The impact of synchronized human activities on power system frequency

Yin, Lina; Zhang, Ye; Guo, Jiahui; Zhou, Dao; Culliss, Jerel; Irminger, Philip; Liu, Yilu

doi:10.1109/pesgm.2014.6939472

Cited by 10 publications

(4 citation statements)

References 3 publications

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“…For the sake of the sensitivity analysis carried out in the case study, fully correlated estimation errors related to the load demand are modelled as in (2), where µ p is a time-varying mean value according to:…”

Section: B Modelling Of Correlated Errorsmentioning

confidence: 99%

“…We assume that such oscillation is an harmonic content of the overall estimation error, due for example, to some systematic error of the forecast or measurement system. Hence, in the case study, (4) is coupled with the stochastic model provided by (2).…”

Section: B Modelling Of Correlated Errorsmentioning

confidence: 99%

“…The FDR is a FNET/GridEye device, developed at Virginia Tech, that measures the frequency, phase angle, and voltage of the power signal found at ordinary electrical outlets. The main goal of the FNET project is to register and analyze frequency variations following large disturbances [2], [3]. In this paper, we follow a different approach.…”

Section: Introduction a Motivationmentioning

confidence: 99%

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Impact of variability, uncertainty and frequency regulation on power system frequency distribution

Mele

Ortega

Zárate-Miñano

et al. 2016

2016 Power Systems Computation Conference (PSCC)

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This work originates from the observation of the frequency distribution of the Irish system as obtained from a Frequency Disturbance Recorder lent to the last author by the University of Tennessee. The probability density function of such a distribution appears to be bimodal. The paper first investigates how stochastic sources, in particular, load and wind power estimation errors, impact on the distribution of the frequency of a high-voltage transmission system. Then, possible routes to obtain a bimodal distribution of the frequency are explored and the most likely cause that leads to the observed behaviour of the Irish system is identified. Finally, the paper presents a comparison of different frequency regulation strategies and their impact on the distribution of the frequency. A sensitivity analysis of wind speed and load parameters is presented and discussed based on the IEEE-14 bus system.

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Section: B Modelling Of Correlated Errorsmentioning

confidence: 99%

Section: B Modelling Of Correlated Errorsmentioning

confidence: 99%

Section: Introduction a Motivationmentioning

confidence: 99%

See 1 more Smart Citation

Impact of variability, uncertainty and frequency regulation on power system frequency distribution

Mele

Ortega

Zárate-Miñano

et al. 2016

2016 Power Systems Computation Conference (PSCC)

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“…Employing some data mining techniques, FNET/GridEye historic data can be extremely informative. For instance, statistical analysis is able to demonstrate how the disturbances in the EI system distribute over a year (as shown by Fig.18) [34] and the impact of social events like the FIFA World Cup or the NFL SuperBowl on the power grids can be analyzed [35]. …”

Section: Historic Data Statistical Analysismentioning

confidence: 99%

Wide-Area-Measurement System Development at the Distribution Level: An FNET/GridEye Example

Liu

Zhan

Zhang

et al. 2016

IEEE Trans. Power Delivery

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110

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Electric power grid wide-area monitoring system (WAMS) have been extended from the transmission to distribution level. As the first WAMS deployed at the distribution level, the frequency monitoring network FNET/GridEye uses GPS-timesynchronized monitors called frequency disturbance recorders (FDRs) to capture dynamic grid behaviors. In this paper, the latest developments of monitor design and the state-of-the-art data analytics applications of FNET/GridEye are introduced. Its innovations and uniqueness are also discussed. Thanks to its low cost, easy installation and multi-functionalities, FNET/GridEye works as a cost-effective situational awareness tool for power grid operators and pioneers the development of WAMS in electric power grids.Index Terms-Distribution level, frequency disturbance recorder (FDR), phasor estimation, situational awareness, synchrophasor, wide-area monitoring system (WAMS).

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Wide Area Monitoring through Synchrophasor Measurement

Liu

Zhang

et al. 2016

Smart Grid Handbook

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Considered as one of the most significant developments of smart grid technology, wide area monitoring system (WAMS) utilizing synchrophasor measurements has been expected to help create a more reliable and efficient electric power infrastructure. The use of phasor measurement units (PMUs) can help with understanding, predicting, or even controlling the status of power grid stability in real time. A power system frequency monitoring network (FNET/GridEye) was first proposed in 2001 and then established in 2004. As a pioneering WAMS, it serves the entire North American power grid and other main power grids worldwide through advanced real‐time situational awareness techniques, such as real‐time measurement visualization, accurate disturbance location estimation, and interarea oscillation modal analysis. Furthermore, taking advantage of the vast historical database, postevent analysis, measurement‐aided model validation, and other nonreal‐time applications have also been investigated. Dozens of papers published in the past 10 years had discussed the FNET/GridEye's various functionalities. This chapter summarizes the FNET/GridEye work and presents some of the latest implementations of FNET/GridEye's applications.

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The impact of synchronized human activities on power system frequency

Cited by 10 publications

References 3 publications

Impact of variability, uncertainty and frequency regulation on power system frequency distribution

Impact of variability, uncertainty and frequency regulation on power system frequency distribution

Wide-Area-Measurement System Development at the Distribution Level: An FNET/GridEye Example

Wide Area Monitoring through Synchrophasor Measurement

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