Application of domination integrity of graphs in PMU placement in electric power networks

Mariappan, Saravanan; Sujatha, R.; Sundareswaran, R.; Balasubramanian, Muthu Selvan

doi:10.3906/elk-1711-242

Cited by 6 publications

(4 citation statements)

References 8 publications

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“…In this case, once the electrical power is available near to your city or town, then the electrical voltage is decrease or stepped-down in a utility-based substation to a very low distribution voltage near around your city or town. As such an electrical power of the system reaches close to the user home, it is further stepped-down to the voltage to be used in the house with the help of another transformer [1] [10]. This amount of power generally enters the home through the user-based electrical meter.…”

Section: Figure 1: Smart Grid [18]mentioning

confidence: 99%

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Parameter Estimation of Smart Grid using PMU with Kalman Filter and Bayesian Prediction

Sarker¹,

Mohan²,

Prakash³

2019

IJITEE

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Load flow is the main issue which occurs in power grid systems. To improve the performance, reduce the cost and enhance the reliability in power systems, smart grids have been proposed. In electricity distribution system, smart devices like smart meters are used for effective performance. The real concern in these devices is to protect the data from unauthorized parties and noise occurring in data. Smart device reader acts as the bridge which connects the smart grid devices with smart grid clouds. In many of the instances of circuit-based analysis, the network parts are restricted to the regarded value of impedances with voltage and current resource. But the issue of load flow is usually diverse in the sense that rather of impedances, the known amounts are active and reactive powers in most of the network buses, since the performance of most of the load in a great deal of instances are as continuous power loads, presuming that voltages used on them stay within suitable ranges. There are various methods which are used to solve these problems. Kalman filters are proposed to achieve the optimal performance on the smart grid devices. This filter identifies the device failures, unusual disturbance, and malicious data attacks. Kalman Filter is a dynamic state estimation method which is mainly used in this paper for noise variation estimation. The use of dynamic state estimation methods such as the Kalman filter provides an optimal solution to the process of real-time data prediction and reduces the problem based on non-linearity. The analysis of real-time data depends on Phasor Measuring Units (PMU) which plays a significant role in power transmission and distribution processes due to their ability to monitor the power flow within a network. The process of PMU-based monitoring improves the quality of the smart grid. Simultaneously, the implementation of PMU increases the dynamics of noise variance which further inflates the uncertainty in noise-based distribution. This paper presents a method to reduce the amount of uncertainty in noise by using a linear quadratic estimation method (LQE), usually known as Kalman filter along with Taylor expansion series but this process is time-consuming and is vulnerable to a large number of errors at the time of testing. The main reason behind this approach is the high complexity of the system which makes it very hard to derive the process. The proposed studies adopts a technique to work on covariance earlier based estimation using Bayesian method together with the estimation of dynamic polynomial prior by using Particle Swarm Optimization (PSO). The experimental evaluation compares the outcomes received from the primary Kalman filter, PSO optimized Kalman filter out and Kalman filter Covariance Bayesian method. Finally, the effects received from the analysis highlights the truth that the PSO optimized Kalman clear out to be more effective than the Kalman filter out with Covariance Bayesian approach

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Section: Figure 1: Smart Grid [18]mentioning

confidence: 99%

“…Mariappan Saravanan, et al [1] proposed the application of power domination integrity to an electric network of power system. A phasor measurement unit was used for analysing and controlling the energy system by measurement of voltage phase in transmission lines and electrical nodes.…”

Section: Related Workmentioning

confidence: 99%

Parameter Estimation of Smart Grid using PMU with Kalman Filter and Bayesian Prediction

Sarker¹,

Mohan²,

Prakash³

2019

IJITEE

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“…For some investigations of the cost effective concept, we refer the readers to see [6,9,11]. For some practical application of distance concept, we refer the readers to [1,4,5,10,12].…”

Section: Introductionmentioning

confidence: 99%

Distance k-Cost Effective Sets in the Corona and Lexicographic Product of Graphs

Caadan¹,

Paluga²,

Aniversario³

2023

Eur. J. Pure Appl. Math.

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Let G be a connected graph and k ≥ 1 be an integer. The open k-neighborhood Nk G(v) of v ∈ V (G) is the set Nk G(v) = {u ∈ V (G) \ {v}: dG(u, v) ≤ k}. A set S of vertices of G is called distance k-cost effective of G if for every vertex u in S, |Nk G(u) ∩ (V (G) \ S)| − |Nk G(u) ∩ S| ≥ 0. The maximum cardinality of a distance k-cost effective set of G is called the upper distance k-cost effective number of G. In this paper, we characterized the distance k-cost effective sets in the corona and lexicographic product of two graphs. Consequently, the bounds or the exact values of the upper distance k-cost effective numbers of these graphs are obtained.

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“…Peng et al combined non-dominated sorting with differential evolution [37]. Recently, Saravanan et al used the concept of domination integrity [38]. It is inferred that, focusing on the nondominating set, the authors arrived at a global optimal solution.…”

Section: Introductionmentioning

confidence: 99%

Optimal PMU Placement Technique to Maximize Measurement Redundancy Based on Closed Neighbourhood Search

Hyacinth¹,

Venugopal

2021

Energies

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This paper proposes a method for the optimal placement of phasor measurement units (PMUs) for the complete observability of a power system based on the degree of the neighbourhood vertices. A three-stage algorithm is used to determine the minimum number of PMUs needed to make the system observable. The key objective of the proposed methodology is to minimize the total number of PMUs to completely observe a power system network and thereby minimize the installation cost. In addition, the proposed technique also focuses on improving the measurement redundancy. The proposed method is applied on standard IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 57-bus and IEEE 118-bus test systems and a hybrid AC/DC microgrid test system. The results obtained are compared with already existing methods in terms of the Bus Observability Index (BOI) and System Observability Redundancy Index (SORI). The results show that the proposed method is simple to implement and provides better placement locations for effective monitoring compared to other existing methods.

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Application of domination integrity of graphs in PMU placement in electric power networks

Cited by 6 publications

References 8 publications

Parameter Estimation of Smart Grid using PMU with Kalman Filter and Bayesian Prediction

Parameter Estimation of Smart Grid using PMU with Kalman Filter and Bayesian Prediction

Distance k-Cost Effective Sets in the Corona and Lexicographic Product of Graphs

Optimal PMU Placement Technique to Maximize Measurement Redundancy Based on Closed Neighbourhood Search

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