technologies, improving management measures and optimizing
network structures. But blackout is inherently inevitable because
of unforeseen circumstances, incompleteness of information, treacherous
weather and increasing complication of power systems.
The impact of a blackout increases exponentially with the duration
of restoration, once blackout occurs, it is imperative to take
effective and secure measures to restore the power system as soon
as possible [3–5]. Generally, power system restoration includes
three phases: black-start, network reconfiguration and load
restoration [1]. The objectives of restoration are to take the power
system return to normal securely and rapidly, minimize losses and
restoration duration, and diminish adverse impact on the society
[2]. For network reconfiguration, the purpose is to restore the backbone
network concerned, interconnect relevant subsystems and
finally rebuild a stable skeleton network [6].
Backbone-network reconfiguration can be described as a multistage,
multivariable, multi-objective, combinatorial, nonlinear and
constrained optimization problem. There are no known mathematical
methods for solving such a NP-complete problem exactly
in polynomial time [7]. In order to speed up restoration without
violating security constraints, many methods have been addressed.
Expert system [8] has been employed extensively in making
restoration schemes, it has promising prospects of application.
But the establishment and maintenance of knowledge base is akey problem, especially when the system is becoming larger
technologies, improving management measures and optimizingnetwork structures. But blackout is inherently inevitable becauseof unforeseen circumstances, incompleteness of information, treacherousweather and increasing complication of power systems.The impact of a blackout increases exponentially with the durationof restoration, once blackout occurs, it is imperative to takeeffective and secure measures to restore the power system as soonas possible [3–5]. Generally, power system restoration includesthree phases: black-start, network reconfiguration and loadrestoration [1]. The objectives of restoration are to take the powersystem return to normal securely and rapidly, minimize losses andrestoration duration, and diminish adverse impact on the society[2]. For network reconfiguration, the purpose is to restore the backbonenetwork concerned, interconnect relevant subsystems andfinally rebuild a stable skeleton network [6].Backbone-network reconfiguration can be described as a multistage,multivariable, multi-objective, combinatorial, nonlinear andconstrained optimization problem. There are no known mathematicalmethods for solving such a NP-complete problem exactlyin polynomial time [7]. In order to speed up restoration withoutviolating security constraints, many methods have been addressed.Expert system [8] has been employed extensively in makingrestoration schemes, it has promising prospects of application.But the establishment and maintenance of knowledge base is akey problem, especially when the system is becoming larger
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