# Data Analytics for Profiling Low-Voltage Customers with Smart Meter Readings
## 6 Conclusions  
This paper proposes a methodology for finding typical load profiles for LV customers by using clustering techniques. Such a task is particularly challenging due to the great diversity of electricity use by such customers. The main scientific contribution of the paper is that new and updated LPs closer to the actual characteristics of customers of different categories are provided to the DSO, on the basis of recent and large databases gathered from extensive measurement campaigns, which covered much of the Italian territory. For reaching this goal, different clustering algorithms are exploited in a novel output-based approach that does not a priori prefer a specific clustering technique but uses one that provides the best results. The results obtained by applying the proposed approach to several categories of end-users confirm the improvement in the accuracy of the network representation. The results demonstrate that one LP only for each category of customers is not enough to represent the actual behavior of LV customers, especially the residential ones that exhibit great variability in their consumptions. This result is convincing because the inaccuracy due to coincident peaks of groups of customers nominally homogeneous is overcome. The comparison of two recent databases demonstrates that some characteristics of the customer electrical behavior were maintained over the period of a few years. Finally, this paper proposes an easy association of the most suitable typical load profile to new customers by considering only features available for the DSO (e.g., annual energy, rated power, monthly peak). Thus, it represents a concrete improvement of the state of the art and a step forward in the field of load profiling since the outcome of the research activity can be exploited in current real-life applications and the possible functionalities of advanced metering infrastructures are only partially enabled and would not fully be enabled in the near future. The proposed example of application of the LPs proves the validity of the approach. Future works include the extensive application of the resulted profiles to operation and planning studies and the comparison of the typical load profiles of customers of different European Countries. Data curation, G.P., S.R., and M.T. ; formal analysis, G.P. and M.T. ; funding acquisition, F.P. ; methodology, F.P., G.P., and M.T. ; software, M.T. ; supervision, F.P. and G.P. ; validation, G.P. and M.T. ; visualization, S.R. ; writing--original draft, G.P. and M.T. ; writing--review and editing, F.P., G.P., S.R., and M.T. All authors have read and agreed to the published version of the manuscript. Figure 21: Voltage profile of the node N_35 during the winter working day (real days in light grey, mean of real day values in green, DSO’s LPs in orange, and new LPs in blue; voltage limit in red). Funding: This research has been supported by the project \"Planning and flexible operation of micro-grids with generation, storage and demand control as a support to sustainable and efficient electrical power systems: regulatory aspects, modelling and experimental validation\", funded by the Italian Ministry of Education, University and Research (MIUR) Progetti di Ricerca di Rilevante Interesse Nazionale (PRIN) Bando 2017-grant 2017K4 JZEE, and by the European Commission project \"OSMOSE-Optimal System-Mix of Flexibility Solutions for European Electricity\", within the Horizon 2020 framework (program: H2020-EU.3.3.4.--A single, smart European electricity grid; topic: ICE-04-2017--Demonstration of system integration with smart transmission grid and storage technologies with increasing share of renewables; grant agreement ID: 773406). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Restrictions apply to the availability of the data included in the databases. Data was obtained from a third party and they are available for the authors within a research project with the permission of the third party.