Multi-agent design for power distribution system reconfiguration based on the artificial immune system algorithm

Belkacemi, Rabie; Feliachi, A.

doi:10.1109/iscas.2010.5537841

Cited by 14 publications

(13 citation statements)

References 8 publications

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“…This combination is also aimed at collecting valuable information during the hypermutation process, decreasing the number of generations and clones, and, consequently, speeding up the convergence process while reducing the computational time. Belkacemi and Feliachi [22] use a multiagent system (MAS) which follows the human immune system behavior to propose a new technique for power system reconfiguration and restoration, applied to a model of Southern California Edison's Circuit of the Future. Each element of the MAS represents a natural immunological element that interacts with the other elements to heal the body.…”

Section: Ais Applications In Energymentioning

confidence: 99%

“…Each element of the MAS represents a natural immunological element that interacts with the other elements to heal the body. Similarly, the MAS is able to detect and isolate faults and restore power to the affected loads taking into consideration line capacity, voltage profile, and power losses [22]. de Oliveira et al [23] present a methodology for the reconfiguration of radial electrical distribution systems to minimize energy losses making use of the bioinspired metaheuristic artificial immune system.…”

Section: Ais Applications In Energymentioning

confidence: 99%

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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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Section: Ais Applications In Energymentioning

confidence: 99%

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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“…The Tabu Search is a metaheuristic technique developed by Glover [121,122]. This technique aims to emulate the human mind in order to avoid repeating previous configurations or events.…”

Section: Tabu Search (Ts)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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“…(6) can be re-expressed in terms of failure rate and repair rate such that, The unavailability (Q) is sometimes known as Forced Outage Rate (FOR), its converse of the availability and can be defined in similar terms as in Eq. (9) or in terms of failure rate and repair rate as in Eq. (10).…”

Section: The Concept Of Reliability Evaluationmentioning

confidence: 99%

“…The agents employed are the bus and facilitator agents and has been shown a promising approach to more complex large-scale networks. In spite of that, in [9], MAS is employed to resolve the DG configuration and regeneration distribution networks.…”

Section: Introductionmentioning

confidence: 99%

Distributed generation location using multi-agent system for reliability assessment

Shalash

Ahmad

2013

2013 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

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Recently, distributed generation (DG) exploited is predicted to play an important role in the electric power system in term of low cost, security and reliability. In this paper, a new technique for optimize the DG location based on multi agent system (MAS) model for power system reliability evaluation was proposed. The MAS consist of three agents as follows; first agent is a grounding index, which is responsible for adding DG randomly by grounding indices. Second is a reliability evaluation agent that uses a recursive algorithm to predict the suitable generator based on the frequency and duration reliability indices in each state. Third agent is the storage and transfer of data between the other two agents. These agents are created from Malaysia distribution network (DISCO-Net) that implemented by using JADE package software. The simulation results show the effectiveness of proposed multi-agent approach can be taken as a measurement criterion for selecting the best location to add DG in order to improve the power system grounding and reliability.

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Multi-agent design for power distribution system reconfiguration based on the artificial immune system algorithm

Cited by 14 publications

References 8 publications

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

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

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

Distributed generation location using multi-agent system for reliability assessment

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