Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems

Souza, Simone Silva Frutuoso de; Romero, Rubén

doi:10.1016/j.epsr.2014.10.012

Cited by 39 publications

(40 citation statements)

References 21 publications

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“…It can be observed that after the reconfiguration the voltage levels are improved and all nodal voltages comply with the specified limits. It is noteworthy that the final topologies obtained for the DSR problem considering several demands, for all test systems, were the same as the ones identified considering a single demand, as presented in [7].…”

Section: A Test Systems With 33 70 84 and 136 Busesmentioning

confidence: 81%

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Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios

Souza

Romero

Pereira

et al. 2015

2015 IEEE Eindhoven PowerTech

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Abstract-This paper describes the application of the specialized genetic algorithm of Chu-Beasley to solve the Distribution System Reconfiguration, DSR, problem considering different demand scenarios. This algorithm is an approach inspired in the natural selection and evolution of species. The reconfiguration problem of distribution networks taking into account different demand scenarios aims at identifying the most adequate radial topology of a distribution system assuming that this topology is used for all demand scenarios under study. This search is driven by the minimization of the cost of energy losses in the network along a full operation year. The performance of the algorithm is evaluated considering test systems having 33, 70, 84 and 136 buses and a real system with 417 buses. The obtained results confirm the robustness and efficiency of the developed approach and its potential to be used in distribution control centers.

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Section: A Test Systems With 33 70 84 and 136 Busesmentioning

confidence: 81%

“…The computation time taken to identify the final topology for this system is presented in the Table VIII. The final topology obtained for the DSR problem considering several demands, for the real systems with 417 buses was the same one that was obtained for the DSR problem considering a single demand, as presented in [7].…”

Section: B Real Systems With 417 Busesmentioning

confidence: 95%

Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios

Souza

Romero

Pereira

et al. 2015

2015 IEEE Eindhoven PowerTech

Self Cite

View full text Add to dashboard Cite

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“…The obtained results were compared with those in the literature in order to validate and prove the efficiency of the proposed algorithm. Souza et al [25] also aim to solve the reconfiguration problem of EDS by comparing the results of the Copt-aiNet (artificial immune network for combinatorial optimization) and the Opt-aiNet (artificial immune network for optimization) algorithms. A specialized forward/backward radial power flow was used to evaluate each of the proposed solutions in order to determine its power losses and its feasibility regarding the operational constraints of the EDS.…”

Section: Ais Applications In Energymentioning

confidence: 99%

An Evaluation of a Metaheuristic Artificial Immune System for Household Energy Optimization

et al. 2018

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Devices in a smart home should be connected in an optimal way; this helps save energy and money. Among numerous optimization models that can be found in the literature, we would like to highlight artificial immune systems, which use special bioinspired algorithms to solve optimization problems effectively. The aim of this work is to present the application of an artificial immune system in the context of different energy optimization problems. Likewise, a case study is performed in which an artificial immune system is incorporated in order to solve an energy management problem in a domestic environment. A thorough analysis of the different strategies is carried out to demonstrate the ability of an artificial immune system to find a successful optima which satisfies the problem constraints.

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“…An Artificial Immune Network for Combinatorial Optimization (Copt-aiNet)-based and Artificial Immune Network for Optimization (Opt-aiNet) approach was used in [39] to solve the reconfiguration problem. It uses the fundamental loop theory to avoid non-radial configurations and a backward/forward sweep-based method to evaluate affinity, which is the objective function (power losses).…”

Section: Immune Algorithms (Ia)mentioning

confidence: 99%

Recent Trends of the Most Used Metaheuristic Techniques for Distribution Network Reconfiguration

Quintero-Duran

Candelo-Becerra

Sousa

2017

JESTR

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Distribution network reconfiguration (DNR) continues to be a good option to reduce technical losses in a distribution power grid. However, this non-linear combinatorial problem is not easy to assess by exact methods when solving for large distribution networks, which requires large computational times. For solving this type of problem, some researchers prefer to use metaheuristic techniques due to convergence speed, near-optimal solutions, and simple programming. Some literature reviews specialize in topics concerning the optimization of power network reconfiguration and try to cover most techniques. Nevertheless, this does not allow detailing properly the use of each technique, which is important to identify the trend. The contributions of this paper are three-fold. First, it presents the objective functions and constraints used in DNR with the most used metaheuristics. Second, it reviews the most important techniques such as particle swarm optimization (PSO), genetic algorithm (GA), simulated annealing (SA), ant colony optimization (ACO), immune algorithms (IA), and tabu search (TS). Finally, this paper presents the trend of each technique from 2011 to 2016. This paper will be useful for researchers interested in knowing the advances of recent approaches in these metaheuristics applied to DNR in order to continue developing new best algorithms and improving solutions for the topic.

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Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems

Cited by 39 publications

References 21 publications

Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios

Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios

An Evaluation of a Metaheuristic Artificial Immune System for Household Energy Optimization

Recent Trends of the Most Used Metaheuristic Techniques for Distribution Network Reconfiguration

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