Distribution network reliability enhancement and power loss reduction by optimal network reconfiguration

Anteneh, Degarege; Khan, Baseem; Mahela, Om Prakash; Alhelou, Hassan Haes; Guerrero, Josep M.

doi:10.1016/j.compeleceng.2021.107518

Cited by 23 publications

(13 citation statements)

References 15 publications

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“…Experimental research has shown that most outages will occur at distribution network within the entire power system because of the instability of new energy and EVs [10]. Besides, serious power loss is a major problem in different size of distribution networks [11].…”

Section: B Development and Research Status Of Dnrmentioning

confidence: 99%

“…This work emphasizes the loss of DNR, enhance reliability and improve the voltage profile. In literature [10], some reliable indexes of distribution network were presented including the system average interruption frequency index (SAIFI), system average interruption duration index (SAIDI), and expected energy not supply (EENS). Study [19] considered the uncertainty of DGs, the safe and economic operation of the loads.…”

Section: B Development and Research Status Of Dnrmentioning

confidence: 99%

“…. N br (10) where I m means the current flow in mth branch; I m,max refers to the maximum standard in different distribution network.…”

Section: ) Maximum Current Constraintmentioning

confidence: 99%

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Multi-Objective Optimization for Distribution Network Reconfiguration With Reactive Power Optimization of New Energy and EVs

2023

IEEE Access

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The rise of new energy and the wide application of electric vehicles (EVs) have led to the substantial expansion of distribution network in recent years. The problems such as the decline of transmission reliability and the rise of power loss in distribution network are becoming increasingly serious. Therefore, distribution network can greatly improve its reliability and quality of power supply voltage through changing topology. This work built a distribution network reconfiguration (DNR) model with new energy and EVs firstly. Then, the position of bus tie switches and the reactive power regulation range of new energy and EVs were proposed as decision variables. A multi-objective evolutionary algorithm would be applied to this DNR model and the optimization results will be obtained when considering the line loss and voltage deviation as the objective function. In order to get different optimal compromise solutions with the changes of actual environment, this work employed a new decision-making method named Prevalence Effect Method (PEM). Finally, a high-quality strategy of DNR and reactive power regulation will be obtained.

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Section: B Development and Research Status Of Dnrmentioning

confidence: 99%

Section: B Development and Research Status Of Dnrmentioning

confidence: 99%

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Multi-Objective Optimization for Distribution Network Reconfiguration With Reactive Power Optimization of New Energy and EVs

2023

IEEE Access

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“…Total Real Power Loss. Te NR problem, which is represented mathematically as follows, is to minimize the network topology's total real power loss [11].…”

Section: Problem Formulationmentioning

confidence: 99%

“…For the network reconfguration, modifed shark-smell optimization [11] and the improved cuckoo search algorithm (ICSA) [12] were used to solve a real distribution system to enhance the voltage profle and reduce power loss, but this algorithm requires complex parameter selection. For the dynamic distribution network reconfguration problem, a multigroup fight slime mould algorithm (MFSMA) was proposed in [13] by combining an adaptive Levy fight strategy and multigroup optimization.…”

Section: Introductionmentioning

confidence: 99%

Application of Optimal Network Reconfiguration for Loss Minimization and Voltage Profile Enhancement of Distribution System Using Heap-Based Optimizer

Otuo-Acheampong

Rashed

Akwasi

et al. 2023

International Transactions on Electrical Energy Systems

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A distribution system’s network reconfiguration (NR) is the process of changing the status of the switches to change the topology of the feeders. Using optimal NR at various network load levels, this research proposed an economical way for improving the voltage profile and reducing power loss in distribution systems. A new metaheuristic Heap-based optimizer based on the corporate rank hierarchy is used to solve the optimization problem in order to find the optimal radial distribution network. The objective functions used in this article include voltage profile improvement, power loss reduction, reduction of operation cost, and minimization of gas emissions. This novel technique provides accurate results while avoiding the issue of premature convergence and requires fewer control parameter settings. The proposed method is evaluated at three different load levels on a standard IEEE 33-bus test system, and the simulation results are compared to those of other optimization methods published in the literature, demonstrating that the proposed method improves the system voltage profile while minimizing losses and power costs, establishing that this technique is effective in finding the best result. The Wilcoxon and Friedman tests are also used to verify the effectiveness of the proposed technique.

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Distributed generator and capacitor‐embedded reconfiguration in three‐phase unbalanced distribution systems using teaching learning‐based optimization

Mehroliya,

Arya

2023

Comp Applic In Engineering

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In the transmission and distribution networks, both active and reactive power play significant roles. While active power does the beneficial work, reactive power maintains the voltage that necessitates management from a system reliability perspective. The voltage variation from the nominal range may result in unintentional operation and early component failure. To maximize the amount of real power that can be transported over the power‐transmitting media, the system must also control reactive power flow. In a three‐phase unbalanced distribution system reinforced with distributed generator units (DGUs) and shunt capacitor units (SCUs), this paper suggests a teaching learning‐based optimization (TLBO) approach to be applied to combinatorial problems for simultaneous reduction of real power loss and net reactive power flow, enhance voltage stability index (VSI) and minimize aggregated voltage deviation index. A multiobjective formulation based on TLBO has been implemented to choose the ideal sizes and placements of DGUs and SCUs in large distribution networks. The case studies have been carried out on an IEEE 33‐bus standard system and a large 123‐bus unbalanced system. The analysis of the IEEE 33‐ and 123‐bus test systems reveals the economic efficiency of the suggested TLBO algorithm. Notably, by applying DG and capacitor simultaneously in the 33‐bus system, a significant reduction of 59.35%, 55.05%, and 50.76% (phases a, b, and c), and for the 123‐bus system, a significant reduction of 43.65%, 19%, and 48.65% (phases a, b, and c) in total active power losses have been achieved. The results suggest that the proposed method renders significant improvement in voltage stability and reduces power losses concerning the base case for both test systems.

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Distribution network reliability enhancement and power loss reduction by optimal network reconfiguration

Cited by 23 publications

References 15 publications

Multi-Objective Optimization for Distribution Network Reconfiguration With Reactive Power Optimization of New Energy and EVs

Multi-Objective Optimization for Distribution Network Reconfiguration With Reactive Power Optimization of New Energy and EVs

Application of Optimal Network Reconfiguration for Loss Minimization and Voltage Profile Enhancement of Distribution System Using Heap-Based Optimizer

Distributed generator and capacitor‐embedded reconfiguration in three‐phase unbalanced distribution systems using teaching learning‐based optimization

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