A particle swarm optimization based power dispatch algorithm with roulette wheel re-distribution mechanism for equality constraint

Cheng, Yu-Shan; Chuang, Man-Tsai; Liu, Yi‐Hua; Wang, Shun‐Chung; Yang, Zong‐Zhen

doi:10.1016/j.renene.2015.11.023

Cited by 32 publications

(22 citation statements)

References 36 publications

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“…Generally, it is not a prerequisite to always generate an initial individual that fully satisfy the constraints. Individuals that cannot meet with all the constraints can be later assigned with the worst fitness, and then can be eliminated throughout by elitism and roulette wheel selection (Cheng, Chuang, Liu, Wang, & Yang, 2016). Besides, these worst individuals have the opportunity to be improved through crossover and mutation.…”

Section: Initial Population Generationmentioning

confidence: 99%

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An efficient genetic algorithm for large-scale planning of dense and robust industrial wireless networks

Gong

David

Tanghe

et al. 2018

Expert Systems with Applications

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An industrial indoor environment is harsh for wireless communications compared to an office environment, because the prevalent metal easily causes shadowing effects and affects the availability of an industrial wireless local area network (IWLAN). On the one hand, it is costly, time-consuming, and ineffective to perform trial-and-error manual deployment of wireless nodes. On the other hand, the existing wireless planning tools only focus on office environments such that it is hard to plan IWLANs due to the larger problem size and the deployed IWLANs are vulnerable to prevalent shadowing effects in harsh industrial indoor environments. To fill this gap, this paper proposes an overdimensioning model and a genetic algorithm based over-dimensioning (GAOD) algorithm for deploying large-scale robust IWLANs. As a progress beyond the state-of-the-art wireless planning, two full coverage layers are created. The second coverage layer serves as redundancy in case of shadowing. Meanwhile, the deployment cost is reduced by minimizing the number of access points (APs); the hard constraint of minimal inter-AP spatial separation avoids multiple APs covering the same area to be simultaneously shadowed by the same obstacle. The computation time and occupied memory are dedicatedly considered in the design of GAOD for large-scale optimization. A greedy heuristic based over-dimensioning (GHOD) algorithm and a random OD algorithm are taken as benchmarks. In two vehicle manufacturers with a small and large indoor environment, GAOD outperformed GHOD with up to 20% less APs, while GHOD outputted up to 25% less APs than a random OD algorithm. Furthermore, the effectiveness of this model and GAOD was experimentally validated with a real deployment system.

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Section: Initial Population Generationmentioning

confidence: 99%

“…The crossover operation is defined by Algorithm 3. The input is two qualified individuals (i.e., indiv1 and indiv2 in Algorithm 3), which are selected by the roulette wheel selection algorithm (Cheng, et al, 2016).…”

Section: Crossovermentioning

confidence: 99%

An efficient genetic algorithm for large-scale planning of dense and robust industrial wireless networks

Gong

David

Tanghe

et al. 2018

Expert Systems with Applications

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“…Garcia et al [18,19] proposed an intelligent energy management system to determine the power sharing between the hydrogen and battery storage based on operating costs in the hybrid standalone system and yielded better results as against the simple state-based energy management strategies. Cheng et al [20] used PSO with roulette wheel redistribution mechanism to include power balance equality constraints in the energy management strategy. The energy management strategy considers the effects of depth of discharge of the battery storage and enables extending longevity by penalizing charging and discharging based on SOC levels.…”

Section: Esss For Energy Management Of Dgsmentioning

confidence: 99%

Energy Storage Systems for Energy Management of Renewables in Distributed Generation Systems

Fathima¹,

Palanisamy²

2016

Energy Management of Distributed Generation Systems

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Distributed generation (DG) systems are the key for implementation of micro/smart grids of today, and energy storages are becoming an integral part of such systems. Advancement in technology now ensures power storage and delivery from few seconds to days/ months. But an effective management of the distributed energy resources and its storage systems is essential to ensure efficient operation and long service life. This chapter presents the issues faced in integrating renewables in DG and the growing necessity of energy storages. Types of energy storage systems (ESSs) and their applications have also been detailed. A brief literature study on energy management of ESSs in distributed microgrids has also been included. This is followed by a simple case study to illustrate the need and effect of management of ESSs in distributed systems.

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“…The result is acceptable. The roulette redistribution mechanism is proposed in [5] with the power distribution algorithm based on the PSO (Particle Swarm Optimization). The proposed method improves the efficiency of 0.82% to 1.76% of system.…”

Section: Introductionmentioning

confidence: 99%

Supervision of a PV system with storage connected to the power line and design of a battery protection system

et al. 2018

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This work presents the supervision strategy in an Arduino card PV generator with storage connected to the low voltage grid. The studied system is composed of a photovoltaic generator, a boost converter, a buck-boost converter and a singlephase inverter. The power of the PV module depends on atmospheric conditions. Batteries are often confronted with overload problems and underload. The objective of this article is to manage the charging and discharging of the batteries, taking into account their protection against overload and under load and supervise the system. For this, supervision algorithms implemented in Arduino developed. Simulation results under Matlab show that the Arduino board has ensured the protection of the batteries and system supervision.

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A particle swarm optimization based power dispatch algorithm with roulette wheel re-distribution mechanism for equality constraint

Cited by 32 publications

References 36 publications

An efficient genetic algorithm for large-scale planning of dense and robust industrial wireless networks

An efficient genetic algorithm for large-scale planning of dense and robust industrial wireless networks

Energy Storage Systems for Energy Management of Renewables in Distributed Generation Systems

Supervision of a PV system with storage connected to the power line and design of a battery protection system

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