A practical approach to observability analysis and state estimation in distribution networks

Brinkmann, B.; Negnevisky, Michael

doi:10.1109/pesgm.2016.7741271

Cited by 4 publications

(3 citation statements)

References 17 publications

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“…Due to the random nature of the measurement noise, it is always possible that an estimated parameter does not satisfy (1) or (4). No matter how many measurements are placed in a network.…”

Section: A Compliance Ratiomentioning

confidence: 99%

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A practical approach to meter placement in distribution networks

Brinkmann

Scott

Bicevskis

et al. 2017

2017 IEEE Manchester PowerTech

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Abstract-This paper presents a novel approach to the optimal meter placement problem in distribution networks. Conventional methods place meters in order to achieve a predefined level of accuracy for the estimated parameters such as voltages and currents. However, there is no generic method to determine this desired accuracy value for the individual parameters. Hence, a uniform accuracy value is generally chosen. Considering that parameters which are not in proximity to their constraint do not need to be monitored with a high level of accuracy, using a uniform accuracy for every estimated parameter may not be optimal. The method proposed in this paper takes a new approach which accounts for the proximity of the estimated parameters to their constraints. This approach can potentially reduce the number of required metering devices compared to conventional meter placement methods, while providing a practical level of state estimation accuracy.Index Terms-Optimal meter placement, uncertainty, power system measurements, distribution network state estimation

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“…Due to the random nature of the measurement noise, it is always possible that an estimated parameter does not satisfy (1) or (4). No matter how many measurements are placed in a network.…”

Section: A Compliance Ratiomentioning

confidence: 99%

“…the voltage compliance range) and its physical properties (e.g. thermal limits of network components) [4]. In [5] a new meter placement method has been proposed that increases the accuracy of the estimated parameters depending upon their proximity to their respective constraints under worst case considerations.…”

Section: Introductionmentioning

confidence: 99%

A practical approach to meter placement in distribution networks

Brinkmann

Scott

Bicevskis

et al. 2017

2017 IEEE Manchester PowerTech

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“…Hence, using this data to set NLTC transformer taps to suitable positions based on all possible loading regimes within any given year can assist maintaining the network voltages within admissible limits cost-effectively over longer time periods. Furthermore, with improved distribution network observability and robust distribution state estimation, more data will become available to distribution network operators to improve confidence in the network state and the influence of NLTC transformer tap settings [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

A Practical Approach to Optimising Distribution Transformer Tap Settings

Paoli

Brinkmann²,

Negnevitsky

2020

Energies

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This paper proposes a method of determining the optimal tap settings for no-load distribution transformers with tap-changing capabilities that is practical to apply in real distribution networks. The risk of low voltage distribution networks violating voltage constraints is impacted by the increasing uptake of distributed energy resources and embedded generation. Some of this risk can be alleviated by suitably setting no-load transformer tap settings, however, modifying these taps requires customer outages and must be infrequent. Hence, loading over the entire year must be considered to account for seasonal variations when setting these taps optimally. These settings are determined using evolution strategy optimisation based on an average loading case. Monte Carlo simulations are used to calculate the probability that the terminal voltages on the distribution transformer secondary terminals violate the network voltage limits when the optimal set of taps for the average case is applied over a whole year. This algorithm was tested on several cases of a real distribution feeder of varying complexity, and produces a sufficiently-optimal set of taps without significant computation time.

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