Full Coverage of Optimal Phasor Measurement Unit Placement Solutions in Distribution Systems Using Integer Linear Programming

Chen, Xuebing; Sun, Lu; Chen, Tengpeng; Sun, Yuhao; Rusli, Rusli; Tseng, King Jet; Ling, Keck Voon; Ho, Weng Khuen; Amaratunga, G.A.J.

doi:10.3390/en12081552

Cited by 26 publications

(10 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hence the values of each element are set to be more than the actual connections. In (5), the minimization of the difference between the desired value (M) and the actual value (obtained from PMU placement) is nothing but the maximization of measurement redundancy. The placement set with a minimum MR value will give the best placement result.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Similarly, the BILP is implemented in [4] to solve the placement problem of PMUs with the consideration of communication links for the distributed state estimation in the distribution network. A hybrid ILP-based method is proposed in [5] to solve the OPP problem for the distribution network by finding all the possible solutions with observability. A heuristic Binary-based Particle Swarm Optimization (BPSO) algorithm is proposed in [6] to minimize the PMU number and maximize redundancy.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Allocation of Synchrophasor Units in the Distribution Network Considering Maximum Redundancy

Priyadarshini

Panigrahi

2020

Eng. Technol. Appl. Sci. Res.

View full text Add to dashboard Cite

Phasor Measurement Unit (PMU) is a smart measuring device commonly used in wide-area monitoring systems. It provides the synchronized phasor values and the magnitudes of voltages and currents in real-time for the proper state calculation of the electrical network in a common time reference frame. But in order to avoid unnecessary placements, minimize installation cost, and due to the lack of communication facilities at the substations, the placing of PMUs at every location is not possible. Therefore several optimization techniques have been developed to solve the Optimal PMU Placement (OPP) problem. The OPP problem aims to reduce the number of PMUs by achieving a completely observable network. Many solutions to the OPP problem have been proposed for the transmission networks with the use of conventional and heuristic-based approaches, but very few for distribution networks. In this paper, the Binary Grey Wolf Optimization (BGWO) algorithm is proposed to solve the OPP problem considering the measurement redundancy (MR) to achieve complete observability of the distribution network. Finally, case studies have been done by implementing the proposed algorithm on different IEEE test feeders such as the IEEE -13, -33, -37, and -123 node feeder systems. The obtained results are compared with previous studies to verify the feasibility and efficiency of the proposed technique.

show abstract

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Allocation of Synchrophasor Units in the Distribution Network Considering Maximum Redundancy

Priyadarshini

Panigrahi

2020

Eng. Technol. Appl. Sci. Res.

View full text Add to dashboard Cite

show abstract

“…In [12,13], integer linear programming and backtracking search were respectively used for optimizing PMU allocation to minimize the number of units and maximize measurement redundancy. In [14], information theory was used to formulate the PMU placement in terms of mutual information, which was then optimized by means of a greedy algorithm in order to reduce the number of PMU units while guaranteeing complete system observability.…”

Section: Related Workmentioning

confidence: 99%

Reliability Based Genetic Algorithm Applied to Allocation of Fiber Optics Links for Power Grid Automation

et al. 2019

View full text Add to dashboard Cite

In this work, we address the problem of allocating optical links for connecting automatic circuit breakers in a utility power grid. We consider the application of multi-objective optimization for improving costs and power network reliability. To this end, we propose a novel heuristic for attributing reliability values to the optical links, which makes the optimization converge to network topologies in which nodes with higher power outage indexes receive greater communication resources. We combine our heuristic with a genetic algorithm in order to solve the optimization problem. In order to validate the proposed method, simulations are carried out with real data from the local utility. The obtained results validate the allocation heuristic and show that the proposed algorithm outperforms gradient descent optimization in terms of the provided Pareto front.

show abstract

“…Even though PMUs are superior to SCADA, they are costly and cannot be installed at all the power system buses. Therefore, optimal PMU Placement (OPP) was introduced to guarantee complete power system observability by deploying fewer PMUs than the number of the buses in the network hence minimizing their installation costs [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission network

Okendo¹,

Wekesa²,

Saulo³

2021

Heliyon

View full text Add to dashboard Cite

Modern power systems require advanced monitoring and control, a capability made possible by Phasor Measurement Units (PMUs) aided by synchrophasor technology. Because PMUs have significant costs, it is necessary to optimally place them in an electrical power network. This paper proposes the Optimal PMU Placement (OPP) on the Kenya Power Transmission Network (Nairobi Region 30-bus system) using the existing methods; The Depth-First method, the Mixed Integer Linear Programming (MILP) using intlinprog solver, and the Artificial Bee Colony (ABC) algorithm. The algorithms are first implemented on the IEEE-14 and 30 bus test systems for verification before implementing the Kenya Power Transmission Network (Nairobi Region 30-bus system). Finally, the results for the three methods are compared. A key consideration is the System Observability Redundancy Index (SORI) under normal baseload conditions, with and without the inclusion of Zero Injection Buses (ZIBs). A higher value of SORI increases the measurement redundancy of the PMUs installed at a given bus. This paper further proposes the modelling of ZIB with adjacent buses by considering their Observability Index (OI). The case studies are modelled in Power System Analysis Toolbox (PSAT), and the simulations are carried out in MATLAB. From the simulation results, the ABC algorithm gives the optimal solution with the highest SORI compared to the Depth-First method and MILP, with the exclusion of the ZIB. The Nairobi region 30-bus system require 12 PMUs located at buses; 2, 5, 8, 9, 11, 13, 14, 16, 21, 24, 27 and 29 for complete power system observability with a SORI of 43.

show abstract

Full Coverage of Optimal Phasor Measurement Unit Placement Solutions in Distribution Systems Using Integer Linear Programming

Cited by 26 publications

References 19 publications

Optimal Allocation of Synchrophasor Units in the Distribution Network Considering Maximum Redundancy

Optimal Allocation of Synchrophasor Units in the Distribution Network Considering Maximum Redundancy

Reliability Based Genetic Algorithm Applied to Allocation of Fiber Optics Links for Power Grid Automation

Optimal placement of Phasor Measurement Unit considering System Observability Redundancy Index: case study of the Kenya power transmission network

Contact Info

Product

Resources

About