New types of FACTS-devices for power system security and efficiency

Rehtanz, Christian; Zhang, Justin-Jin

doi:10.1109/pct.2007.4538332

Cited by 12 publications

(6 citation statements)

References 4 publications

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“…Step 8: Each hidden unit (zj) sums its delta inputs from units in the layer above δ -inj = Σ δj w jk (6) The error information term is calculated as δ j =δ -inj f(zinj ) (7)…”

Section: Back Propagation Of Errorsmentioning

confidence: 99%

Dynamic Stability Enhancement of Power Transmission System Using Artificial Neural Network Controlled Static Var Compensator

Garg¹,

Agarwal²

2012

IJCA

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Voltage level of the system changes at the time of fault and the drop in the load voltage leads to an increased demand for the reactive power that, if not met by the power system leads to a further decline in the bus voltage. This decline eventually leads to a progressive rapid decline of voltage at that location, which may have a cascading effect on neighboring regions that causes voltage collapse.In this paper, In order to maintain system stability after faults, the transmission line is shunt compensated at its center by a 200-Mvar Static Var Compenstor (SVC) in Matlab/Simulink. SVC are used to maintain the voltage with in the limits. SVC will either supply the reactive power or extract the reactive power. An Artificial Neural Network (ANN) is also developed with a systematic step-by-step procedure which optimizes a criterion commonly known as the learning rule. The input/output training data is fundamental for these networks as it conveys the information which is necessary to discover the optimal operating point. It is shown that trained Neural Network developed has excellent capabilities of forecasting which can be very useful in research.

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“…Step 8: Each hidden unit (zj) sums its delta inputs from units in the layer above δ -inj = Σ δj w jk (6) The error information term is calculated as δ j =δ -inj f(zinj ) (7)…”

Section: Back Propagation Of Errorsmentioning

confidence: 99%

Dynamic Stability Enhancement of Power Transmission System Using Artificial Neural Network Controlled Static Var Compensator

Garg¹,

Agarwal²

2012

IJCA

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“…Dynamic voltage support and reactive power compensation were identified as a very significant measure for improving the transient stability of the system. Flexible AC Transmission Systems (FACTS) devices with an appropriate control strategy have the potential to increase the system stability margin [2][3][4][5][6]. Shunt FACTS devices play an important role in th e power network's reactive power flow.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy controlled SVC for power system damping

Kamis

Ghani

Kamaruddin

et al. 2020

IJEECS

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<p>This paper presents the ability of the fuzzy logic-based stabilizer used to generate the supplementary voltage control signal of the SVC to improve the damping of the inter-area mode oscillation in the power system. The base system is symmetrical, consisting of two identical areas connected by a relatively weak tie line. The SVC is chosen to be installed at the tie line midpoint. The active power of the local line will be used as an input signal for the stabilizer. The additional signal is calculated using fuzzy membership function to determine the quantity of reactive power supplied absorbed by SVC. The system oscillation is indicated by a 3-phase-to-ground short circuit occurring at 0.2s of the simulation and subsequently clearing after 100ms. Simulation with the sample power system shows that when subjected to a disturbance, fuzzy logic-based SVC stabilizer provides good damping in inter-area mode oscillation for the system. The effectiveness of the stabilizer applied with and without PSS will also be investigated.</p>

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“…Traditionally, these problems have been solved by building new power plants and transmission lines. However, this solution is costly to implement, involves long construction times, and faces many obstacles [1].…”

Section: Introductionmentioning

confidence: 99%