Optimal rescheduling of real power to mitigate congestion using gravitationalsearch algorithm

Paul, Kaushik; Kumar, Niranjan; Agrawal, Saligram; Paul, Kamalendu

doi:10.3906/elk-1708-91

Cited by 16 publications

(6 citation statements)

References 25 publications

(77 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This paper interprets the saving in cost yielded by optimal use of PHSU when operated during peak demand and thermal usage during off-peak demand [24]. The superiority of PHSU elevated the efficiency in energy transaction [25][26][27]. FPA and its variants have been developed in recent years which are found to yield better efficient outputs in applications for optimization designing due to its single probability switching parameter [28].…”

Section: Introductionmentioning

confidence: 93%

Rescheduling of Generators with Pumped Hydro Storage Units to Relieve Congestion Incorporating Flower Pollination Optimization

et al. 2019

View full text Add to dashboard Cite

In this paper, a Flower Pollination Algorithm (FPA) has been proposed for relieving congestion in the deregulated power electricity industry. Congestion in the power market is one the contemplative challenges to be overcome in the era of deregulation. The primary cause of congestion is due to the loss of the transmission line, an increase in load, or loss of generator(s). Hence, managing congestion is one of the issues which have to be tackled in the present scenario. There are several techniques to relieve congestion. It is quite well-known that the thermal limits of transmission lines in a power system are fixed. One of the methods to abate congestion is to reschedule the real power of the generators. The purpose of the present work is to benefit the Independent System Operator (ISO) in reliving congestion. (1) In order to meet this objective effectively, a FPA algorithm has been proposed for relieving congestion and is simulated on a modified IEEE 30-bus system initially. (2) Congestion cost, compared with and without the application of FPA, is computed. (3) To validate its effectiveness, the obtained results are compared with recent power system optimization algorithms present in the literature. (4) Further, the work has been extended with the incorporation of a Pumped Hydro Storage Unit (PHSU). Here an economic analysis of congestion cost reduction employing FPA before and after the incorporation of PHSU is investigated applying FPA. In comparison with other evolutionary algorithms, the uniqueness of generating a new population is attained in FPA by the levy flight procedure. It is one of the latest evolved algorithms and is suited for different power system problem due to fewer clear-cut tuning parameters in contrast with other algorithms. (5) Furthermore, the effects of other network parameters, including system losses and voltage, has been computed. The result obtained is tested in terms of congestion mitigation with and without the incorporation of PHSU, in terms of novel objective improvement, and with and without applying recently evolving FPA for the above application. Thus the objective-wise and algorithmic-wise innovative concept has been presented. This proves effectiveness of the algorithm in terms of minimized cost convergence and other parameter including system losses and voltage before and after the incorporation of PHSU as compared with other recent trendsetting reported optimization techniques.

show abstract

Section: Introductionmentioning

confidence: 93%

Rescheduling of Generators with Pumped Hydro Storage Units to Relieve Congestion Incorporating Flower Pollination Optimization

et al. 2019

View full text Add to dashboard Cite

show abstract

“…An optimal rescheduling of real power to mitigate congestion with the incorporation of wind farms using gravitational search algorithm (GSA) in deregulated environment was demonstrated by Paul et al (2017). This approach uses the GSA to reduce the active power yield.…”

Section: Review Of Related Workmentioning

confidence: 99%

Congestion management in deregulated power system using adaptive moth swarm optimization

Ramaporselvi¹,

Geetha²

2021

COMPEL

View full text Add to dashboard Cite

Purpose The purpose of this paper is to enhance the line congestion and to minimize power loss. Transmission line congestion is considered the most acute trouble during the operation of the power system. Therefore, congestion management acts as an effective tool in using the available power without breaking the system hindrances or limitations. Design/methodology/approach Over the past few years, determining the optimal location and size of the devices have pinched a great deal of consideration. Numerous approaches have been established to mitigate the congestion rate, and this paper aims to enhance the line congestion and minimize power loss by determining the compensation rate and optimal location of a thyristor-switched capacitor (TCSC) using adaptive moth swarm optimization (AMSO) algorithm. Findings An AMSO algorithm uses the performances of moth flame and the chaotic local search-based shrinking scheme of the bacterial foraging optimization algorithm. The proposed AMSO approach is executed and discussed for the IEEE-30 bus system for determining the optimal location of single TCSC and dual TCSC. Originality/value In addition to this, the proposed algorithm is compared with various other existing approaches, and the results thus obtained provide better performances than other techniques.

show abstract

“…An optimal rescheduling of real power to mitigate congestion with incorporation of wind farm using gravitational search algorithm in deregulated environment was demonstrated by Paul et al [14].This approach utilizes the Gravitational search algorithm (GSA) to reduce the active power yield. The parameters employed for evaluation are rescheduling cost, sensitivity factor, and power loss.…”

Section: Literature Reviewmentioning

confidence: 99%

Congestion Management in Deregulated Power System using Adaptive Moth Swarm Optimization

Ramaporselvi

Geetha

2021

Preprint

View full text Add to dashboard Cite

Transmission line congestion is considered the most acute trouble during the operation of the power system. Therefore, congestion management acts as an effective tool in utilizing the available power without breaking the system hindrances or limitations. Over the past few years, determining an optimal location and size of the devices have pinched a great deal of consideration. Numerous approaches have been established to mitigate the congestion rate and this paper aims to enhance the line congestion and minimize power loss by determining the compensation rate and optimal location of thyristor-controlled series capacitor (TCSC) using adaptive moth swarm optimization (AMSO) algorithm. An adaptive moth swarm AMSO algorithm utilizes the performances of moth flame and chaotic local search-based shrinking scheme of the bacterial foraging optimization algorithm. The proposed AMSO approach is executed and discussed for IEEE-30 bus system for determining the optimal location of single TCSC and dual TCSC. In addition to this, the proposed algorithm is compared with various other existing approaches and the results thus obtained provide better performances when compared with other techniques.

show abstract

Optimal rescheduling of real power to mitigate congestion using gravitationalsearch algorithm

Cited by 16 publications

References 25 publications

Rescheduling of Generators with Pumped Hydro Storage Units to Relieve Congestion Incorporating Flower Pollination Optimization

Rescheduling of Generators with Pumped Hydro Storage Units to Relieve Congestion Incorporating Flower Pollination Optimization

Congestion management in deregulated power system using adaptive moth swarm optimization

Congestion Management in Deregulated Power System using Adaptive Moth Swarm Optimization

Contact Info

Product

Resources

About