A comparison of MV Distribution System State Estimation methods using field data

Hayes, Barry; Prodanović, Milan

doi:10.1109/pesgm.2015.7285656

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…The comparative study among DSSE's based on accuracy, computational burden, complexity, mean absolute percentage error (MAPE), absolute value error etc. are summarised in Table 2 from available literatures [62,67,[76][77][78][79][80] for proper selection and modification of DSSE algorithm.…”

Section: Comparative Study For Various Dssementioning

confidence: 99%

A combined survey on distribution system state estimation and false data injection in cyber‐physical power distribution networks

Bhattar

Pindoriya

Sharma

2021

IET cyber-phys. syst.

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The penetration of renewable energy sources (RES) in distribution systems has entailed heavy deployment of monitoring and control infrastructure in the distribution system. This deployment of sensors and communication infrastructure has led to the emergence of a modern grid with a complex cyber-physical network. On one hand, the cyber-physical system can play a pivotal role in coordination and control of distribution systems through distribution system state estimation (DSSE). On the other hand, the risk caused by cyber-attack has emerged as a major challenge for grid operation. The modelling aspects, namely DC loads, plug-in-vehicle and distributed generators (DGs) in DSSE and security aspects in cyber-physical distribution systems, are highlighted herein. This paper is divided into different sections emphasising on the problems and challenges associated with DSSE, cyber-attack focussing primarily on impact of false data injection (FDI) attack and co-simulation platform for investigation of vulnerability of cyber-physical systems. A comparative study among various DSSE and challenges namely, pseudo-measurement, time synchronisation and communication issues are discussed. The potential investigation of FDI and need for a co-simulation platform in distribution systems for risk analysis are also addressed. The opportunities and future research in the field of cyber-physical distribution systems are discussed in depth. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Comparative Study For Various Dssementioning

confidence: 99%

A combined survey on distribution system state estimation and false data injection in cyber‐physical power distribution networks

Bhattar

Pindoriya

Sharma

2021

IET cyber-phys. syst.

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“…The WLS estimator is particularly sensitive to outlier points, since the larger the residual, the larger an influence it has on the quadratic objective function. In order to improve the robustness of the SE in the presence of bad data, a number of authors have developed "robust" estimators [32], [33], which work by re-assigning the weights ofW as the SE minimisation is solved, so that the weights of suspected bad data (outlier) points are reduced in the calculation. In this paper, the equivalent weight function based on robust statistics theory in [32] is applied to create a "robust" WLS estimator.…”

Section: ) State Estimation Algorithmmentioning

confidence: 99%

User Flexibility Aware Price Policy Synthesis for Smart Grids

Mancini¹,

Mari²,

Melatti³

et al. 2015

2015 Euromicro Conference on Digital System Design

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In order to optimally manage a modern electricity distribution network, peaks in residential users demand should be avoided, as this can reduce energy and network asset management costs. Furthermore, this must be done without compressing residential users demand. To this aim, in a demand response setting, residential users are given a price policy, which economically motivates them to shift their loads in order to achieve this goal. However, if the price policy for all users is similar, this demand response may result in simply shifting the demand peaks (peak rebound), leaving the problem unsolved. In this paper we propose a novel methodology which i) for each network substation s, automatically computes the desired power profile to be kept in order to optimally manage the network itself; ii) for each network substation s, automatically synthesizes individualized price policies for residential users connected to s, so that s is kept at the desired profile. Note that price policies individualization avoids the peak rebound problem, as different users have different low tariff areas. Furthermore, our methodology measures the flexibility of a residential user as the capacity needed by a home energy storage system (e.g., a battery) to always follow the given price policy, thus mitigating residential users discomfort. We show the feasibility of our approach on a realistic scenario taken from an existing medium voltage Danish distribution network.

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Number and location of meters to improve state estimation in distribution networks

Rivera

Baeza

2017

2017 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

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A comparison of MV Distribution System State Estimation methods using field data

Cited by 5 publications

References 15 publications

A combined survey on distribution system state estimation and false data injection in cyber‐physical power distribution networks

A combined survey on distribution system state estimation and false data injection in cyber‐physical power distribution networks

User Flexibility Aware Price Policy Synthesis for Smart Grids

Number and location of meters to improve state estimation in distribution networks

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