Distribution System Model Calibration With Big Data From AMI and PV Inverters

Peppanen, Jouni; Reno, Matthew J.; Broderick, Robert Joseph; Grijalva, Santiago

doi:10.1109/tsg.2016.2531994

Cited by 70 publications

(35 citation statements)

References 17 publications

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“…In terms of algorithm design for DSSE and topology identification, one considerable difference between the methods proposed for systems with only smart meters and systems with PMUs is the "small phase angle difference assumption". Hence, due to unavailability of phase angle data in absence of PMUs many papers have assumed that the nodal voltage phase angles in a system are almost equal [65], [66], [84]. While this assumption introduces bounded inaccuracies in the final estimation/identification outcomes, it enables system operators to monitor the state of distribution systems without PMUs.…”

Section: B Pmu Applications and Impacts On Dssementioning

confidence: 99%

A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems

Dehghanpour

Wang

et al. 2019

IEEE Trans. Smart Grid

334

173

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This paper presents a review of the literature on State Estimation (SE) in power systems. While covering some works related to SE in transmission systems, the main focus of this paper is Distribution System State Estimation (DSSE). The paper discusses a few critical topics of DSSE, including mathematical problem formulation, application of pseudomeasurements, metering instrument placement, network topology issues, impacts of renewable penetration, and cyber-security. Both conventional and modern data-driven and probabilistic techniques have been reviewed. This paper can provide researchers and utility engineers with insights into the technical achievements, barriers, and future research directions of DSSE.

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Section: B Pmu Applications and Impacts On Dssementioning

confidence: 99%

A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems

Dehghanpour

Wang

et al. 2019

IEEE Trans. Smart Grid

334

173

View full text Add to dashboard Cite

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“…Voltage and power or equivalent current measurements from AMI are used to estimate the 1-phase or 3-phase DN models [120]. Incorporation of data from smart meters is still challenging because of its non-synchronized and low data rate.…”

Section: Inclusion Of Smart Meter Measurement Data In Dssementioning

confidence: 99%

Distribution system state estimation-A step towards smart grid

Ahmad

Rasool

Özsoy

et al. 2018

Renewable and Sustainable Energy Reviews

141

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“…This can be implemented by exploiting the large amount of data from the advanced metering infrastructure (AMI) [8]. Therefore, with respect to the accuracy and quality, network topology and reliable control of all devices, implementation of the Big Data environment is of crucial importance.…”

Section: Big Data Analysis Modelmentioning

confidence: 99%

Smart Grid Development: Multinational Demo Project Analysis

Oļeiņikova

Mutule

Obushevs

et al. 2016

Latvian Journal of Physics and Technical Sciences

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This paper analyses demand side management (DSM) projects and stakeholders' experience with the aim to develop, promote and adapt smart grid tehnologies in Latvia. The research aims at identifying possible system service posibilites, including demand response (DR) and determining the appropriate market design for such type of services to be implemented at the Baltic power system level, with the cooperation of distribution system operator (DSO) and transmission system operator (TSO). This paper is prepared as an extract from the global smart grid best practices, smart solutions and business models.

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Distribution System Model Calibration With Big Data From AMI and PV Inverters

Cited by 70 publications

References 17 publications

A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems

A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems

Distribution system state estimation-A step towards smart grid

Smart Grid Development: Multinational Demo Project Analysis

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