Event stream processing for improved situational awareness in the smart grid

Dahal, Nischal; Abuomar, O.; King, Robert; Madani, Vahid

doi:10.1016/j.eswa.2015.05.003

Cited by 36 publications

(19 citation statements)

References 25 publications

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“…Conventional supervisory control and data acquisition (SCADA) systems do not provide the ability to monitor transient events [7,8]. Even though the connected remote terminal units (RTU) can communicate cyclically, the measurements samples are typically not time aligned when arriving at the control center [9,10].…”

Section: Application Of Synchrophasors In Modern Control Centersmentioning

confidence: 99%

A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems

et al. 2020

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Synchrophasor based applications become more and more popular in today’s control centers to monitor and control transient system events. This can ensure secure system operation when dealing with bidirectional power flows, diminishing reserves and an increased number of active grid components. Today’s synchrophasor applications provide a lot of additional information about the dynamic system behavior but without significant improvement of the system operation due to the lack of interpretable and condensed results as well as missing integration into existing decision-making processes. This study presents a holistic framework for novel machine learning based applications analyzing both historical as well as online synchrophasor data streams. Different methods from dimension reduction, anomaly detection as well as time series classification are used to automatically detect disturbances combined with a web-based online visualization tool. This enables automated decision-making processes in control centers to mitigate critical system states and to ensure secure system operations (e.g., by activating curate actions). Measurement and simulation-based results are presented to evaluate the proposed synchrophasor application modules for different use cases at the transmission and distribution level.

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Section: Application Of Synchrophasors In Modern Control Centersmentioning

confidence: 99%

A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems

et al. 2020

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“…Responds to prevent further Self healing. Automatically detects and responds to problems-focus on damage-focus is on protecting assets following fault prevention, minimizing impact to consumer (Dahal et al, 2015)…”

Section: Smart Grid Featuresmentioning

confidence: 99%

A Review on Smart Energy Grid Technology: Features and Specifications

Mahmoud¹,

Tang²,

Maseleno³

et al. 2019

J. Eng. Appl. Sci.

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Although, it is widely recognized that smart grid technology is a necessity to reduce the impact of global warming while encouraging efficiency, reliability and effective governance in the supply of electrical energy, the understanding of smart grid technology among researchers is limited. To provide a clear insight to this problem and support researchers, we need a background understanding of various aspects related to smart grid. Current electricity transmission and distribution networks can be categorized as conventional electricity networks because they have not been able to provide excellent service and present real-time data. This network has not been able to provide reliability, safety and efficiency in supplying electrical energy even not yet have the flexibility to be integrated with the generation of renewable energy or microgrid. In this study, a comprehensive review is conducted to map the literature studies to a coherent taxonomy. These include the features and specifications of smart grid. The fundamentals of smart grid presented in this study can benefit readers who wish to embark in smart grid research and applications development.

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“…Gaber et al (2005) provide a good overview of these techniques. An application of data stream mining in smart grids can be found in Dahal et al (2015). Online KDO has received renewed attention recently.…”

Section: Knowledge-driven Optimization (Kdo)mentioning

confidence: 99%

Data mining methods for knowledge discovery in multi-objective optimization: Part A - Survey

Bandaru

Deb

2017

Expert Systems with Applications

152

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Real-world optimization problems typically involve multiple objectives to be optimized simultaneously under multiple constraints and with respect to several variables. While multi-objective optimization itself can be a challenging task, equally difficult is the ability to make sense of the obtained solutions. In this two-part paper, we deal with data mining methods that can be applied to extract knowledge about multi-objective optimization problems from the solutions generated during optimization. This knowledge is expected to provide deeper insights about the problem to the decision maker, in addition to assisting the optimization process in future design iterations through an expert system. The current paper surveys several existing data mining methods and classifies them by methodology and type of knowledge discovered. Most of these methods come from the domain of exploratory data analysis and can be applied to any multivariate data. We specifically look at methods that can generate explicit knowledge in a machine-usable form. A framework for knowledge-driven optimization is proposed, which involves both online and offline elements of knowledge discovery. One of the conclusions of this survey is that while there are a number of data mining methods that can deal with data involving continuous variables, only a few ad hoc methods exist that can provide explicit knowledge when the variables involved are of a discrete nature. Part B of this paper proposes new techniques that can be used with such datasets and applies them to discrete variable multi-objective problems related to production systems.

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Event stream processing for improved situational awareness in the smart grid

Cited by 36 publications

References 25 publications

A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems

A Novel Framework for Synchrophasor Based Online Recognition and Efficient Post-Mortem Analysis of Disturbances in Power Systems

A Review on Smart Energy Grid Technology: Features and Specifications

Data mining methods for knowledge discovery in multi-objective optimization: Part A - Survey

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