An efficient artificial immune algorithm for power system reliability optimisation

Rami, Abdelkader; Zeblah, Abdelkader; Hamdaoui, Habib; Massim, Y.; Harrou, Fouzi

doi:10.1504/ijpec.2009.027943

Cited by 7 publications

(8 citation statements)

References 51 publications

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“…With less than four references per application, PHC technologies have been used in dynamic state estimation [94,200,201], power system planning [236,237], TSCOPF [230,231], power system reliability [238,239], electromagnetic transient simulation [91,92], dynamic models [2,216], short circuit analysis [235], security constrained economic dispatch [242], probabilistic power flow [224], and hydro thermal scheduling [243]. In ref.…”

Section: Other Applicationsmentioning

confidence: 99%

A Review of Parallel Heterogeneous Computing Algorithms in Power Systems

et al. 2021

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The power system expansion and the integration of technologies, such as renewable generation, distributed generation, high voltage direct current, and energy storage, have made power system simulation challenging in multiple applications. The current computing platforms employed for planning, operation, studies, visualization, and the analysis of power systems are reaching their operational limit since the complexity and size of modern power systems results in long simulation times and high computational demand. Time reductions in simulation and analysis lead to the better and further optimized performance of power systems. Heterogeneous computing—where different processing units interact—has shown that power system applications can take advantage of the unique strengths of each type of processing unit, such as central processing units, graphics processing units, and field-programmable gate arrays interacting in on-premise or cloud environments. Parallel Heterogeneous Computing appears as an alternative to reduce simulation times by optimizing multitask execution in parallel computing architectures with different processing units working together. This paper presents a review of Parallel Heterogeneous Computing techniques, how these techniques have been applied in a wide variety of power system applications, how they help reduce the computational time of modern power system simulation and analysis, and the current tendency regarding each application. We present a wide variety of approaches classified by technique and application.

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Section: Other Applicationsmentioning

confidence: 99%

A Review of Parallel Heterogeneous Computing Algorithms in Power Systems

et al. 2021

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“…The comparisons between the best solution of firefly algorithm (FA) and the best solutions obtained by the methods in references [5,6,7,8,9,10,30] are provided in Table 3. Note that in these references the proposed algorithm is of a stochastic nature.…”

Section: B Execution and Firefly Algorithm Parametersmentioning

confidence: 99%

“…The firefly algorithm on the redundancy optimization problem (ROP) for a multi-state system (MSS) with heterogeneous redundancy generally yields better solutions with a lower cost and reasonable reliability than the other algorithms. We take, for example, for reliability level (A 0 = 0.975) the solutions found by all algorithms are better than those by Tabu search [9], for another example the reliability level (A 0 = 0.98) the solutions found by all algorithms are better than those by HS [7], IA [10] and TS [9].…”

Section: B Execution and Firefly Algorithm Parametersmentioning

confidence: 99%

“…The ROP for the multi-state reliability was introduced in [3,4,5]. Many meta-heuristic were used such as: Genetic Algorithms [5], Particles Swarm Optimization and Local Search [6], Harmony Search [7], Ant Colony Optimization [8], Tabu Search [9] and Immune Algorithm [10].…”

Section: Introductionmentioning

confidence: 99%

“…To evaluate the reliability for series-parallel system structure, we develop a procedure which is based on universal moment generating function (UMGF) [3]. An approach to model the redundancy optimization problem is suggested in [4][5][6][7][8][9][10][11][12]. In this approach costs of components are defined as explicit analytical function of component capacities and the same reliability index value is assigned to all components of a given type, regardless of their capacity.…”

Section: Introductionmentioning

confidence: 99%

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Series-Parallel Power System Optimization Using Firefly Algorithm

Guerraiche¹,

Rahli²,

Zeblah³

et al. 2015

ijeei

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In this paper, we try to solve the Redundancy Optimization Problem (ROP) using a recent bio-inspired meta-heuristic that is Firefly Algorithm (FA) combined to Universal Moment Generating Function (UMGF).The problem consists on selecting the appropriate components from a multi-state system (MSS) given the minimum cost. The solution must also fulfill a system reliability constraint. The reliability in our work is considered as the ability to satisfy the demand and is calculated using u-tranform technique. Our algorithm was tested on a system contained multiple choices of five subsystems from a list of product available in the market. The components of each subsystem are characterized by their cost, performance (capacity) and availability. The results obtained by the proposed algorithm are compared with several algorithm founds in literature.

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A human–computer cooperative particle swarm optimization based immune algorithm for layout design

Zhao

Yang

et al. 2014

Neurocomputing

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An efficient artificial immune algorithm for power system reliability optimisation

Cited by 7 publications

References 51 publications

A Review of Parallel Heterogeneous Computing Algorithms in Power Systems

A Review of Parallel Heterogeneous Computing Algorithms in Power Systems

Series-Parallel Power System Optimization Using Firefly Algorithm

A human–computer cooperative particle swarm optimization based immune algorithm for layout design

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