Dynamic and multi-objective reconfiguration of distribution network using a novel hybrid algorithm with parallel processing capability

Jafari, Amirreza; Ganjehlou, Hamed Ganjeh; Darbandi, Farzad; Mohammadi‐Ivatloo, Behnam; Abapour, Mehdi

doi:10.1016/j.asoc.2020.106146

Cited by 53 publications

(34 citation statements)

References 29 publications

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“…Then, the decision matrix R = [r ij ] n×m is formed according to decision values (11), (12), and (13) with the benefit objective function, cost objective function, and interval objective function. (11) where r ij represents the decision value when the objective function is defined as the benefit type index.…”

Section: Grey Target Decision-making Modelmentioning

confidence: 99%

“…(11) where r ij represents the decision value when the objective function is defined as the benefit type index. (12) where r ij represents the decision value when the objective function is defined as the cost type index.…”

Section: Grey Target Decision-making Modelmentioning

confidence: 99%

“…Many studies have exploited hybrid algorithms based on previously cited researchers who proposed methods for multiobjective distribution system reconfiguration in a structure, as in [5], [6], and other studies have considered the correlation among objectives by the grey correlation method in evolutionary programming and its role in optimizing particles by integrating the objectives. Additionally, some studies have focused on providing the multiobjective problem of network reconfiguration with different techniques, such as fuzzy evaluation theory [8]- [10] and cloud theory [11], and all of these approaches can obtain ideal solutions with better objectives [12], [13]. These methods, which are subject to uncertainty theory, can improve the quality of the solutions, especially for traditional distribution systems, but they cannot achieve the optimal variability of load and DG for a distribution network.…”

Section: Introductionmentioning

confidence: 99%

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A Chaos Disturbed Beetle Antennae Search Algorithm for a Multiobjective Distribution Network Reconfiguration Considering the Variation of Load and DG

Wang

Yuan

et al. 2020

IEEE Access

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As the distributed generation (DG) in a power supply and the user load demand constantly change in an actual distribution network, multiobjective optimal network reconfiguration considering variations in load and DG has become a major concern, which is important and required to make system operations safe and economical. The aim is to minimize the sum of the active power loss, the sum of the load balancing index and the sum of the maximum node voltage deviation index simultaneously during the reconfiguration period. Here, this article proposes a new Chaos Disturbed Beetle Antennae Search (CDBAS) algorithm to reduce the computational time and solve the multiobjective optimal problem of network reconfiguration. To adopt the Chaos Disturbed Beetle Antennae Search algorithm for solving this multiobjective problem, grey target decision-making technology is used to rank the beetles. Additionally, to the enhance the system static voltage stability and voltage quality, a grey target decision-making model is established to achieve a layer relationship between each index and the switching operation index. The plausibility and effectiveness of the presented methodology is verified on the modified IEEE 33, 69 and 118-Bus Test Radial Distribution Network. Finally, compared with other research methods in the literature, the CDBAS algorithm outperforms other algorithms and produces a quality decision solution. INDEX TERMS Distribution system, load and distributed generation variation, multiobjective optimization, grey target decision-making, CDBAS algorithm. HAIYUN WANG received the B.E. degree in electric power systems and automation from Xin

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Section: Grey Target Decision-making Modelmentioning

confidence: 99%

Section: Grey Target Decision-making Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Chaos Disturbed Beetle Antennae Search Algorithm for a Multiobjective Distribution Network Reconfiguration Considering the Variation of Load and DG

Wang

Yuan

et al. 2020

IEEE Access

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“…In [27]- [29], to solve the optimization problem for the normal operation of a distribution network for all objective functions simultaneously, a non-dominated sorting genetic algorithm was improved based on fuzzy theory and a mathematical simplification process. In [30]- [32], a hybrid evolutionary algorithm for obtaining the best combination of on/off statuses of the switches was introduced for a distribution network considering DG from various aspects, such as time-varying electricity prices and different load levels as well as demand response services with objective functions of operation cost and power loss. Based on the above analysis, we find the following two deficiencies: (1) Artificial intelligence algorithms still face the problems of falling into local optima and poor convergence.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Reconfiguration of Multiobjective Distribution Networks Considering DG and EVs Based on a Novel LDBAS Algorithm

Wang¹,

Wang²,

Wang³

et al. 2020

IEEE Access

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Aiming to improve the operation economy and power quality of distribution systems subject to the fluctuating and stochastic power outputs of distributed generation (DG) units and electric vehicles (EVs), a multiobjective optimization model for network reconfiguration and its corresponding solution method are proposed. First, a dynamic reconfiguration model is constructed based on the power loss rate (PLR) as well as the active power loss, the load balancing index and the maximum node voltage deviation, which serve as the optimization indexes. Second, the Lé vy flight and chaos disturbed beetle antennae search (LDBAS) algorithm is presented based on the grey target decision-making technique, which can not only improve the computational efficiency but also find the most satisfactory solution for the proposed dynamic reconfiguration model. Considering the uncertainties of loads and DG outputs, the influence on the load curve of EV connecting to the distribution network at different penetration rates and under different charging/discharging modes is analysed. Additionally, the modified IEEE 33-bus and 118-bus test radial distribution networks are simulated to verify the effectiveness and superiority of the presented reconfiguration model and the improved LDBAS method, and the results illustrate that the proposed reconfiguration method can improve the operation economy and power quality of the distribution system and encourage the penetration of EVs. INDEX TERMS Distribution system, time-varying characteristics of DGs and EVs, dynamic reconfiguration, multiobjective optimization, grey target decision-making, LDBAS algorithm

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“…In radial distribution networks, shunt capacitors should be installed at appropriate places and in appropriate sizes for reducing currents flowing in branches, improving voltage profiles and minimizing total power losses [1][2][3]. As generally estimated, power loss of distribution networks takes about 13% of total generated power of power systems [4] and it can be reduced by installing shunt capacitors to decrease reactive power flows [5].…”

Section: Introductionmentioning

confidence: 99%

Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints

et al. 2020

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This paper presents a highly effective method of installing both capacitors and PV systems in distribution systems for the purpose of reducing total power loss in branches. Three study cases with the installation of one capacitor, two capacitors and three capacitors were implemented and then the optimal solutions were used to install one more photovoltaic (PV) system. One PV system with 20% active power of all loads and less than active power of all loads was tested for two different conditions: (1) with geography location constraint and (2) without geography location constraint for PV system placement. The results from two systems consisting of 33 and 69 nodes were obtained by using the Stochastic Fractal Search Optimization Algorithm (SFSOA). Simulation results show that this method can determine the appropriate location and size of capacitors to reduce the total power losses more effectively than other existing methods. Furthermore, the paper also demonstrates the real impact of using both capacitors and PV systems to reduce active power loss as well as improve the voltage profile of distribution systems. This paper also finds that if it is possible to place PV systems in all nodes in distribution systems, the benefit from reducing total loss is highly significant and the investment of PV system placement is highly encouraged. As a result, it is recommended that capacitors and PV systems be used in distribution networks, and we claim that two important factors of the installed components consisting of location and size can be determined effectively by using SFSOA.

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Dynamic and multi-objective reconfiguration of distribution network using a novel hybrid algorithm with parallel processing capability

Cited by 53 publications

References 29 publications

A Chaos Disturbed Beetle Antennae Search Algorithm for a Multiobjective Distribution Network Reconfiguration Considering the Variation of Load and DG

A Chaos Disturbed Beetle Antennae Search Algorithm for a Multiobjective Distribution Network Reconfiguration Considering the Variation of Load and DG

Dynamic Reconfiguration of Multiobjective Distribution Networks Considering DG and EVs Based on a Novel LDBAS Algorithm

Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints

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