An Intelligent Load Flow Engine for Power System Planning

Fujiwara, Ryoichi; Sakaguchi, Toshiaki; Kohno, Y.; Suzuki, Hiroshi

doi:10.1109/tpwrs.1986.4334998

Cited by 42 publications

(4 citation statements)

References 12 publications

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“…In load-flow planning, the planning engineers execute the load-flow program repeatedly by changing the input data until satisfactory operation condition is achieved. To automate the plan-ning process, Fujiwara et al (1985) built a ruled-based expert system acting as an intelligent load flow engine on a scientific personal workstation, Apollo DN420. The workstation is interfaced with a mainframe computer in which power system data and power system analysis programes are held.…”

Section: Loadflow Planningmentioning

confidence: 99%

Applications of artificial intelligence and expert systems in power engineering

Wong

1990

The Knowledge Engineering Review

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The theme of this paper is to review work carried out in the area of applying expert systems and artificial intelligence in electrical power engineering. It surveys expert systems and artificial-intelligence-based algorithms developed for solving decision problems in power network and generator fault diagnosis, reactive power and voltage control, restoration of power supply, determination of load circuits for shedding in under-frequency load shedding schemes, generator scheduling, allocation of loads and circuits, load-flow planning, generation expansion planning and distribution expansion planning.

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Section: Loadflow Planningmentioning

confidence: 99%

Applications of artificial intelligence and expert systems in power engineering

Wong

1990

The Knowledge Engineering Review

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“…Thus, in reference [10] a rule-based expert system is proposed for making a contingency ranking from the current state of the system. Its drawbacks are the difficulty of looking for a sufficiently expert operator for describing each system; difficulty in generating a sufficiently precise rule set; and non-portability to other systems.…”

Section: Introductionmentioning

confidence: 99%

Contingency evaluation and monitorization using artificial neural networks

Joya

Garcìa-Lagos

Hernández

2009

Neural Comput & Applic

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In this paper, different neural network-based solutions to the contingency analysis problem are presented. Contingency analysis is examined from two perspectives: as a functional approximation problem obtaining a numerical evaluation and ranking contingencies; and as a graphical monitoring problem, obtaining an easy visualization system of the relative severity of the contingencies. For the functional evaluation problem, we analyze the use of different supervised feed-forward artificial neural networks (multilayer perceptron and radial basis function networks). The proposed systems produce a very accurate evaluation and ranking, and so present a high applicability. For the graphical monitoring problem, unsupervised artificial neural networks such as self-organizing maps by Kohonen have been used. This solution allows both a rapid, easy and simultaneous visualization of the severity level of the complete contingency set. The proposed solutions avoid the main drawbacks of previous neural network approaches to this problem, which are explicitly analyzed here.

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“…, operators a s s i s t a n c e [ 4 ] , and operation planning [5]. Some o p e r a t i o n p l a n n i n g a r e reported.…”

mentioning

confidence: 99%

“…F i n a l l y t h e f u t u r e aspects a r e discussed. (1) ADAPOS [5,12] ADAPOS (ADvanced Analyzer of P o w e r S y s t e m ) i s a n i n t e g r a t e d . a n a l y s i s programs f o r power s y s t e m a n a l y s i s and p l a n n i n g .…”

mentioning

confidence: 99%

Expert system applications to power systems operation

Kono

Suzuki

Matsumoto³

Proceedings. 5th IEEE International Symposium on Intelligent Control 1990

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W s t r a c t -This paper discusses t h e key i s s u e s t o develop t h e expert systems f o r power system operation. I t i s based on t h e experience gained during t h e p r a c t i c a l development of t h e expert systems f o r t h e system r e s t o r a t i o n and t h e operation planning. F i r s t , t h e state of t h e a r t of a p p l i c a t i o n s of e x p e r t system i n Japan i s b r i e f l y reviewed. Then t h e experiences of t h e development f o r t h e r e s t o r a t i o n system and t h e o p e r a t i o n p l a n n i n g s y s t e m a r e p r e s e n t e d . R e c o g n i z e d key i s s u e s t o d e v e l o p t h e s e knowledge b a s e s y s t e m s a r e knowledge a c q u i s i t i o n , e v a l u a t i o n of t h e system, man-machine . i n t e r f a c e , a n d i n t e g r a t i o n w i t h e x i s t i n g environment such a s t h e SCADA system and/or conventional a n a l y t i c a l programs.

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An Intelligent Load Flow Engine for Power System Planning

Cited by 42 publications

References 12 publications

Applications of artificial intelligence and expert systems in power engineering

Applications of artificial intelligence and expert systems in power engineering

Contingency evaluation and monitorization using artificial neural networks

Expert system applications to power systems operation

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