Economic dispatch incorporating wind energy by BH, BBO and DE

Hasan, Zakareya; El-Hawary, M.E.

doi:10.1109/ccece.2016.7726767

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…Apart from RL, another type of optimization technique, called metaheuristic methods, also showed competitive performance in solving the nonconvex ED problem. These include grey wolf optimization (GWO; Kumar and Babu, 2021), artificial bee colony (ABC; Secui, 2015), biogeography-based optimization (BBO; Hasan and El-Hawary, 2016), differential evolution (DE; Sheta et al, 2020), artificial immune system (AIS; Chiang, 2020), and genetic algorithm (GA; Zou et al, 2019). However, the no free launch theorems in optimization (Wolpert and Macready, 1997) indicate that no single optimization tool can perform equally well on all problems.…”

Section: Introductionmentioning

confidence: 99%

A diversity-based parallel particle swarm optimization for nonconvex economic dispatch problem

Xin

Wang

et al. 2022

Transactions of the Institute of Measurement and Control

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The economic dispatch (ED) problem aims to minimize the total generation cost while satisfying certain constraints, such as valve-point effects, multi-fuel options, prohibited operating zones, transmission losses, and ramp rate limits. In this paper, these constraints are considered simultaneously for the first time, resulting in a complex nonconvex ED problem. A diversity-based parallel particle swarm optimization (DPPSO) is proposed to solve the nonconvex ED problem, where the implementation details—such as evaluation function design, particle definition, and equality and inequality handling strategies—have been carefully discussed. In our approach, the population of DPPSO is divided into different groups to maintain diversity in particles so that the optimization capacity can be enhanced. An asynchronous information–sharing mechanism (AISM) helps decrease the population size. Hence, the computational burden is reduced. Moreover, information in different groups is calculated parallelly and updated asynchronously to improve computational efficiency. Benchmark functions are employed to demonstrate the effectiveness of the proposed method. Furthermore, three nonconvex ED problems are resolved by the proposed method, and state-of-the-art performance has been achieved. In addition, the proposed algorithm is highly modular, making it easy to unite other salient variants of particle swarm optimization (PSO) to improve its performance.

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Section: Introductionmentioning

confidence: 99%

A diversity-based parallel particle swarm optimization for nonconvex economic dispatch problem

Xin

Wang

et al. 2022

Transactions of the Institute of Measurement and Control

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show abstract

“…This condition forces to explore potential primary energy sources, such as wind, solar and others. Technically, the renewable energy integration (REI) is depended on applied current technologies and role on the power penetration [6][7][8][9][10]. Recently, this mitigation becomes one of the most issues in the energy procurement for providing power outputs of the alternative generating system.…”

Section: Introductionmentioning

confidence: 99%

Renewable Energy Inclusion on Economic Power Optimization using Thunderstorm Algorithm

Afandi¹,

Fujita²,

Sulistyorini³

et al. 2017

EECSI

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This paper presents an economic operation considered renewable energy which is optimized using thunderstorm algorithm. The problem is constrained by an emission standard and various technical limits implemented on the 62-bus system model. Simulations showed that the renewable energy inclusion penetrates to the unit commitment of generating units with strongly approach for the computational solution. This inclusion also affects to the individual power production in accordance to the fuel cost and pollutant discharge.

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Renewable energy inclusion on economic power optimization using thunderstorm algorithm

Afandi

Sulistyorini

Fujita

et al. 2017

2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)

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Economic dispatch incorporating wind energy by BH, BBO and DE

Cited by 5 publications

References 15 publications

A diversity-based parallel particle swarm optimization for nonconvex economic dispatch problem

A diversity-based parallel particle swarm optimization for nonconvex economic dispatch problem

Renewable Energy Inclusion on Economic Power Optimization using Thunderstorm Algorithm

Renewable energy inclusion on economic power optimization using thunderstorm algorithm

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