A cost-benefit multiobjective approach for placement of meters in electrical distribution systems

Duque, Felipe Gomes; Oliveira, Leonardo W. de; Oliveira, Edimar J. de; Souza, Julio Cesar Stacchini de

doi:10.1016/j.epsr.2020.106897

Cited by 7 publications

(4 citation statements)

References 26 publications

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“…In contrast, probabilistic percentage error was proposed to handle the impacts of failure probability and transmitting faulty data, probability in distribution network estimation problem to accomplish preset probabilistic error percentage in magnitude and angle [12]. Modified Greedy Algorithm [13] was used to solve the tri objective optimization problem; however, [14] suggested a technique for assigning metering equipment in electrical distribution systems and strives to provide candidate solutions that represent strong trading between two competing objectives. The Non-Dominated Sorting Genetic Algorithm [15] was also used for solving optimal PMU placement problems.…”

Section: State Of the Art Methodsmentioning

confidence: 99%

Optimal PMU placements using sea lion optimization for adaptable distribution system

Arivazhagan¹,

Srikrishna²,

Kaliyan³

et al. 2022

J. meas. eng.

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The technological advancements and policy reformations make the electric power distribution system an active network. The modern power system operational regulations encourage coordinated network operations among various entities and customer participation. Unlike traditional operational environments, real-time monitoring has become a mandate for secure and reliable operations. Phasor Measurement Units (PMU) is the most reliable data acquisition tool, and their application for State Estimation (SE) has already been proven. This work extends the application of PMUs for the distribution system. A multi-objective optimization framework is proposed considering the optimal placement of PMU, network reconfiguration, and topology expansion. A novel optimization tool, the sea lion optimizer has been chosen to address the developed optimization problem. The proposed operational model is employed in IEEE RBTS-2 bus system, IEEE 33 node system and 69 node radial distribution network. Numerical results provide new insights into PMUs role in enhancing distribution network operations. The statistical indices confirm that the intended optimizer performs well in the chosen highly constrained optimization environment.

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Section: State Of the Art Methodsmentioning

confidence: 99%

Optimal PMU placements using sea lion optimization for adaptable distribution system

Arivazhagan¹,

Srikrishna²,

Kaliyan³

et al. 2022

J. meas. eng.

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“…These assumptions, although simplistic, have been adopted because they concern modelling details beyond the desired goal of the simulations, which is to show the operation and the concepts behind the proposed meter placement strategy. Finally, regarding the costs of the meters, the total investment associated with the installation of a meter is assumed equal to 40 kC (same order of magnitude as in [34]), with an amortization over 15 years.…”

Section: A Simulation Setup and Scenariosmentioning

confidence: 99%

A Meter Placement Strategy for Distribution Grids Based on Cost–Benefit Analysis

Pau,

Ginocchi,

Pacheco

et al. 2024

IEEE Trans. Instrum. Meas.

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Distribution system operators are progressively expanding the measurement infrastructure in their grids in order to enhance the real-time monitoring capabilities. Meter placement algorithms allow identifying the best type and location for new measurements, thus being a key tool in support of meter installation decisions and planning. Existing meter placement solutions aim at reducing the monitoring uncertainties below an arbitrary accuracy threshold, but typically they are not explicitly linked to some tangible benefits achievable by the grid operator via the measurement infrastructure upgrade. This paper aims at filling this gap by presenting an overall meter placement strategy that takes into account how the monitoring uncertainties translate into costs for avoiding contingencies and then drives the meter placement process according to the economic benefit resulting from the reduction of those uncertainties. An exemplary implementation is presented to describe the underlying concepts and the role and functionalities of the different software components involved in the meter placement cost-benefit analysis. Simulations performed on a sample grid show the application of the proposed meter placement strategy in a realistic scenario and highlight how this may be used to determine not only type and location of the new meters but also the number of measurements that makes sense to install according to cost-benefit criteria.

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“…The State Estimation problem is widely evaluated by the quadratic error, formulated in (1), called SEE (State Estimation Error) [10]. In addition to the SEE index, the present work also evaluates three more indices proposed by [8]:…”

Section: Background 21 Estimation Indicesmentioning

confidence: 99%

A Hybrid Meta-Heuristic Approach for Optimal Meter Allocation in Electric Power Distribution Systems

Almeida¹,

Braga²,

Oliveira³

et al. 2023

Learn. Nonlin. Mod.

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The number of nodes present in Electric Power Distribution Systems (EPDS) is a complicating factor for carrying out the State Estimation (SE) and the choice of allocation of available meters affects the quality of observability obtained by the SE. Thus, it is necessary to use optimization methods that evaluate the positions of meters in the system that can contribute to an optimal SE. Artificial Neural Networks (ANN) can perform SE, processing the information obtained by the available meters in an agile way. Meta-heuristics techniques apply to the optimal allocation problem but can be slow processing. Thus, the work seeks to evaluate the potential of a hybrid method that associates the meta-heuristic technique, Artificial Immune System (AIS), with ANNs for evaluating several allocation options in an agile way to find an optimal solution for the allocation of meters.

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A cost-benefit multiobjective approach for placement of meters in electrical distribution systems

Cited by 7 publications

References 26 publications

Optimal PMU placements using sea lion optimization for adaptable distribution system

Optimal PMU placements using sea lion optimization for adaptable distribution system

A Meter Placement Strategy for Distribution Grids Based on Cost–Benefit Analysis

A Hybrid Meta-Heuristic Approach for Optimal Meter Allocation in Electric Power Distribution Systems

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