Using smart meters for checking the topology and power flow calculation of a secondary distribution network

Abstract

The paper analyzes options of using smart meters for power flow calculation and for assessing the state of a real three-phase four-wire secondary distribution network based on measurements of average values of active and reactive power and of voltages. The work is based on the authors’ research on allocation of measurements to ensure secondary distribution network observability and on selection of the most efficient method for linear and non-linear state estimation. The paper illustrates solution of a problem on identification composition of load nodes in the phases and reveals challenges related to voltage account in the neutral wire and in its grounding.

DSSE in European-Type Networks Using PLC-Based Advanced Metering Infrastructure

“…In (7), k is the iteration number. According to the augmented matrix approach [30], which shows a high immunity against ill-conditioning, the WLS problem is solved as follows,…”

“…Even though SMs have recently been massively deployed, the feasibility of DSSE in LVDS is still unclear due to the non-synchronized measurements provided by these devices. Despite the fact that the SM has a RTC which updates its time periodically [6], [7], the packet losses, performance deterioration, latency, and signal interference are examples of the consequences of the diverse spectrum characteristics of the crowded communications [8]. This, in turn, diminishes the communication performance of AMI which contains a great number of SMs, many access points, and a mesh network.…”

“…Furthermore, since synchronizing the measurements of a big number of SMs is too costly to be applied in LVDS and may not be taken into account by many DSOs [10], [9], SMs may be programmed so as to send the measurements data at a specific time once per the day for billing purpose, which reduces the benefit of using real-time measurements of SMs [11], [12]. SM measurements are, as a base, nonsynchronized due to errors in the adjustment of the RTC recording the time of measurements, and due to time delay of data transmission by narrow-band communication channels [7]. Thus, it is unfeasible to run a DSSE algorithm based on an instantaneous snapshot of the complete distribution network.…”

Phase topology identification in low-voltage distribution networks: A Bayesian approach

“…Most voltage-based phase identification methods rely on finding the substation phase feeder that has the highest similarity voltage profile to that of the customer [8]. For example, in [3] and [9], the correlation between customers and feeder voltages was used to identify the network connectivity. Although most solutions seek customer-to-feeder voltage correlation, customer-to-customer voltage correlation can also be used in the phase identification problem [10,11].…”

“…Bayes's theorem is shown in (9), where P(A) and P(B) are the independent probabilities for events A and B, and P(A|B) and P(B|A) are the conditional probabilities of A assuming B true, and B assuming A true, respectively.…”