## 1 Introduction
For example, in Denmark, along with a fault-ride-through requirement, a fast fault current injection requirement (also only during a symmetrical fault) has been introduced: not only for type B and type C power plants connected to the HV and MV grids, but also for type A (up to 125 kW) connected to the LV grid [10,11]. Notably, this requirement should not be confused with a reactive power control requirement for long-duration voltage level regulation (also included in the documents) where various algorithms, reviewed in [12], are used (e.g., Q(U), Q(P), and others). The scope of this paper is focused on the short-duration events. Most equipment is sensitive to voltage sags [13]. Thus, the effective practical implementation of a PQ monitoring system is essential in anticipation of both legal regulations and the need to develop an efficient mitigation strategy--optimal grid observability must be achieved with a limited number of monitors. Since measurement opportunities (e.g., access to the electrical grid, the frequency of the event occurrence, and the functionality of monitors) and resources (e.g., financial, human, transport, data processing and storage, and the communication network) are always limited, theoretical research of voltage sag physics (including, in particular, the propagation mechanism) is indispensable [5]. A lack of (scientific) literature on the topic (especially on voltage sags propagation mechanisms) was encountered during the projects on the implementation of a PQ monitoring system for the Lithuanian DSO grid. A good intuition with a theoretical background is important not only for the optimization of monitor placement, but also for further processing of measurement data, which is nowadays mainly implemented manually. Therefore, the second motivation of the work is the anticipation of artificial intelligence (AI) algorithms for PQ assessment: a versatile theoretical database is a prerequisite for machine learning (typical characteristics, threshold values, patterns, waveform, etc.). For scientific and technical progress in both spheres, a comprehensive database is required: grid voltage, topology, and other features, type and main characteristics of the sag, primary reason(s) of origin, waveform patterns and their alterations along the propagation path, interconnection with other PQ events, etc. Moreover, the database could also be useful in other PQ disciplines such as legal documents and the preparation (or amendment) of standards. On the other hand, there are some examples when PQ research is started from monitoring in practice; however, these cases are massive and long-running campaigns. To begin with, an Australian multi-year (2002-2016) monitoring experience is presented in [14]: PQ data were collected from over 12,000 sites in order to investigate many key problems. The following further research avenues, determined in [14], are useful to highlight the significance of this paper (either directly or indirectly): (1) the optimal number of sites (since \"installation of PQ instrumentation remains costly\"); (2) voltage sag reporting; (3) distributed generation impact on PQ (mitigation is not mentioned). Another example is [15]--in Italy \"the most extensive program in the world\", with 3500 fixed monitors in the MV grid. In contrast to the Australian project, [15] focuses only on the identification of the origin of a voltage sag in HV/MV substations, and outputs the binary result--either a TSO HV grid or a DSO MV grid. A few compact paragraphs about voltage sags propagation are included in reference [15]; however, the amount of information is sufficient neither for allocation nor for AI algorithms, the propagation path is not investigated, the sags are not grouped by their properties (fault type, phase-to-phase, or phase-to-ground, etc.).