A new hybrid evolutionary algorithm based on new fuzzy adaptive PSO and NM algorithms for Distribution Feeder Reconfiguration

Niknam, Taher; Azad‐Farsani, Ehsan; Jabbari, Masoud

doi:10.1016/j.enconman.2011.09.014

Cited by 70 publications

(25 citation statements)

References 27 publications

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“…The results showed that with volt/var control by shunt capacitor, on-load tap changer, voltage regulator, and feeder reconfiguration, DG injection can be maximized. Similar works are presented in [48] and [49].…”

Section: Particle Swarm Optimization (Pso)supporting

confidence: 63%

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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Section: Particle Swarm Optimization (Pso)supporting

confidence: 63%

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

Quintero-Duran

Candelo-Becerra

Sousa

2017

JESTR

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“…Reconfiguration of radial distribution networks is a viable option for ensuring optimal or nearly optimal operation in the presence of several constraints and variable power demand [7,16,[18][19][20][21][22]35]. From a theoretical perspective, distribution networks can always be reconfigured whenever imminent loading variations are detected.…”

Section: Introductionmentioning

confidence: 99%

Robust feeder reconfiguration in radial distribution networks

Barbosa

Mendes

Vasconcelos

2014

International Journal of Electrical Power & Energy Systems

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a b s t r a c tDistribution feeder reconfiguration has been an active field of research for many years. Some recent theoretical studies have highlighted the importance of smart reconfiguration for the operating conditions of such radial networks. In general, this problem has been tackled using a multi-objective formulation with simplified assumptions, in which the uncertainties related to network components have been neglected by both mathematical models and solution techniques. These simplifications guide searches to apparent optima that may not perform optimally under realistic conditions. To circumvent this problem, we propose a method capable of performing interval computations and consider seasonal variability in load demands to identify robust configurations, which are those that have the best performance in the worst case scenario. Our proposal, named the Interval Multi-objective Evolutionary Algorithm for Distribution Feeder Reconfiguration (IMOEA-DFR), uses interval analysis to perform configuration assessment by considering the uncertainties in the power demanded by customers. Simulations performed in three cases on a 70-busbar system demonstrated the effectiveness of the IMOEA-DFR, which obtained robust configurations that are capable to keep such system working under significant load variations. Moreover, our approach achieved stable configurations that remained feasible over long periods of time not requiring additional reconfigurations. Our results reinforce the need to include load uncertainties when analyzing DFR under realistic conditions.

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“…The PSO algorithm is an evolutionary algorithm first proposed by Kennedy and Eberhart [19,20]. It is used for solving the nonlinear mixed integer and the complex optimization problem [21][22][23][24][25]. The performance of the PSO algorithm is highly dependent on its parameters such as inertia weight and learning factors.…”

Section: Literature Reviewmentioning

confidence: 99%

Placement of Combined Heat, Power and Hydrogen Production Fuel Cell Power Plants in a Distribution Network

Farjah¹,

Bornapour

Niknam

2012

Energies

Self Cite

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This paper presents a new Fuzzy Adaptive Modified Particle Swarm Optimization algorithm (FAMPSO) for the placement of Fuel Cell Power Plants (FCPPs) in distribution systems. FCPPs, as Distributed Generation (DG) units, can be considered as Combined sources of Heat, Power, and Hydrogen (CHPH). CHPH operation of FCPPs can improve overall system efficiency, as well as produce hydrogen which can be stored for the future use of FCPPs or can be sold for profit. The objective functions investigated are minimizing the operating costs of electrical energy generation of distribution substations and FCPPs, minimizing the voltage deviation and minimizing the total emission. In this regard, this paper just considers the placement of CHPH FCPPs while investment cost of devices is not considered. Considering the fact that the objectives are different, non-commensurable and nonlinear, it is difficult to solve the problem using conventional approaches that may optimize a single objective. Moreover, the placement of FCPPs in distribution systems is a mixed integer problem. Therefore, this paper uses the FAMPSO algorithm to overcome these problems. For solving the proposed multi-objective problem, this paper utilizes the Pareto Optimality idea to obtain a set of solution in the multi-objective problem instead of only one. Also, a fuzzy system is used to tune parameters of FAMPSO algorithm such as inertia weight. The efficacy of the proposed approach is validated on a 69-bus distribution system. OPEN ACCESS

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A new hybrid evolutionary algorithm based on new fuzzy adaptive PSO and NM algorithms for Distribution Feeder Reconfiguration

Cited by 70 publications

References 27 publications

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

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

Robust feeder reconfiguration in radial distribution networks

Placement of Combined Heat, Power and Hydrogen Production Fuel Cell Power Plants in a Distribution Network

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