Determination of static voltage stability-margin of the power system prior to voltage collapse

Jalboub, M. K.; Ihbal, A. M.; Rajamtani, H.; Abd-Alhameed, R. A.

doi:10.1109/ssd.2011.5981420

Cited by 7 publications

(4 citation statements)

References 12 publications

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“…The stability of a network can be evaluated by line voltage stability indices. Figure 2 shows the two-bus representation that is used to formulate all line voltage stability indices (VSIs) (Jalboub et al, 2011). The shunt admittance for these representations is ignored since all network lines are simulated for 1 KM in length.…”

Section: Line Voltage Stability Indicesmentioning

confidence: 99%

Investigation of Optimal PV Allocation to Minimize System Losses and Improve Voltage Stability for Distribution and Transmission Networks Using MATLAB and DigSilent

Rasheed

Verayiah

2021

Front. Energy Res.

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Electricity generation from renewable energy sources such as solar energy is an emerging sustainable solution. In the last decade, this sustainable source was not only being used as a source of power generation but also as distributed generation (DG). Many literatures have been published in this field with the objective to minimize losses by optimizing the DG size and location. System losses and voltage profile go hand-in-hand; as a result, when system losses are minimized, eventually the voltage profile improves. With improvement in inverter technologies, PV-DG units do not have to operate at a unity power factor. The majority of proposed algorithms and methods do not consider power factor optimization as a necessary optimization. This article aims to optimize the size, location, and power factor of PV-DG units. The simulations are performed on the IEEE 33 bus radial distribution network and IEEE 14 bus transmission network. The methodologies developed in this article are divided into two sections. The first section aims to optimize the PV-DG size and location. A multi-objective function is developed by using system losses and a voltage deviation index. Genetic algorithm (GA) is used to optimize the multi-objective function. Next, analytical processes are developed for verification. The second section aims to further enhance PV-DG by optimizing the power factor of PV-DG. The simulation is performed for static load in both systems, which are the IEEE 33 bus radial distribution network and IEEE 14 bus transmission network. A mathematical analytical method was developed, and it was found to be sufficient to optimize the power factor of the PV-DG unit. The results obtained show that voltage stability indices help minimize the computation time by determining the optimal locations for DG placement in both networks. In addition, the GA method attained faster convergence than the analytical method and hence is the best optimal sizing for both test systems with minimum computation time. Additionally, the optimization of the power factor for both test systems has demonstrated further improvement in the voltage profile and loss minimization. In conclusion, the proposed methodology has shown promising results for both transmission and distribution networks.

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Section: Line Voltage Stability Indicesmentioning

confidence: 99%

Investigation of Optimal PV Allocation to Minimize System Losses and Improve Voltage Stability for Distribution and Transmission Networks Using MATLAB and DigSilent

Rasheed

Verayiah

2021

Front. Energy Res.

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“…There are works on voltage stability indices with PMU measurements, some intended for real-time applications, [35, 36, 37]. Some indexes are not suitable to any power system topology and are only accurate for radial networks [38, 39] and exhibit large deviations or require complex computational processes when the system is meshed.…”

Section: Introductionmentioning

confidence: 99%

Radial basis function for fast voltage stability assessment using Phasor Measurement Units

González

Isaac

López

et al. 2019

Heliyon

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A simple method, based on Machine Learning Radial Basis Functions, RBF, is developed for estimating voltage stability margins in power systems. A reduced set of magnitude and angles of bus voltage phasors is used as input. Observability optimization technique for locating Phasor Measurement Units, PMUs, is applied. A RBF is designed and used for fast calculation of voltage stability margins for online applications with PMUs. The method allows estimating active local and global power margins in normal operation and under contingencies. Optimized placement of PMUs leads to a minimum number of these devices to estimate the margins, but is shown that it is not a matter of PMUs quantity but of PMUs location for decreasing training time or having success in estimation convergence. Compared with previous work, the most significant enhancement is that our RBF learns from PMU data. To test the proposed method, validations in the IEEE 14-bus system and in a real electrical network are done.

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“…At the same time, because of the increase in electronic charges, the quality of power supply has become a critical issue [4]. In view of all these things, there is now an increasing trend to switch from a centralized power grid system to a local energy grid with a control capability called micro grid in the event of an emergency or power shortage in the main grid [5].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Cyber Attacks on Load Frequency Control in Smart Grid

Hossain

Khan

2019

Journal of Future Internet

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Smart Grid has gained tremendous technology momentum over the past few years. The data and cyber security of the smart grid face severe challenges and has gained significant importance. This paper addresses the reliability of smart grid by examining their own importance and the effect of cyber-attack during sudden load changes in frequency disturbing aspects. Moreover, it also introduces a solution approach for stabilizing the system. Using the continuous power flow approach with static var compensator (SVC) and static synchronous compensator (STATCOM), maximum load ability of the load buses is determined. The stable limit of speed control for load frequency control (LFC) and integral controller gain for automatic generation control (AGC) is extracted from their characteristic equations to evaluate the effect of cyberattack on power systems. Simulations are conducted to demonstrate the frequency variations and oscillations of the power system, depending on the nature of cyber-attack (positive biased or negative biased attack). Finally, to eliminate these oscillations, a feedback LFC block with a three-input shift is proposed.Contribution/Originality: Cybersecurity of the modern power system is becoming a major concern throughout the design and implementation of smart grid applications and technology. Therefore, it is essential to study the impact of cyber attacks on the power system. This paper discusses cyberattacks that induce positive and negative biased attacks and their impact on transient stability. Cyber attacks are launched on measured data for a FACTS device (static var compensator -SVC). Therefore, a new procedure of analyzing power system frequency stability under cyber-attack by static var compensator (SVC) and static synchronous compensator (STATCOM).

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Determination of static voltage stability-margin of the power system prior to voltage collapse

Cited by 7 publications

References 12 publications

Investigation of Optimal PV Allocation to Minimize System Losses and Improve Voltage Stability for Distribution and Transmission Networks Using MATLAB and DigSilent

Investigation of Optimal PV Allocation to Minimize System Losses and Improve Voltage Stability for Distribution and Transmission Networks Using MATLAB and DigSilent

Radial basis function for fast voltage stability assessment using Phasor Measurement Units

Analysis of Cyber Attacks on Load Frequency Control in Smart Grid

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