Transmission System Loadability Enhancement Study by Ordinal Optimization Method

Chang, Yang‐Ming; Chang, Rung-Fang; Hsiao, Tesheng; Lu, Chan‐Nan

doi:10.1109/tpwrs.2010.2049667

Cited by 24 publications

(21 citation statements)

References 23 publications

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“…While in step 4 of the proposed solution algorithm, a particle with the best fitness sharing will instead take the position to guide the swarm into the next generation. And, accordingly, due to that the objective of the MDCP is to maximize the loading factor, with the fitness sharing of each particle calculated by (11), (13) and (14), the gbest in step 4 of the proposed solution algorithm is determined as follows: gbest = the pbest of the particle with the best fitness sharing (15) The setting of σ is determined on a basis of system case-by-case; in the study, with a certain number of simulations, the effects of various σ values to achieve the optimal solution are carefully inspected for the test systems.…”

Section: Proposed Methodologymentioning

confidence: 99%

“…Using the traditional PSO-based method with particle and iteration numbers set to 30 and 1000 respectively, the MDCP under the considered contingency are solved for 1000 trails. In the 1000 trails, it is found that there are only eight solutions with system loadabilities at values of * λ larger than or equal to 0.0651, each of which is considered as a good enough solution and to be capable of the required loadability [15]. The SVC and TCSC installation results of a good enough solution with loadability at 0651 .…”

Section: Taiwan Power Systemmentioning

confidence: 99%

“…While in [15], a crude model was proposed to fast estimate the rough solutions of the MDCP for a set of candidate locations, and then the accurate solutions for a smaller set of candidates selected based on ordinal optimization theory [4] were obtained with the correct method. The best solution in the selected set was taken as the good enough solution for recommendation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fitness Sharing Particle Swarm Optimization Approach to FACTS Installation for Transmission System Loadability Enhancement

Chang¹

2013

Journal of Electrical Engineering and Technology

Self Cite

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-Proper installation of Flexible AC Transmission Systems (FACTS) devices in existing transmission networks can enable power systems to accommodate more power transfer with less network expansion cost. The problem to maximize transmission system loadability by determining optimal locations and settings for installations of two types of FACTS devices, namely static var compensator (SVC) and thyristor controlled series compensator (TCSC), is formulated as a mixed discrete-continuous nonlinear optimization problem (MDCP). For solving the MDCP, in the paper, the proposed method with fitness sharing technique involved in the updating process of the particle swarm optimization (PSO) algorithm, can diversify the particles over the search regions as much as possible, making it possible to achieve the optimal solution with a big probability. The modified IEEE-14 bus network and a practical power system are used to validate the proposed method.

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Section: Proposed Methodologymentioning

confidence: 99%

Section: Taiwan Power Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Fitness Sharing Particle Swarm Optimization Approach to FACTS Installation for Transmission System Loadability Enhancement

Chang¹

2013

Journal of Electrical Engineering and Technology

Self Cite

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“…The OO theory aims to obtain sufficiently good solutions with a high probability instead of finding the perfect optimal solutions to avoid time consuming calculation. The OO theory has been widely used in many aspects such as bidding strategy for electric power suppliers [22], optimal power flow with discrete variables [23], transmission system enhancement [24], reactive optimization in distribution systems [25], etc.…”

Section: Oo Theorymentioning

confidence: 99%

Ordinal Optimization Theory Based Planning for Clustered Wind Farms Considering the Capacity Credit

Wang¹,

Zhang²,

Chen³

et al. 2015

Journal of Electrical Engineering and Technology

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-Wind power planning aims to locate and size wind farms optimally. Traditionally, wind power planners tend to choose the wind farms with the richest wind resources to maximize the energy benefit. However, the capacity benefit of wind power should also be considered in large-scale clustered wind farm planning because the correlation among the wind farms exerts an obvious influence on the capacity benefit brought about by the combined wind power. This paper proposes a planning model considering both the energy and the capacity benefit of the wind farms. The capacity benefit is evaluated by the wind power capacity credit. The Ordinal Optimization (OO) Theory, capable of handling problems with non-analytical forms, is applied to address the model. To verify the feasibility and advantages of the model, the proposed model is compared with a widely used genetic algorithm (GA) via a modified IEEE RTS-79 system and the real world case of Ningxia, China. The results show that the diversity of the wind farm enhances the capacity credit of wind power.

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“…Hence in the recent years, in order to reduce the existing interactions and to promote the performance level of the power systems, the researchers' approach has been directed towards the simultaneous design of FACTS and PSS controllers instruments, some of which to be mentioned are: Static VAR Compensator (SVC), Static Synchronous Series Compensator (SSSC), Static Synchronous Compensator (STATCOM), etc [6][7][8][9].In this paper, simultaneous control of PSS and another product of the FACTS family that is TCSC, have been taken into consideration. Thyristor controlled series compensator (TCSC) as one of the FACTS controllers is used to increase the stability and damping of the oscillations in the power systems [10][11][12]. TCSC can take up different roles in the power system some of which to be mentioned are: power system damping, increasing the transmission capacity from the line, transient stability improvement, fault current limiter and sub-synchronous resonance damping [13].…”

Section: Introductionmentioning

confidence: 99%

Coordinated Control of Flexible AC Transmission System Devices and Power System Stabilizer for improve the Power System Stability Using Fuzzy Adaptive Bacterial Foraging

Khorram¹,

Lesani²

2015

ijeei

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Due to the development of power networks and the ever increasing use of Flexible AC Transmission Systems (FACTS) instruments, the unpredicted interactions have been increased in the power system. Thus, the designing and setting of proper controllers is crucial for the improvement of the dynamic response of a power system along with the FACTS instruments. Because of that in this paper, a new optimization algorithm-based method of Fuzzy Adaptive Bacterial Foraging (FABF) has been used to design the Power System Stabilizer (PSS) and the Thyrist or Controlled Series Capacitor (TCSC) for damping the low frequency oscillations of the power system. The aim of this design is to minimize the deviation of speed and generators terminal voltage in a great range of loads with the use of FABF algorithm. Designing of TCSC and PSS has been both independently and simultaneously performed to confirm the discussed method. The comparison of this method with the Particle Swarm Optimization algorithm (PSO) in the4-machine Kundur system and the10-machine New England system, shows the superiority potential of this method.

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Transmission System Loadability Enhancement Study by Ordinal Optimization Method

Cited by 24 publications

References 23 publications

Fitness Sharing Particle Swarm Optimization Approach to FACTS Installation for Transmission System Loadability Enhancement

Fitness Sharing Particle Swarm Optimization Approach to FACTS Installation for Transmission System Loadability Enhancement

Ordinal Optimization Theory Based Planning for Clustered Wind Farms Considering the Capacity Credit

Coordinated Control of Flexible AC Transmission System Devices and Power System Stabilizer for improve the Power System Stability Using Fuzzy Adaptive Bacterial Foraging

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