A New Hybrid State Estimation Considering Different Accuracy Levels of PMU and SCADA Measurements

Kabiri, Mehdi; Amjady, Nima

doi:10.1109/tim.2018.2872446

Cited by 47 publications

(23 citation statements)

References 35 publications

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“…Also, different measurement types and locations introduce time synchronization and time skewness issues because of the different latency of the measurements. In this work, we assume that voltage measurements are synchronized using existing synchronization approaches [64]- [67].…”

Section: ) Standard Ieee 123-node Benchmark Systemmentioning

confidence: 99%

Detection of Cyber Attacks on Voltage Regulation in Distribution Systems Using Machine Learning

2021

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Several wired and wireless advanced communication technologies have been used for coordinated voltage regulation schemes in distribution systems. These technologies have been employed to both receive voltage measurements from field sensors and transmit control settings to voltage regulating devices (VRDs). Communication networks for voltage regulation can be susceptible to data falsification attacks, which can lead to voltage instability. In this context, an attacker can alter multiple field measurements in a coordinated manner to disturb voltage control algorithms. This paper proposes a machine learning-based two-stage approach to detect, locate, and distinguish coordinated data falsification attacks on control systems of coordinated voltage regulation schemes in distribution systems with distributed generators. In the first stage (regression), historical voltage measurements along with current meteorological data (solar irradiance and ambient temperature) are provided to random forest regressor to forecast voltage magnitudes of a given current state. In the second stage, a logistic regression compares the forecasted voltage with the measured voltage (used to set VRDs) to detect, locate, and distinguish coordinated data falsification attacks in realtime. The proposed approach is validated through several case studies on a 240-node real distribution system (based in the USA) and the standard IEEE 123-node benchmark distribution system. The results show that the proposed approach can detect low margin attacks (as low as 1% of actual measurements) with up to 99% accuracy. All of the developed source codes of the proposed solution are publicly available at Github.https://github.com/nbhusal/Data-Attack-on-Voltage-Regulation.INDEX TERMS Coordinated control of voltage regulation, data falsification cyber attack, machine learning, and photovoltaic.

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Section: ) Standard Ieee 123-node Benchmark Systemmentioning

confidence: 99%

Detection of Cyber Attacks on Voltage Regulation in Distribution Systems Using Machine Learning

2021

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“…In Ref. 29 a methodology for improving the condition number for different accuracy levels of measurements is proposed. In Ref.…”

Section: Introductionmentioning

confidence: 99%

Linear tracking sequential hybrid power system state estimator

Devara¹,

Kumari

2021

Int Trans Electr Energ Syst

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“…The refresh rate of PMU measurements is typically 30 times per second, whereas SCADA systems capture one snapshot every 2-6 seconds. Different accuracy level may result in ill-conditioning and convergence problem[42]. Two types of solutions have been proposed in literatures, indirect and direct approaches[42,43].In indirect approaches, the system is assumed to be fully observed by conventional SCADA measurements with which the conventional SE is carried out before the PMU measurements are incorporated.…”

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confidence: 99%

“…Different accuracy level may result in ill-conditioning and convergence problem[42]. Two types of solutions have been proposed in literatures, indirect and direct approaches[42,43].In indirect approaches, the system is assumed to be fully observed by conventional SCADA measurements with which the conventional SE is carried out before the PMU measurements are incorporated. Zhou et al proposed a linear post-processing step to combine PMU measurements with estimation results of the conventional state estimator[35].…”

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confidence: 99%

“…The two-stage method is also used by Asprou et al to track for track the dynamics of the power system states during a fault. The weighted least absolute value (LAV) is adopted to estimate the system states at instants when only PMU measurements are updated[54].Kabiri et al propose a method to decouple the SCADA and PMU measurements and transform the hybrid hybrid SE into two separate problems to circumvent the ill-conditioning caused by disparity of accuracy level of PMU and SCADA measurements[42]. The disadvantage of direct method is that it requires change to the current SCADA based SE software package.…”

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State monitoring of future power distribution grid using micro-PMU and state estimation

Chen¹

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A New Hybrid State Estimation Considering Different Accuracy Levels of PMU and SCADA Measurements

Cited by 47 publications

References 35 publications

Detection of Cyber Attacks on Voltage Regulation in Distribution Systems Using Machine Learning

Detection of Cyber Attacks on Voltage Regulation in Distribution Systems Using Machine Learning

Linear tracking sequential hybrid power system state estimator

State monitoring of future power distribution grid using micro-PMU and state estimation

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