2020
DOI: 10.22266/ijies2020.0430.06
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Emergency Load Shedding for Voltage Stability Enhancement: With Particular Reference to the Iraqi National Power Grid

Abstract: In the present days, power systems are operated favourably close to their stability limit. System stability can be safeguarded by employing an emergency control technique, known as load shedding; this technique is affected by shedding some loads. Such a technique implemented only when the voltage or frequency deterioration below a specific voltage or frequency threshold. In this work, an advanced emergency load shedding model is forwarded based on the voltage stability indicator aimed at enhancing voltage. Thi… Show more

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Cited by 4 publications
(4 citation statements)
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“…From Table 2 it is clear that by removing 141.77 MW with proposed method will enhance the frequency to above the critical level which is less than the curtailed power by the conventional UFLS. By using of voltage recovery concept [20] which calculate the percentage enhancement of the system voltages we find that voltage recovery of the network Vrec=2.9556% and the Figure 5 shows the bus voltage levels before and after load shedding and it's clear that there is no violation in voltage level in this case and show the enhancement of bus voltage level after load shedding. the system shows that bus voltages of buses 23, 24, 25, and 30 under the critical voltage (0.95) as it clear in Figure 6 and after load shedding of 14.5241 MW from load buses we can see the enhancement of voltage level at these buses which can be sense by compute the voltage recovery of the network Vrec=1.3868% and Table 3 shows a comparison with the results of applying genetic algorithm to enhance voltage stability of the same system (IEEE 30) under the same contingency [25].…”
Section: P Ls Min = 141775 Mwmentioning
confidence: 88%
“…From Table 2 it is clear that by removing 141.77 MW with proposed method will enhance the frequency to above the critical level which is less than the curtailed power by the conventional UFLS. By using of voltage recovery concept [20] which calculate the percentage enhancement of the system voltages we find that voltage recovery of the network Vrec=2.9556% and the Figure 5 shows the bus voltage levels before and after load shedding and it's clear that there is no violation in voltage level in this case and show the enhancement of bus voltage level after load shedding. the system shows that bus voltages of buses 23, 24, 25, and 30 under the critical voltage (0.95) as it clear in Figure 6 and after load shedding of 14.5241 MW from load buses we can see the enhancement of voltage level at these buses which can be sense by compute the voltage recovery of the network Vrec=1.3868% and Table 3 shows a comparison with the results of applying genetic algorithm to enhance voltage stability of the same system (IEEE 30) under the same contingency [25].…”
Section: P Ls Min = 141775 Mwmentioning
confidence: 88%
“…The voltage enhancement may have happened in some buses but not others, or it may have worsened in some buses. It is challenging to deal with a large number of voltages in buses to determine the presence of an improved voltage level in the whole for controlling all voltages of buses is as follows [1]:…”
Section: Concept Of Voltage Recoverymentioning
confidence: 99%
“…Evidence has shown that the instability of the voltage could contribute to substantial system failures caused by the inequity between the production of power and the load required within the power system. Therefore, load-shedding strategies are employed as a final resort to prevent the power grid from collapsing under major failures [1].…”
Section: Introductionmentioning
confidence: 99%
“…The optimization-based approach models ELS as an optimization problem with nonlinear constraints or objectives. As to constraints, voltage/frequency deviation security is always considered a nonlinear constraint, which can lead to transient angle stability constraints (Xu et al, 2017), multi-operation modes constraints (Xu et al, 2019), voltage stability constraints (Al-Rubayi and Abd, 2020), stochastic correlation constraints (Jiang et al, 2019), etc. Some methods are used to enhance optimization efficiency, such as the constraint relaxation method (Li et al, 2017) and the parallel methods (Jiang, Wang and Geng, 2014;Gan et al, 2018).…”
Section: Introductionmentioning
confidence: 99%