Probabilistic Low-Voltage State Estimation Using Analog-Search Techniques

Abstract

Abstract-Power systems are becoming more complex and the need for increased awareness at the lower voltage levels of the distribution grid requires new tools that provide a reliable and accurate estimation of the system state. This paper describes an innovative state estimation method for low voltage (LV) grids that analyses similarities between a real-time snapshot comprising only a subset of smart meters with real-time communications and fully observed system states present in historical data. Real-time estimates of voltage magnitudes are obtained by smoothing the most similar past snapshots with a data-driven methodology that does not relies on full knowledge of the grid topology and electrical characteristics. Moreover, the output of the LV state estimator is a conditional probability distribution obtained with kernel density estimation. The results show highly accurate estimation of voltage magnitude, even in a scenario characterized by a strong integration of photovoltaic (PV) microgeneration.

Impact of data availability and pseudo‐measurement synthesis on distribution system state estimation

“…First of all, it has to be emphasised that the use of real distribution grids including the F I G U R E 1 1 Adjusted root-mean-square error of reactive power injections among the loaded buses with respect to different types of pseudo-measurement synthesis, smart meter placements and capabilities, and penetrations of measurements LV level with the corresponding SM data is rare in the academic literature in general. A few studies rely on real systems which are nevertheless not larger than a few dozen buses [12,32,33]. The study presented in this study demonstrates the feasibility of a sensitivity analysis related to DSSE on a large real distribution system with almost 1000 buses and more than 2600 customers.…”

“…First of all, it has to be emphasised that the use of real distribution grids including the LV level with the corresponding SM data is rare in the academic literature in general. A few studies rely on real systems which are nevertheless not larger than a few dozen buses [12, 32,33]. The study presented in this study demonstrates the feasibility of a sensitivity analysis related to DSSE on a large real distribution system with almost 1000 buses and more than 2600 customers.…”

Functional Scalability and Replicability Analysis for Smart Grid Functions: The InteGrid Project Approach

“…In real-time timescale, the algorithm uses a state estimation algorithm, the LVSE, to obtain a snapshot of the network in real-time recurring to a subset of the measurements of the smart meter available in the LV network [38,39]. It is essential to highlight the requirement for the usage of an LVSE algorithm since current advanced metering infrastructure (AMI) solutions are unable to provide accurate synchronized real-time measurements in useful time [39]. The main objective of the real-time control module is to assess the actual network conditions registered in real-time and compare them to the forecasted conditions at the preventive stage.…”

Uncertainty Quantification in LV State Estimation Under High Shares of Flexible Resources

“…Ref. [12] proposes a data-driven probabilistic LVSE based on an analog search technique and kernel density estimation. This approach relies on finding similar past patterns, and it assumes real-time information from the secondary substation and voltage values from a number of LV buses, while validation is performed by assessing the impact of varying levels of PV penetration.…”