Comparison between time-constrained and time-unconstrained optimization for power losses minimization in Smart Grids using genetic algorithms

Storti, Gian Luca; Paschero, Maurizio; Rizzi, Antonello; Mascioli, Fabio Massimo Frattale

doi:10.1016/j.neucom.2015.02.088

Cited by 24 publications

(5 citation statements)

References 25 publications

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“…A GA optimization based demand response control is proposed for grid power balance in peak demand of a building group [292]. Power factor correction (PFC) and distributed feeder reconfiguration (DFR) are optimized through GA in Italian distribution network [293]. GA is used in time constrained and time unconstrained means for minimization of power loss.…”

Section: A Genetic Algorithmmentioning

confidence: 99%

A Critical Analysis of Methodologies for Detection and Classification of Power Quality Events in Smart Grid

et al. 2021

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Recently, power quality (PQ) issues have drawn considerable attention of the researchers due to the increasing awareness of the customers towards power quality. The PQ issues maintain its preeminence because of the significant growth encountered in the smart grid technology, distributed generation, usage of sensitive and power electronic equipments with the integration of renewable energy resources. The IoT and 5G networks technologies have a number of advantages like smart sensor interfacing, remote sensing and monitoring, data transmission at high speed. Due to this, applications of these two are highly adopted in smart grid. The prime focus of the paper is to present an exhaustive survey of detection and classification of power quality disturbances by discussing signal processing techniques and artificial intelligence tools with their respective pros and cons. Further, critical analysis of automatic recognition techniques for the concerned field is posited with the viewpoint of the types of power input signal (synthetic/real/noisy), pre-processing tools, feature selection methods, artificial intelligence techniques and modes of operation (online/offline) as per the reported articles. The present work also elaborates the future scope of the said field for the reader. This paper provides valuable guidelines to the researchers those having interest in the field of PQ analysis and exploring the better methodologies for further improvement. Comprehensive comparisons have been presented with the help of tabular presentations. Although this critical survey cannot be collectively exhaustive, still this survey comprises the most significant works in the concerned paradigm by examining more than 300 research publications.

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Section: A Genetic Algorithmmentioning

confidence: 99%

A Critical Analysis of Methodologies for Detection and Classification of Power Quality Events in Smart Grid

et al. 2021

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“…A study of a real-life scenario at ACEA Distribuzione in Italy was developed by Luca et al in [116] that utilized a GA for the integration of DG units in a small smart grid. It is considered that real networks must be updated constantly; thus, this approach focused on making a comparison between time-constraint (TC) and time-unconstraint (TU) scenarios based on the daily load curve and significant changes in load and PV generation profiles from hour to hour.…”

Section: Genetic Algorithm (Ga)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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“…Their details can be found in the literature. 36,37 In this work, we shall briefly introduce the ABC, PSO, and BBO.…”

Section: Optimization Algorithmmentioning

confidence: 99%

Multi-objective path finding in stochastic networks using a biogeography-based optimization method

Wang

Yang

et al. 2016

SIMULATION

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Multi-objective path finding (MOPF) problems are widely applied in both academic and industrial areas. In order to deal with the MOPF problem more effectively, we propose a novel model that can cope with both deterministic and random variables. For the experiment, we compared five intelligence-optimization algorithms: the genetic algorithm, artificial bee colony (ABC), ant colony optimization (ACO), biogeography-based optimization (BBO), and particle swarm optimization (PSO). After a 100-run comparison, we found the BBO is superior to the other four algorithms with regard to success rate. Therefore, the BBO is effective in MOPF problems.

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Comparison between time-constrained and time-unconstrained optimization for power losses minimization in Smart Grids using genetic algorithms

Cited by 24 publications

References 25 publications

A Critical Analysis of Methodologies for Detection and Classification of Power Quality Events in Smart Grid

A Critical Analysis of Methodologies for Detection and Classification of Power Quality Events in Smart Grid

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

Multi-objective path finding in stochastic networks using a biogeography-based optimization method

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