An efficient particle swarm optimization algorithm to solve optimal power flow problem integrated with FACTS devices

Naderi, Ehsan; Pourakbari‐Kasmaei, Mahdi; Abdi, Hamdi

doi:10.1016/j.asoc.2019.04.012

Cited by 147 publications

(72 citation statements)

References 63 publications

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“…It is a multi-agent search technique that has evolved from the emergent motion of a flock of birds searching for food. This technique has been widely used for optimization problems in power system applications [22]- [27]. For example, in [26], PSO was utilized to optimize combined heat and power system.…”

Section: Proposed Loss Minimization Methods a Particle Swarm Optimentioning

confidence: 99%

“…For example, in [26], PSO was utilized to optimize combined heat and power system. Also, in [27], the algorithm was exploited to operate thyristor-controlled series capacitor (TCSC). In the implementation of the PSO algorithm, the position vector (P m ) and velocity vector (U m ) should be first defined at the current step (m).…”

Section: Proposed Loss Minimization Methods a Particle Swarm Optimentioning

confidence: 99%

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Loss Minimization of Electrified Railway Traction Systems Using SVC Based on Particle Swarm Optimization

et al. 2020

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Section: Proposed Loss Minimization Methods a Particle Swarm Optimentioning

confidence: 99%

Section: Proposed Loss Minimization Methods a Particle Swarm Optimentioning

confidence: 99%

Loss Minimization of Electrified Railway Traction Systems Using SVC Based on Particle Swarm Optimization

et al. 2020

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“…Valve-point effects occurs in the work of power-only units. It refers to the phenomenon that when the valve suddenly opens, steam loss leads to increased consumption and superimposes unit consumption curve and pulsation effect [5], which is described in Fig.1 [27]: As shown in Fig.1, Min and Max are the lower upper limits of the power-only unit capacity. The change function of consumption characteristics of traditional units caused by valve-point effects is | sin{ ( − )}| , where represents the real power output of the ith unit, represents the lower limit of the power output of the ith unit, and are the cost change coefficients of the ith power-only unit.…”

Section: Fuel Costsmentioning

confidence: 99%

Indicator & crowding distance-based evolutionary algorithm for combined heat and power economic emission dispatch

Sun

Deng

2020

Applied Soft Computing

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Heat and power have become the most indispensable resources. However, the traditional ways of generating power and heat are inefficient and cause high pollution; a CHP (Combined Heat and Power) unit can solve these problems well. In recent years, more attention has been paid to energy conservation and environmental protection, and Combined Heat and Power Economic Emission Dispatch (CHPEED) has become an important multi-objective optimization problem. In this paper, an Indicator & crowding Distance-based Evolutionary Algorithm (IDBEA) is put forward for handling this non-convex and non-linear problem. With consideration of the valve-point effects and power transmission loss, IDBEA is tested on three standard test systems with different types, including four units, five units and seven units. In the experiment, IDBEA is compared with several evolutionary algorithms, the simulation results demonstrate that IDBEA has strong stability and superiority, while the solutions show better convergence and diversity than several typical algorithms.

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“…However, optimal allocation of the FACTS and setting their control variables poses a complex constraint optimization problem. Furthermore, such optimization has considerable influence on the effectiveness in system performance, by providing loss reduction, voltage profile improvement, network load ability enhancement, increased voltage stability and fuel cost reduction through optimal power flow 9 – 12 .…”

Section: Introductionmentioning

confidence: 99%

Design of fractional evolutionary processing for reactive power planning with FACTS devices

Yasir

Akhtar

Khan

et al. 2021

Sci Rep

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Reactive power dispatch is a vital problem in the operation, planning and control of power system for obtaining a fixed economic load expedition. An optimal dispatch reduces the grid congestion through the minimization of the active power loss. This strategy involves adjusting the transformer tap settings, generator voltages and reactive power sources, such as flexible alternating current transmission systems (FACTS). The optimal dispatch improves the system security, voltage profile, power transfer capability and overall network efficiency. In the present work, a fractional evolutionary approach achieves the desired objectives of reactive power planning by incorporating FACTS devices. Two compensation arrangements are possible: the shunt type compensation, through Static Var compensator (SVC) and the series compensation through the Thyristor controlled series compensator (TCSC). The fractional order Darwinian Particle Swarm Optimization (FO-DPSO) is implemented on the standard IEEE 30, IEEE 57 and IEEE 118 bus test systems. The power flow analysis is used for determining the location of TCSC, while the voltage collapse proximity indication (VCPI) method identifies the location of the SVC. The superiority of the FO-DPSO is demonstrated by comparing the results with those obtained by other techniques in terms of measure of central tendency, variation indices and time complexity.

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An efficient particle swarm optimization algorithm to solve optimal power flow problem integrated with FACTS devices

Cited by 147 publications

References 63 publications

Loss Minimization of Electrified Railway Traction Systems Using SVC Based on Particle Swarm Optimization

Loss Minimization of Electrified Railway Traction Systems Using SVC Based on Particle Swarm Optimization

Indicator & crowding distance-based evolutionary algorithm for combined heat and power economic emission dispatch

Design of fractional evolutionary processing for reactive power planning with FACTS devices

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