Distribution network reconfiguration and reactive power compensation using a hybrid Simulated Annealing – Minimum spanning tree algorithm

Stojanović, Branko; Rajić, Tomislav; Šošić, Darko

doi:10.1016/j.ijepes.2022.108829

Cited by 15 publications

(9 citation statements)

References 22 publications

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“…For a rational allocation problem, in other words, there are more possible (recipient) locations than factually active tools to be settled to those locations to further satisfy consumers. Such problems are solved by using minimum spanning trees to ensure efficient coverage with the minimum of cost [3], [4]. In particular, article [5] considered a problem of building a minimum spanning tree connecting a given number of the nodes, which can be less than the cardinality of the initial set of planar nodes.…”

Section: Available Node Constraintmentioning

confidence: 99%

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Pruning Minimum Spanning Trees and Cutting Longest Edges to Connect a Given Number of Nodes by Minimizing Total Edge Length

Romanuke

2023

ITS

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Background. Whereas in many tasks of designing efficient telecommunication networks, the number of network nodes is limited, the initial choice of nodes is wider. There are more possible locations than factually active tools to be settled to those locations to further satisfy consumers. This induces an available node constraint problem. Objective. Given an initial set of planar nodes, the problem is to build a minimum spanning tree connecting a given number of the nodes, which is less than the cardinality of the initial set. Therefore, the available node constraint problem aims at building an optimally minimum spanning tree to connect a given number of planar nodes being less than an initial number of nodes by minimizing the tree length. Methods. The initial set of nodes is triangulated. This gives a set of edges, whose lengths are calculated and used as graph weights. A minimum spanning tree is built over this graph. The desired number of nodes is reached by pruning the minimum spanning tree connecting the initial number of nodes, where free edges whose weights are the largest are iteratively removed from the tree. The other approach, the cutting method, removes longest edges off the initial minimum spanning tree, regardless of whether they are free or not. Results. Unlike the pruning method, the method of cutting longest edges may result in a minimum spanning tree connecting fewer nodes than the desired number. However, the cutting method often outputs a shorter tree, especially when the edge length varies much. Besides, the cutting method is slower due to it iteratively rebuilds a minimum spanning tree. Conclusions. The problem is initially solved by the pruning method. Then the cutting method is used and its solution is compared to the solution by the pruning method. The best tree is shorter. A tradeoff for the nodes and tree length is possible.

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Section: Available Node Constraintmentioning

confidence: 99%

“…It is quite clear that lengths (4) can be used as weights for any graph containing respective edges from set (1). So, length (3) is the weight of edge q E .…”

Section: Pruning Minimum Spanning Treesmentioning

confidence: 99%

Pruning Minimum Spanning Trees and Cutting Longest Edges to Connect a Given Number of Nodes by Minimizing Total Edge Length

Romanuke

2023

ITS

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“…Constraints ( 2) and ( 3) also represent real and imaginary current balance equations in each bus and each hour, which can be achieved using Kirchhoff's current law (KCL) [28][29][30][31]. In addition, equations of real and imaginary terms of the drop in the distribution lines are given by limits ( 4) and (5). Moreover, real and imaginary terms of the current injected to loads in each bus can be calculated based on ( 6) and ( 7) [28,[32][33][34].…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Therefore, system reconfiguration is a desirable program in the distribution network to improve the operating situation. According to the mentioned cases, appropriate energy management of local resources and optimal planning of system reconfiguration can help technical measures to enhance significantly [4,5].…”

Section: Introduction 1motivationmentioning

confidence: 99%

Energy Management Capability in the Reconfigurable Distribution Networks with Distributed Generation for Minimization of Energy Loss

Jiang

Zhang

2023

Applied Sciences

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One of the approaches to improve operation indices, such as power loss and reliability, is to smoothen voltage profiles. Energy management of generation units and network reconfiguration are two methods to achieve this. Hence, the latter is presented in this paper in a distribution with distributed generation units. To this end, an objective function is formulated aiming to minimize power loss and enhance the operating situation of the network. This problem is subject to various constraints and limits such as AC power flow equations, operation limits, planning model, and operation model of distributed generations. It is an integer nonlinear optimization problem and is solved using the crow search algorithm and the optimal solution is obtained. Two major innovations of the study include modeling generation units’ operation and network configuration mathematical expression of operation indicators. The method is applied to a test system and results demonstrate the high performance of this approach in improving the operation of the network. Finding the solution in less time with a satisfying standard deviation are two advantages of the proposed algorithm. Adopting this method, the network operator can reduce power loss through proper management of distributed generation power and optimal scheduling of switches. Moreover, the obtained voltage profile is more desirable in comparison to that of power flow studies.

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“…A comparative analysis of all these methods is presented in Table 1. Other than conventional optimization techniques, some hybrid techniques such as simulated annealing [25,38,41], sunflower optimization [12], bibliography originated [27], Slap swarm [35], and so forth are also obtainable with satisfactory performance indices. Moreover, it is beyond the necessity of the parameter selection for its operation irrespective of the size of the problem and the iteration requirement [22,32].…”

Section: Introductionmentioning

confidence: 99%

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 reconfiguration and reactive power compensation using a hybrid Simulated Annealing – Minimum spanning tree algorithm

Cited by 15 publications

References 22 publications

Pruning Minimum Spanning Trees and Cutting Longest Edges to Connect a Given Number of Nodes by Minimizing Total Edge Length

Pruning Minimum Spanning Trees and Cutting Longest Edges to Connect a Given Number of Nodes by Minimizing Total Edge Length

Energy Management Capability in the Reconfigurable Distribution Networks with Distributed Generation for Minimization of Energy Loss

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

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