Power flow methods used in AC distribution networks: An analysis of convergence and processing times in radial and meshed grid configurations

Grisales-Noreña, Luis Fernando; Morales-Duran, J.C.; Velez-Garcia, S.; Montoya, Oscar Danilo; Gil-González, Walter

doi:10.1016/j.rineng.2023.100915

Cited by 19 publications

(15 citation statements)

References 28 publications

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“…The results presented in Section 4 underscore significant achievements in computational efficiency within the mixed-integer nonlinear model. Notably, by replacing the Radiality Constraint proposed by [11] with a larger set of constraints, each involving fewer variables (15), we observed a marked improvement in computation time. This strategic adjustment reflects the benefit of this approach to represent radiality conditions, instead of the traditional method used in the literature.…”

Section: Discussionmentioning

confidence: 91%

“…in the power triangle constraint leads to deviations in topological decisions. The error associated with using the set of Constraint ( 16) was quantified using Gauss-Seidel power flow analysis [15] and is detailed in Table 3 under the column "%ER". In the 133 bus system, the model shows a 3% discrepancy in power loss compared to those reported in the literature, despite achieving an optimality gap of 0%.…”

Section: Discussion Of Resultsmentioning

confidence: 99%

“…Concerning the relaxation of the original problem, Merlin et al [5] assumed a purely resistive distribution network, making power flow calculations to estimate losses in a DC load flow. This approach has significant limitations, as distribution networks typically do not exhibit a significantly higher resistive component than inductive [15]. The same assumption was made by Broadwatert et al [16], by assuming a power factor near one throughout the distribution network.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Base model (14-13), (14-9), (14-4), , , , , , , (4-3), (4-2), (3-7), (2-1) Model with radiality reformulated (14-13), (14-9), (14-4), , , , , , , (4-3), (4-2), (3-7), (2-1) Linearization of term V 2 i I 2 k,i (14-13), (14-9), (14-4), , , , , , , (4-3), (4-2), (3-7), (2-1) Double constraint for power triangle (14-13), (14-9), (14-4), , , , , , , (4-3), (4-2), (3-7), (2-1) (1-2), (2-3), (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19), (3)(4), , (4-5), (5-6), (6-7), , (8)(9), (9)(10)(11)(12)(13)(14)(15), , , (12)(13), (13)(14), (15)(16), (16)(17), (17)(18), (18)(19)(20)(21)(22)(23)(24)(25)(26)(27)…”

Section: Model Optimal Treementioning

confidence: 99%

“…(1-2), (2-3), (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19), (3)(4), , (4-5), (5-6), (6-7), , (8)(9), (9)(10)(11)(12)(13)(14)(15), , , (12)(13), (13)(14), (15)(16), (16)(17), (17)(18), (18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33),…”

Section: Model Optimal Treementioning

confidence: 99%

See 4 more Smart Citations

An Innovative Approach to Radiality Representation in Electrical Distribution System Reconfiguration: Enhanced Efficiency and Computational Performance

Cortés Sanabria,

Tabares Pozos,

Álvarez-Martínez

et al. 2024

Energies

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The reconfiguration problem (DPSR) in electrical distribution systems is a critical area of research, aimed at optimizing the operational efficiency of these networks. Historically, this problem has been approached through a variety of optimization methods. Regarding mathematical models, a key challenge identified in these models is the formulation of equations that ensure the radial operation of the system, along with the nonlinear equations representing Kirchhoff’s laws, the last often necessitating complex relaxations for practical application. This paper introduces an alternative representation of system radiality, which potentially surpasses or matches the existing methods in the literature. Our approach utilizes a more intuitive and compact set of equations, simplifying the representation process. Additionally, we propose a linearization of the current calculation in the power flow model typically used to solve DPSR. This linearization significantly accelerates the process of obtaining feasible solutions and optimal reconfiguration profiles. To validate our approach, we conducted rigorous computational comparisons with the results reported in the existing literature, using a variety of test cases to ensure robustness. Our computational results demonstrate a considerable improvement in computational time. The objective functions used are competitive and, in many instances, outperform the best reported results in the literature. In some cases, our method even identifies superior solutions.

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Section: Discussionmentioning

confidence: 91%

Section: Discussion Of Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Model Optimal Treementioning

confidence: 99%

Section: Model Optimal Treementioning

confidence: 99%

See 3 more Smart Citations

An Innovative Approach to Radiality Representation in Electrical Distribution System Reconfiguration: Enhanced Efficiency and Computational Performance

Cortés Sanabria,

Tabares Pozos,

Álvarez-Martínez

et al. 2024

Energies

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Co-simulation-based optimal reactive power control in smart distribution network

Wagle,

Pham,

Tricarico

et al. 2023

Electr Eng

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The increasing integration of distributed energy resources such as photovoltaic (PV) systems into distribution networks introduces intermittent and variable power, leading to high voltage fluctuations. High PV integration can also result in increased terminal voltage of the network during periods of high PV generation and low load consumption. These problems can be solved by optimal utilization of the reactive power capability of a smart inverter. However, solving the optimization problem using a detailed mathematical model of the distribution network may be time-consuming. Due to this, the optimization process may not be fast enough to incorporate this rapid fluctuation when implemented in real-time optimization. To address these issues, this paper proposes a co-simulation-based optimization approach for optimal reactive power control in smart inverters. By utilizing co-simulation, the need for detailed mathematical modeling of the power flow equation of the distribution network in the optimization model is eliminated, thereby enabling faster optimization. This paper compares three optimization algorithms (improved harmony search, simplicial homology global optimization, and differential evolution) using models developed in OpenDSS and DigSilent PowerFactory. The results demonstrate the suitability of the proposed co-simulation-based optimization for obtaining optimal setpoints for reactive power control, minimizing total power loss in distribution networks with high PV integration. This research paper contributes to efficient and practical solutions for modeling optimal control problems in future distribution networks.

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Development of hierarchical two-stage constrained spectral clustering algorithm to enhance power system distribution network resiliency under zonal attacks

Priya,

Preetha Roselyn

2024

Electr Eng

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Power flow methods used in AC distribution networks: An analysis of convergence and processing times in radial and meshed grid configurations

Cited by 19 publications

References 28 publications

An Innovative Approach to Radiality Representation in Electrical Distribution System Reconfiguration: Enhanced Efficiency and Computational Performance

An Innovative Approach to Radiality Representation in Electrical Distribution System Reconfiguration: Enhanced Efficiency and Computational Performance

Co-simulation-based optimal reactive power control in smart distribution network

Development of hierarchical two-stage constrained spectral clustering algorithm to enhance power system distribution network resiliency under zonal attacks

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