Statistical method to determine operating rules in the event of generator dropout on EDF French Guyana Grid

Martigne, H.; Cholley, P.; King, David L.; Christon, J.

doi:10.1109/ptc.2001.964599

Cited by 5 publications

(5 citation statements)

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“…A wide range of data mining applications to power systems have been proposed in the literature [5,[25][26][27][28][29][30][31][32][33][34].…”

Section: Chapter 2 Literature Reviewmentioning

confidence: 99%

“…The systematic load scaling procedure used to generate diverse operating points may also be improved by implementing an economic dispatch algorithm. Due to the intrinsic characteristics of load flow analysis, it is implicitly assumed that the variations in load are matched by rescheduling the amount of imported generation 31 . Due to the manner in which the load variations were formulated, an inertial re-dispatch, where all machines in the system increase their generation proportionally to their inertia, does not effectively represent the system behavior.…”

Section: Future Researchmentioning

confidence: 99%

“…If corrective actions had been taken during the eight seconds that 31 The model used in this dissertation has two equivalent swing generators that represent the interaction between California and the rest of the world. Both swing generators "pick up" the changes in load.…”

Section: Coordination Of Transmission Of Electricity (Ucte Now Callementioning

confidence: 99%

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Methodology for a Security/Dependability Adaptive Protection Scheme Based on Data Mining

Bernabeu

Thorp

Centeno

2012

IEEE Trans. Power Delivery

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The power industry is currently in the process of re-inventing itself. The unbundling of the traditional monopolistic structure that gave birth to a deregulated electricity market, the mass tendency towards a greener use of energy, the new emphasis on distributed generation and alternative renewable resources, and new emerging technologies have revolutionized the century old industry.Recent blackouts offer testimonies of the crucial role played by protection relays in a reliable power system. It is argued that embracing the paradigm shift of adaptive protection is a fundamental step towards a reliable power grid. The adaptive philosophy of protection systems acknowledges that relays may change their characteristics in order to tailor their operation to prevailing system conditions. The purpose of this dissertation is to present methodology to implement a security/dependability adaptive protection scheme. It is argued that the likelihood of hidden failures and potential cascading events can be significantly reduced by adjusting the security/dependability balance of protection systems to better suit prevailing system conditions.

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“…A wide range of data mining applications to power systems have been proposed in the literature [5,[25][26][27][28][29][30][31][32][33][34].…”

Section: Chapter 2 Literature Reviewmentioning

confidence: 99%

Section: Future Researchmentioning

confidence: 99%

See 1 more Smart Citation

Methodology for a Security/Dependability Adaptive Protection Scheme Based on Data Mining

Bernabeu

Thorp

Centeno

2012

IEEE Trans. Power Delivery

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“…French transmission operator RTE has been using decision tree based security assessment methods to define operational security rules, especially regarding voltage collapse prevention Schlumberger et al 1999Schlumberger et al , 2002Pierre et al 1999;Martigne et al 2001;Paul and Bell 2004;Henry et al 1999Henry et al , 2004aHenry et al , 2006Cholley et al 1998). They provide operators a better knowledge of the distance from instability for a post-contingency scenario in terms of pre-contingency conditions, and thus save a great amount of money by preserving the reliability while enabling more informed operational control closer to the stability limits.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Power System Security Assessment Through Intelligent Decision Trees

Krishnan

2014

Complex System Modelling and Control Through Intelligent Soft Computations

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Power system security assessment involves ascertaining the post-contingency security status based on the pre-contingency operating conditions. A system operator accomplishes this by the knowledge of critical system attributes which are closely tied to the system security limits. For instance, voltage levels, reactive power reserves, reactive power flows are some of the attributes that drive the voltage stability phenomena, and hence provide easy guidelines for the operators to monitor and maneuver the highly stressed power system to a secure state. With tremendous advancements in computational power and machine learning techniques, there is increased ability to produce security guidelines that are highly accurate and robust under a wide variety of system conditions. Particularly, the decision trees, a data mining tool, has lend itself well in extracting highly useful and succinct knowledge from a very large repository of historical information. The most vital and sensitive part of such a decision tree based security assessment is the stage of training database generation, a computationally intensive process which involves sampling many system operating conditions and performing power system contingency assessment simulations on them. The classification performance of operating guidelines under realistic testing scenarios depend heavily on the quality of the training database used to generate the decision trees. So the primary objective of this chapter is to develop an improvised database generation process that creates a satisfactory training database by sampling the most influential operating conditions from the input operating parameter state space prior to the stage of power system contingency simulation. Embedding such intelligence to the system scenario sampling process enhances the information content in the training database, while minimizing the computing requirements to generate it. This chapter will clearly explain and demonstrate the process of identifying such high information contained sampling space and the advantage of deriving security guidelines from decision trees that exclusively use such an enhanced training database.

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“…Many utilities have taken and are continuing to take a serious interest in implementing learning algorithm such as decision tree in their decision making environment. French transmission operator RTE has been using decision tree based security assessment methods to define operational security rules, especially regarding voltage collapse prevention [34,35,36,37,38,39,40,41,42,43,44]. They provide operators a better knowledge of the distance from instability for a post-contingency scenario in terms of pre-contingency system conditions, and they save a great amount of money while preserving the reliability of the system by enabling more informed control of the operation nearer to the stability limits.…”

Section: Decision Tree Based Inductive Learningmentioning

confidence: 99%

Efficient processing of system scenarios in statistical and machine learning studies for power system operational and investment planning

Krishnan¹

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Statistical method to determine operating rules in the event of generator dropout on EDF French Guyana Grid

Cited by 5 publications

References 1 publication

Methodology for a Security/Dependability Adaptive Protection Scheme Based on Data Mining

Methodology for a Security/Dependability Adaptive Protection Scheme Based on Data Mining

Enhanced Power System Security Assessment Through Intelligent Decision Trees

Efficient processing of system scenarios in statistical and machine learning studies for power system operational and investment planning

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