General Considerations

El‐Hawary, Mohamed E.

doi:10.1002/9781119480402.ch1

Cited by 3 publications

(14 citation statements)

References 27 publications

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“…Hence, the smallest PMUs in amount are counted. At the same time, the maximum reliability of monitoring the network buses is fulfilled around the modern grid equipped with PMU devices in a least number and optimally at the same time [2]- [3].…”

Section: Optimal Sensor Arrangement Using a Yalmip Branch-and-bound A...mentioning

confidence: 99%

“…The goal of this paper is to improve the reliability of wide area monitoring by making it possible to do and improve the power system protection, power control schemes by using PMUs [2]- [3].…”

Section: Optimal Sensor Arrangement Using a Yalmip Branch-and-bound A...mentioning

confidence: 99%

“…(1) and lower bound constraint: (2) This optimization procedure of the branching strategy suffices that none of the integer solutions are not being rid of the process. The optimization procedure continues until an integer optimum point has been found.…”

Section: Theory Of Branch-and-bound Algorithmmentioning

confidence: 99%

“…In [23], an optimal PMU formulation is presented based on the maximum observability indicator whereas the optimal solutions are satisfied by the state estimator tool [2]- [3]. A branch-and-bound algorithm completed in two phases is utilized to attack the widely recognized and used integer constraint programming model with binary variables [21]- [22].…”

Section: Introductionmentioning

confidence: 99%

“…Then the objective function is extended with the aim to satisfy two terms, that is, to minimize the PMU cost installation while the reliability is satisfactorily in maximum amount for state estimation purposes [2]- [3]. The optimization terminates within a stopping criterion to find an optimum point.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Calculating Global Minimum Points to Binary Polynomial Optimization Problem: Optimizing the Optimal PMU Localization Problem as a Case-Study

Theodorakatos,

Moschoudis,

Babu

2024

J. Phys.: Conf. Ser.

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State estimation (SE) is an algorithmic function of an energy management system (EMS). SE provides an actual-time monitoring and control of modern electrical power grids. State Estimation can be worked with sufficiency using Phasor Measurement Units optimally placed within a power grid. This paper concerns the implementation of proper algorithms embedded in optimization solvers to the optimal PMU localization problem solving globally. The optimization model is formulated as a 0 - 1 nonlinear minimization problem. The problem is transformed to a polyhedron using linearization methods and B&B tree. In this model, we use a linear cost function under polynomial constraints and binary restrictions on the design variables in a symbolic format. This mathematical model is programmed in the YALMIP environment which is fully compatible with MATLAB. The 0 - 1 Nonlinear Programming (NLP) model is suitable for getting concisely global optimal solutions. The optimal solution is given by a wrapped optimization engine including a local optimizer routine performing together with a mixed-Integer-Linear Programming routine. The solution is achieved within a zero-gap precisely encountered during the iterative process. This tolerance criterion is a necessity for a successful implementation of the B&B tree because it ensures global optimality with an acceptance relative gap. The minimization model is implemented in a YALMIP code fully compatible with MATLAB in two stages. Initially, an objective function with one term is minimized to discover a number of sensors for wide-area monitoring, control and state estimator applications. Then, an extra product is considered in the objective to suffice maximum reliability for observing the network buses. The numerical minimization models are applied to standard power networks in the direction to be solved globally.

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Section: Optimal Sensor Arrangement Using a Yalmip Branch-and-bound A...mentioning

confidence: 99%

Section: Optimal Sensor Arrangement Using a Yalmip Branch-and-bound A...mentioning

confidence: 99%

Section: Theory Of Branch-and-bound Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Calculating Global Minimum Points to Binary Polynomial Optimization Problem: Optimizing the Optimal PMU Localization Problem as a Case-Study

Theodorakatos,

Moschoudis,

Babu

2024

J. Phys.: Conf. Ser.

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Linear Distribution System State Estimation by Hybrid Synchronized/Unsynchronized Measurements

Nassaj,

Jahromi,

et al. 2023

2023 IEEE 13th International Workshop on Applied Measurements for Power Systems (AMPS)

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This paper proposes a linear state estimation method for unbalanced distribution systems using available synchronized/unsynchronized measurements. The paper demonstrates that circuit properties can readily be taken advantage of to linearly express power measurements in terms of bus voltages and line currents. This results in a linear distribution system state estimation (LDSSE) process, which involves two stages. In stage one, the three-phase voltage phase angles are estimated using available measurements and network parameters. By formulating voltage/current phasors based on these phase angles, linear equations are developed that enable the estimation of voltage phasors. The linear nature of the proposed method significantly reduces the computation time while maintaining the solution's accuracy. The superiority of the proposed LDSSE method over existing methods is verified using extensive simulation studies conducted on different test feeders.

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A Review on State Estimation Techniques in Active Distribution Networks: Existing Practices and Their Challenges

et al. 2022

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This paper provides a comprehensive review of distribution system state estimation in terms of basic definition, different methods, and their application. In the last few years, the operation of distribution networks has been influenced by the installation of distributed generations. In order to control and manage an active distribution network’s performance, distribution system state estimation methods are introduced. A transmission system state estimation cannot be used directly in distribution networks since transmission and distribution networks are different due to topology configuration, the number of buses, line parameters, and the number of measurement instruments. So, the proper state estimation algorithms should be proposed according to the main distribution network features. Accuracy, computational efficiency, and practical implications should be considered in the designing of distribution state estimation techniques since technical issues and wrong decisions could emerge in the control center by inaccurate distribution state estimation results. In this study, conventional techniques are reviewed and compared with data-driven methods in order to highlight the pros and cons of different techniques. Furthermore, the integrated distribution state estimation methods are compared with the distributed approaches, and the different criteria, including the level of area overlapping execution time and computing architecture, are elaborated. Moreover, mathematical problem formulation and different measuring methods are discussed.

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General Considerations

Cited by 3 publications

References 27 publications

Calculating Global Minimum Points to Binary Polynomial Optimization Problem: Optimizing the Optimal PMU Localization Problem as a Case-Study

Calculating Global Minimum Points to Binary Polynomial Optimization Problem: Optimizing the Optimal PMU Localization Problem as a Case-Study

Linear Distribution System State Estimation by Hybrid Synchronized/Unsynchronized Measurements

A Review on State Estimation Techniques in Active Distribution Networks: Existing Practices and Their Challenges

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