Phase Balancing in Power Distribution Systems: A heuristic approach based on group-theory

Ríos, Miguel Ángel Rivera; Castaño, Juan Mauricio; Garcés, Alejandro; Molina-Cabrera, Alexander

doi:10.1109/ptc.2019.8810723

Cited by 13 publications

(13 citation statements)

References 11 publications

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“…This same year, it was proposed to minimize the imbalance in distribution systems employing a heuristic search algorithm that generated an optimal system phase shift using contactors for the loads [27]. A year later, it was implemented in coding based on group theory to minimize power losses in distribution systems through a genetic algorithm [28]. Other algorithms aiming at minimizing power losses have been developed to date, such as the analytical approach algorithms, which perform a minimum base exchange [29].…”

Section: Review Of the State Of The Artmentioning

confidence: 99%

Application of the Hurricane-Based Optimization Algorithm to the Phase-Balancing Problem in Three-Phase Asymmetric Networks

2022

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This article addresses the problem of optimal phase-swapping in asymmetric distribution grids through the application of hurricane-based optimization algorithm (HOA). The exact mixed-integer nonlinear programming (MINLP) model is solved by using a master–slave optimization procedure. The master stage is entrusted with the definition of load connection at each stage by using an integer codification that ensures that, per node, only one from the possible six-load connections is assigned. In the slave stage, the load connection set provided by the master stage is applied with the backward/forward power flow method in its matricial form to determine the amount of grid power losses. The computational performance of the HOA was tested in three literature test feeders composed of 8, 25, and 37 nodes. Numerical results show the effectiveness of the proposed master–slave optimization approach when compared with the classical Chu and Beasley genetic algorithm (CBGA) and the discrete vortex search algorithm (DVSA). The reductions reached with HOA were 24.34%, 4.16%, and 19.25% for the 8-, 28-, and 37-bus systems; this confirms the literature reports in the first two test feeders and improves the best current solution of the IEEE 37-bus grid. All simulations are carried out in the MATLAB programming environment.

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Section: Review Of the State Of The Artmentioning

confidence: 99%

Application of the Hurricane-Based Optimization Algorithm to the Phase-Balancing Problem in Three-Phase Asymmetric Networks

2022

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“…Offline [4], [27] Yes Yes No Yes Heuristic No Yes [5], [17], [28] Yes No No Yes Metaheuristic No Yes [6], [21], [24] No Yes No No Experimental No Yes [7], [8], [26] No Yes No Yes Heuristic No Yes [9], [10] Yes No No Yes Heuristic No Yes [12], [13] No Yes Yes No Metaheuristic No Yes [14], [29] No Yes Yes No Experimental Yes No [15], [16] No Yes No Yes Metaheuristic No Yes [18], [32] No No No Yes Heuristic No Yes [19], [20] Yes Regardless of the algorithm used and the locations where the PLB is done, each consumer should have a smart system integrated in the SMS, which to contain in its structure a smart meter and an automatic phase load balancing device (APBD) [27], Figure 2.…”

Section: On -Linementioning

confidence: 99%

“…The solutions for the PLB model were obtained using various techniques and technical measures, such as hierarchical Petri nets [9], low voltage (LV) feeder reconfiguration [10][11], or switching the consumers on the three phases [12][13][14]. In [15][16][17] the studied problem is solved with particular metaheuristic algorithms. A PLB mechanism at the three-phase power transformer level was proposed in [18].…”

Section: Introductionmentioning

confidence: 99%

Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm

Grigoraș¹,

Neagu²,

Gavrilaș³

et al. 2020

Preprint

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In the electric distribution systems, the “Smart Grid” concept is implemented to encourage energy savings and integration of the innovative technologies, helping the Distribution Network Operators (DNOs) in choosing the investment plans which to lead the optimal operation of the networks and increasing the energy efficiency. In this context, a new phase load balancing algorithm was proposed to be implemented in the low voltage distribution networks with hybrid structures of the consumption points (switchable and non-switchable consumers). It can work in both operation modes (on-line and off-line), uploading information from different databases of the DNO which contain: the consumers’ characteristics, the real loads of the consumers integrated into the Smart Metering System (SMS), and the typical load profiles for the consumers non-integrated in the SMS. The algorithm was tested in a real network, having a hybrid structure of the consumption points, on a time interval by 24 hours. The obtained results were analyzed and compared with other algorithms from the heuristic (Minimum Count of Loads Adjustment algorithm) and the metaheuristic (Particle Swarm Optimization and Genetic Algorithms) categories. The best performances were provided by the proposed algorithm, such that the unbalance coefficient resulted in the smallest value (1.0017). The phase load balancing led to the following technical effects: decreasing the average current in the neutral conductor with 94% and for the energy losses with 61.75 %, and increasing the minimum value of the phase voltage at the farthest pillar with the 7.14 %, compared to the unbalanced case.

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“…In the specialized literature, the balance phase problem, with the minimizing power losses approach, has been solved using different optimization methods, including the Chu and Beasley genetic algorithms [8,16,[21][22][23][24], particle swarm optimization [9], mixedinteger convex optimization [25], bat optimization algorithm [26], differential evolution algorithm [27], simulated annealing optimizer [28], and vortex search algorithm [15], among others.…”

Section: Introductionmentioning

confidence: 99%

An Improved Crow Search Algorithm Applied to the Phase Swapping Problem in Asymmetric Distribution Systems

Cortés-Caicedo

Montoya

et al. 2021

Symmetry

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This paper discusses the power loss minimization problem in asymmetric distribution systems (ADS) based on phase swapping. This problem is presented using a mixed-integer nonlinear programming model, which is resolved by applying a master–slave methodology. The master stage consists of an improved version of the crow search algorithm. This stage is based on the generation of candidate solutions using a normal Gaussian probability distribution. The master stage is responsible for providing the connection settings for the system loads using integer coding. The slave stage uses a power flow for ADSs based on the three-phase version of the iterative sweep method, which is used to determine the network power losses for each load connection supplied by the master stage. Numerical results on the 8-, 25-, and 37-node test systems show the efficiency of the proposed approach when compared to the classical version of the crow search algorithm, the Chu and Beasley genetic algorithm, and the vortex search algorithm. All simulations were obtained using MATLAB and validated in the DigSILENT power system analysis software.

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Phase Balancing in Power Distribution Systems: A heuristic approach based on group-theory

Cited by 13 publications

References 11 publications

Application of the Hurricane-Based Optimization Algorithm to the Phase-Balancing Problem in Three-Phase Asymmetric Networks

Application of the Hurricane-Based Optimization Algorithm to the Phase-Balancing Problem in Three-Phase Asymmetric Networks

Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm

An Improved Crow Search Algorithm Applied to the Phase Swapping Problem in Asymmetric Distribution Systems

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