication Technologies (ICTs) to implement [49][50][51]. Indeed, ICT technologies are recognized as powerful means to support people in bridging the intention-action gap, as is the case of direct display or smart meters coupled with In-Home Displays (IHDs), which offer interesting opportunities, especially when they provide the user with personalized feedback on the impact of their behavior (both positive and negative) on energy consumption [25,[52][53][54][55]. However, both utilities and customers tend to use informative billing because it is a cost-effective method that can be adopted on a broader scale [48].…”

“…The third section investigates people's familiarity and level of interaction with energy metering devices, also asking the user what meter information she/he believes may be the most effective in modifying her/his own behavior. The given device list is based on the outcomes of the scientific literature review (Section 1.3), ranging from traditional meters returning information by paper or electronic bill, to smart meters connected with In-House Display or Apps [49,[53][54][55][65][66][67]. A list of feedback is similarly provided from the most recurring ones in the literature.…”

Energy Monitoring in the Wild: Platform Development and Lessons Learned from a Real-World Demonstrator

“…Promoted by the advent of the smart grid, these advancements eventually reached the edge of the grid into the houses of electricity end-consumers, with the deployment of Advanced Metering Infrastructure and smart-meters [2]. A multitude of services that rely on smart-meter data are currently under extensive research, and demonstration [3,4]. Services, such as Demand Side Management (DSM), Electric Vehicle Charging (EVC), Distributed Storage and Generation, rely on precise and continuous data [5].…”

Forecasting of Electrical Energy Consumption of Households in a Smart Grid

“…Analysing this data could be useful for utilities in understanding customer consumption behaviours (Bhattarai et al, 2019;Hurst and Curbelo Montañez, 2019). In addition, this data can also be transmitted to the data center for storage and automated processing (Völker et al, 2021). This opens up unprecedented possibilities for the analysis, storage, and combination of energy system data for the two entities which are the consumers and the operators of the electricity grid (Yem Souhe et al, 2021;Mbey et al, 2020).…”