# Grid Nodes Selection Strategies for Power Quality Monitoring
## 4 Problems and Future Prospects
### Sophisticated Attention to Every PQ Event
It is noteworthy that the free oscillations frequency, including the process in Figure 6a, in the electrical circuit is inversely proportional to the product of inductance and capacitance; therefore, the minimum requirement can be defined with the following equation (after applying Nyquist-Shannon sampling theorem):  
\[\frac{f_{s}}{2}\geq\frac{1}{2\pi\sqrt{LC}}, \tag{6}\]  
where \(f_{s}\)--sampling frequency; \(L\)--inductance; \(C\)--capacitance. Figure 7: **(a)** Spectrum of voltage transient of Figure 6a: clear peaks at 50 Hz (0 dB; fundamental frequency) and 615 Hz (\(-24\) dB; transient frequency); **(b)** Spectrum of voltage oscillations of Figure 6b; **(c)** Spectrum of voltage oscillations of Figure 6b: focus on 0–20 kHz band. Since all three phases spectrums are almost similar, a single curve is given. All the mentioned issues with transients are directly related to PQ monitors' allocation strategy, and in the future dealing with those issues will lead to the introduction of new nodes selection criteria. Some examples: (1) high commutation frequency zones; (2) high lightning probability regions (based on long-term meteorological data); (3) focus on selected surge arrester operation; (4) investigation of displacement of surge arresters and overall overvoltage mitigation strategy (i.e., mutual effect of all devices); (5) focus on critical and vulnerable loads; (6) investigation of impact on grid equipment, for example, insulators. It is possible that separate special monitors for transient monitoring will be used in the future, but the problem will remain the same--optimization between quantity of monitors, their features and coverage, and price. In addition, measurement transducer issues (such as inappropriate magnitude and phase frequency response) will remain a limiting factor. The future structure of PQ monitoring application is given in Figure 8. Firstly, in comparison with Figure 1, the measurement transducer block is split into two parts. Broadband transducers (with appropriate frequency response) will be designed for high sampling monitors which will output high-precision waveform and broadband spectrum. For example, precise waveform input is required for the wavelet transform tool which can be used in predictive maintenance applications (e.g., impact on insulators evaluation). Secondly, the allocation strategy is strongly dependent on monitor type and its PQ target group. Thirdly, interoperability with all Smart Grid application must be reached in order to achieve the most efficient solutions (including both technical and economic aspects): penalties for grid pollution, compensations, expenditure saving, calculations of CAPEX and OPEX, etc. In Figure 8, most Smart Grid applications (systems) examples are based on terminology used in IEEE Std P2030 [5,27]: supervisory control and data acquisition--SCADA, demand side management--DSM, substation automation--SA, meter data management--MDM (the term closely related to AMI--advanced metering infrastructure), asset management--AM, transmission lines monitoring--TLM (the term closely related to DLR--dynamic line rating), PM--predictive maintenance, DMS--distribution management system, OM--outage management, EV--electric vehicle, WASA--wide-area situational awareness, DG--distributed generation. After integration with other systems, artificial intelligence (AI) algorithms will be used to deliver solutions for many purposes: history and data storage (e.g., impedance database), data classification and statistics (including political reports), compliance verification, legislation and amendments, decision making and their correction, assessment methodic and management strategy correction, machine learning (supervised, semi-supervised, unsupervised, reinforced) and software updates, forecasting, maintenance planning, grid automation commands (including \"self-healing\"), demand side response planning, etc.