Asymmetric power consumption in rural electric networks

Наумов, И. В.; Karamov, Dmitriy; Tretyakov, A N; Yakupova, M A; Fedorinova, E S

doi:10.1088/1755-1315/677/3/032088

Cited by 1 publication

(1 citation statement)

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“…This implies that the currents through all the lines are generally asymmetric [27,28], which significantly increases the energy losses of the network with respect to the ideal balanced case. Ultimately, this has a negative impact on the net profit of the distribution company in the electricity commercialization activity [29]. In order to address the problem of load balancing in three-phase networks, we propose an optimization model from the family of mixedinteger nonlinear programming (MINLP) methods, which are suitable for the analysis of multiperiod operating environments.…”

Section: General Optimization Modelmentioning

confidence: 99%

Operating Cost Reduction in Distribution Networks Based on the Optimal Phase-Swapping including the Costs of the Working Groups and Energy Losses

2021

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The problem of optimal phase-balancing in three-phase asymmetric distribution networks is addressed in this research from the point of view of combinatorial optimization using a master–slave optimization approach. The master stage employs an improved sine cosine algorithm (ISCA), which is entrusted with determining the load reconfiguration at each node. The slave stage evaluates the energy losses for each set of load connections provided by the master stage by implementing the triangular-based power flow method. The mathematical model that was solved using the ISCA is designed to minimize the annual operating costs of the three-phase network. These costs include the annual costs of the energy losses, considering daily active and reactive power curves, as well as the costs of the working groups tasked with the implementation of the phase-balancing plan at each node. The peak load scenario was evaluated for a 15-bus test system to demonstrate the effectiveness of the proposed ISCA in reducing the power loss (18.66%) compared with optimization methods such as genetic algorithm (18.64%), the classical sine cosine algorithm (18.42%), black-hole optimizer (18.38%), and vortex search algorithm (18.59%). The IEEE 37-bus system was employed to determine the annual total costs of the network before and after implementing the phase-balancing plan provided by the proposed ISCA. The annual operative costs were reduced by about 13% with respect to the benchmark case, with investments between USD 2100 and USD 2200 in phase-balancing activities developed by the working groups. In addition, the positive effects of implementing the phase-balancing plan were evidenced in the voltage performance of the IEEE 37-bus system by improving the voltage regulation with a maximum of 4% in the whole network from an initial regulation of 6.30%. All numerical validations were performed in the MATLAB programming environment.

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Section: General Optimization Modelmentioning

confidence: 99%