290 research outputs found
Measurement and analysis of PMU reporting latency for smart grid protection and control applications
Emerging power system protection and control applications require faster-responding measurements and more accurate knowledge of the actual latency of the measurement and communications systems. A new method for accurately determining the reporting latency of a phasor measurement unit (PMU) has been developed and demonstrated. This method operates in real-time, works passively for any existing PMU without requiring changes to the PMU hardware or software, and it is very accurate - providing a measurement uncertainty of ¡500 ns in many cases, significantly surpassing the 0.002 s accuracy requirement in the most recent IEEE Synchrophasor standard. Only low-cost hardware and open source software are required. It is particularly important to understand end-to-end system latency, including the impact of local and wide-area communications, rather than just the latency of the PMU device; the proposed method also supports such practical measurements. It is therefore shown how this advance can be used to enable efficient, but realistic, cross-domain power system simulation studies, which incorporate measurement and communications delays. These capabilities address complexity and uncertainty in the design and operation of future PMU-based protection and control functions for new smart grid services
PMU-Based ROCOF Measurements: Uncertainty Limits and Metrological Significance in Power System Applications
In modern power systems, the Rate-of-Change-of-Frequency (ROCOF) may be
largely employed in Wide Area Monitoring, Protection and Control (WAMPAC)
applications. However, a standard approach towards ROCOF measurements is still
missing. In this paper, we investigate the feasibility of Phasor Measurement
Units (PMUs) deployment in ROCOF-based applications, with a specific focus on
Under-Frequency Load-Shedding (UFLS). For this analysis, we select three
state-of-the-art window-based synchrophasor estimation algorithms and compare
different signal models, ROCOF estimation techniques and window lengths in
datasets inspired by real-world acquisitions. In this sense, we are able to
carry out a sensitivity analysis of the behavior of a PMU-based UFLS control
scheme. Based on the proposed results, PMUs prove to be accurate ROCOF meters,
as long as the harmonic and inter-harmonic distortion within the measurement
pass-bandwidth is scarce. In the presence of transient events, the
synchrophasor model looses its appropriateness as the signal energy spreads
over the entire spectrum and cannot be approximated as a sequence of
narrow-band components. Finally, we validate the actual feasibility of
PMU-based UFLS in a real-time simulated scenario where we compare two different
ROCOF estimation techniques with a frequency-based control scheme and we show
their impact on the successful grid restoration.Comment: Manuscript IM-18-20133R. Accepted for publication on IEEE
Transactions on Instrumentation and Measurement (acceptance date: 9 March
2019
What Can Wireless Cellular Technologies Do about the Upcoming Smart Metering Traffic?
The introduction of smart electricity meters with cellular radio interface
puts an additional load on the wireless cellular networks. Currently, these
meters are designed for low duty cycle billing and occasional system check,
which generates a low-rate sporadic traffic. As the number of distributed
energy resources increases, the household power will become more variable and
thus unpredictable from the viewpoint of the Distribution System Operator
(DSO). It is therefore expected, in the near future, to have an increased
number of Wide Area Measurement System (WAMS) devices with Phasor Measurement
Unit (PMU)-like capabilities in the distribution grid, thus allowing the
utilities to monitor the low voltage grid quality while providing information
required for tighter grid control. From a communication standpoint, the traffic
profile will change drastically towards higher data volumes and higher rates
per device. In this paper, we characterize the current traffic generated by
smart electricity meters and supplement it with the potential traffic
requirements brought by introducing enhanced Smart Meters, i.e., meters with
PMU-like capabilities. Our study shows how GSM/GPRS and LTE cellular system
performance behaves with the current and next generation smart meters traffic,
where it is clearly seen that the PMU data will seriously challenge these
wireless systems. We conclude by highlighting the possible solutions for
upgrading the cellular standards, in order to cope with the upcoming smart
metering traffic.Comment: Submitted; change: corrected location of eSM box in Fig. 1; May 22,
2015: Major revision after review; v4: revised, accepted for publicatio
P and M class phasor measurement unit algorithms using adaptive cascaded filters
The new standard C37.118.1 lays down strict performance limits for phasor measurement units (PMUs) under steady-state and dynamic conditions. Reference algorithms are also presented for the P (performance) and M (measurement) class PMUs. In this paper, the performance of these algorithms is analysed during some key signal scenarios, particularly those of off-nominal frequency, frequency ramps, and harmonic contamination. While it is found that total vector error (TVE) accuracy is relatively easy to achieve, the reference algorithm is not able to achieve a useful ROCOF (rate of change of frequency) accuracy. Instead, this paper presents alternative algorithms for P and M class PMUs which use adaptive filtering techniques in real time at up to 10 kHz sample rates, allowing consistent accuracy to be maintained across a ±33% frequency range. ROCOF errors can be reduced by factors of >40 for P class and >100 for M class devices
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Novel performance evaluation of information and communication technologies to enable wide area monitoring systems for enhanced transmission network operation
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The penetration of renewable energy sources has increased significantly in recent years due to the ongoing depletion of conventional resources and the transition to a low carbon energy system. Renewable energy sources such as wind energy are highly intermittent and unpredictable in nature, which makes the operation of the power grid more dynamic and therefore more complex. In order to operate the power system reliably under such conditions, Phasor Measurement Units (PMUs) through the use of satellite technology can offer a state-of-the-art Wide Area Monitoring System (WAMS) for improving power system monitoring, control and protection. They can improve the operation by providing highly precise and synchronised measurements near to real-time with higher frequency and accuracy. In order to achieve such objectives, a high-speed and reliable communications infrastructure is required to transfer time-critical PMU data from remote locations to the control centre. The signals measured by PMUs are transmitted across Local and Wide Area Networks, where they may encounter excessive delays. Signal delays can have a disruptive effect and make applications at best inefficient and at worse ineffective.
The main research contribution of this thesis is the performance evaluation of communication infrastructures for WAMS. The evaluation begins from inside substations and continues over wide areas from substations to control centre. Through laboratory-based investigations and simulations, the performance of communications infrastructure in a typical power system substation has been analysed. In addition, the performance evaluation of WAMS communications infrastructure has been presented. In the modelling and analysis, an existing WAMS as installed on the GB transmission system has been considered. The actual PMU packets as received at the Phasor Data Concentrator (PDC) were captured for latency analysis. A novel algorithmic procedure has been developed and implemented to automate the large-scale latency calculations. Furthermore, the internal delays of PMUs have been investigated, determined and analysed. Subsequently, the WAMS has been simulated and detailed comparisons have been performed between the simulated model results and WAMS performance data captured from the actual WAMS. The validated WAMS model has been used for analysing possible future developments as well as to test newly proposed mechanisms, protocols, etc. in order to improve the communications infrastructure performance
Measurement Platform for Latency Characterization of Wide Area Monitoring, Protection and Control Systems
Wide area monitoring, protection and control (WAMPAC) systems have emerged as a critical technology to improve the reliability, resilience, and stability of modern power grids. They are based on phasor measurement unit (PMU) technology and synchronized monitoring on a wide area. Since these systems are required to make rapid decisions and control actions on the grid, they are characterized by stringent time constraints. For this reason, the latency of WAMPAC systems needs to be appropriately assessed. Following this necessity, this article presents the design and implementation of a measurement platform that allows latency characterization of different types of WAMPAC systems in several operating conditions. The proposed WAMPAC Characterizer has been metrologically characterized through a WAMPAC Emulator and then used to measure the latency of a WAMPAC system based on an open-source platform frequently used by transmission system operators (TSOs) for the implementation of their PMU-based wide area systems
Near Real-Time Distributed State Estimation via AI/ML-Empowered 5G Networks
Fifth-Generation (5G) networks have a potential to accelerate power system
transition to a flexible, softwarized, data-driven, and intelligent grid. With
their evolving support for Machine Learning (ML)/Artificial Intelligence (AI)
functions, 5G networks are expected to enable novel data-centric Smart Grid
(SG) services. In this paper, we explore how data-driven SG services could be
integrated with ML/AI-enabled 5G networks in a symbiotic relationship. We focus
on the State Estimation (SE) function as a key element of the energy management
system and focus on two main questions. Firstly, in a tutorial fashion, we
present an overview on how distributed SE can be integrated with the elements
of the 5G core network and radio access network architecture. Secondly, we
present and compare two powerful distributed SE methods based on: i) graphical
models and belief propagation, and ii) graph neural networks. We discuss their
performance and capability to support a near real-time distributed SE via 5G
network, taking into account communication delays
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