• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.12
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• pp.645-654
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• 2004

The design of a measurement system to perform Harmonic State Estimation(HSE) is a very complex problem. In particular, the number of available harmonic analysis measurement instruments is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents an optimal algorithm of HSE which is based on an optimal placement of measurement points using Immune Algorithm (IAs). This IA-HSE has been applied to power system for the validation of an optimal algorithm of HSE. The study results have indicated an economical and effective method for optimal placement of measurement points using Immune Algorithm (IAs) in the HSE.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.175-184
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• 2009

In this paper, a method for optimal measurement placement in the problem of static harmonic state estimation in power systems is proposed. At first, for achieving to a suitable method by considering the precision factor of the estimation, a procedure based on Genetic Algorithm (GA) for optimal placement is suggested. Optimal placement by regarding the precision factor has an evident solution, and the proposed method is successful in achieving the mentioned solution. But, the previous applied method, which is called the Sequential Elimination (SE) algorithm, can not achieve to the evident solution of the mentioned problem. Finally, considering both precision and economic factors together in solving the optimal placement problem, a practical method based on GA is proposed. The simulation results are shown an improvement in the precision of the estimation by using the proposed method.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.342-344
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• 2002

This paper presents a new strategy to find starting points for placing optimally Phasor Measurement Units(PMUs). The performance of the starting point, initial placement set of PMUs, affect critically the computational burden and/or time, because the Optimal PMU Placement (OPP) problem is formulated the combinatorial optimization. By analyzing the properties of OPP solutions on IEEE sample systems in detail, a new strategy for initial PMU placement, in this paper, is proposed. To verify the performance of the suggested strategy, the comparison with the existing strategy and the new one, on IEEE sample systems. is performed. By using the new strategy, the numbers of search spaces to solve the OPP problem is drastically decreased.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.8
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• pp.471-480
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• 2003

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. Among the reasons for its complexity are the system size, conflicting requirements of estimator accuracy, reliability in the presence of transducer noise and data communication failures, adaptability to change in the network topology and cost minimization. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs) which is widely used in areas such as: optimization of the objective function, learning of neural networks, tuning of fuzzy membership functions, machine learning, system identification and control. This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Genetic Algorithms (GAs) in the Harmonic State Estimation (HSE).

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.298-300
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• 2002

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. In particular, the number of available harmonic instruments(Continuous Harmonic Analysis in Real Time : CHART) is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs). This HSE has been applied to the New Zealand AC Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using GAs in the HSE.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1195-1198
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• 1999

This paper presents optimal placement of minimal set of phasor measurement units(PMU's) and observability of measurement system with PMU. By using the incidence matrix symbolic method which directly assigns measurement and pseudo-measurement to incidence matrix, it is much simpler and easier to analyze observability. The optimal PMU set is found through the simulated-annealing(SA) and the direct combinational method. The cooling schedule parameter which is suitable to the property of problem to solve is specified and optimal placement is proven by presented direct combinational method. Search spaces are limited within reasonable feasible solution region to reduce a unnecessary one in the SA implementation based on global search. The proposed method presents to save CPU time and estimate state vectors based on optimal PMU set.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.529-530
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• 2007

The design of a measurement system to perform Harmonic State Estimation(HSE) is a very complex problem. In particular, the number of available harmonic analysis measurement instruments is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents an optimal algorithm of HSE which is based on an optimal placement of measurement points using PSO. This PSO-HSE has been applied to power system for the validation of an optimal algorithm of HSE. The study results have indicated an economical and effective method for optimal placement of measurement points using PSO in the HSE.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.18-29
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• 2015

State Estimation (SE) is the basis of a variety of advanced applications used in most modern power systems. An SE problem formed with enough phasor measurement units (PMUs) data is simply a linear weighted least squares problem requiring no iterations. Thus, designing a minimum-cost placement of PMUs that guarantees observability of a power system becomes a worthy challenge. This paper proposes an equivalent integer linear programming method for substation-oriented optimal PMU placement (SOOPP). The proposed method uses an exhaustive search to determine a globally optimal solution representing the best PMU placement for that particular power system. To obtain a more comprehensive model, contingencies and the limitation of the number of PMU measurement channels are considered and embodied in the model as changes to the original constraints and as additional constraints. The proposed method is examined for applicability using the IEEE 14-bus, 118-bus and 300-bus test systems. The comparison between SOOPP results and results obtained by other methods reveals the excellence of SOOPP. Furthermore, practical large-scale power systems are also successfully analyzed using SOOPP.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.7
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• pp.313-322
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• 2000

This paper presents optimal placement of minimal set of Phasor Measurement Units (PMU's) and observability analysis of the network with PMU's. In order to find a observable system, a symbolic method which directly assigns an appropriate symbol for measurement or pseudo-measurement to every entry of node-branch incidence matrix is proposed. It is much simpler and easier to analyze the observability of the network with PMU's than the conventional ones. For the optimal PMU placement problem, two approaches which are based on a modified Simulated-Annealing (SA) method and a Direct Combination method are proposed. Some case studies with IEEE sample system are made to show the performance of the proposed methods are almost alike and more effective than the conventional simulated-annealing method. It is also shown that the Direct Combination method is more effective than the modified simulated-annealing one in the sense of computation burden. The results of this study showed also that the accuracy of power system estimation and system observability can be improved the proposed PMU placements.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.474-486
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• 2015

This paper proposes a multi-objective optimal placement method of Phasor Measurement Units (PMUs) in large electric transmission systems. It is proposed for minimizing the number of PMUs for complete system observability and maximizing measurement redundancy of the buses, simultaneously. The measurement redundancy of the bus indicates that number of times a bus is able to monitor more than once by PMUs set. A high level of measurement redundancy can maximize the system observability and it is required for a reliable power system state estimation. Therefore, simultaneous optimizations of the two conflicting objectives are performed using a binary coded firefly algorithm. The complete observability of the power system is first prepared and then, single line loss contingency condition is added to the main model. The practical measurement limitation of PMUs is also considered. The efficiency of the proposed method is validated on IEEE 14, 30, 57 and 118 bus test systems and a real and large- scale Polish 2383 bus system. The valuable approach of firefly algorithm is demonstrated in finding the optimal number of PMUs and their locations by comparing its performance with earlier works.