Optimal generation share based dynamic available transfer capability improvement in deregulated electricity market

Srinivasan, Aravind; Venkatesh, P.; Dineshkumar, B.

doi:10.1016/j.ijepes.2013.07.003

Cited by 13 publications

(8 citation statements)

References 24 publications

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“…Many researchers 4‐15 considered two margins such as TRM and CBM as zero in DATC evaluation to reduce the computational complexity. But this leads to inaccurate DATC which place system in danger condition at emergency.…”

Section: Transmission Capacity Margins Calculationmentioning

confidence: 99%

See 1 more Smart Citation

Day ahead dynamic available transfer capability evaluation incorporating probabilistic transmission capacity margins in presence of wind generators

Karuppasamypandiyan

Jeyanthy

Devaraj

et al. 2020

Int Trans Electr Energ Syst

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Section: Transmission Capacity Margins Calculationmentioning

confidence: 99%

“…In References 4‐8, the authors proposed some classical algorithms for calculation of ATC. Some meta‐heuristic algorithms are also proposed by many researchers 9‐12 which give better results compared with classical optimization algorithm. Researchers also proposed 13‐16 machine learning‐based algorithms to estimate the ATC.…”

Section: Introductionmentioning

confidence: 99%

Day ahead dynamic available transfer capability evaluation incorporating probabilistic transmission capacity margins in presence of wind generators

Karuppasamypandiyan

Jeyanthy

Devaraj

et al. 2020

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

“…ATC evaluation techniques in the literature can be classified as: continuation power flow (CPF)-based methods [11,12], optimal power flow (OPF)-based techniques [13,14], DC power transfer distribution factor (PTDF)-based methods [15][16][17], ACPTDF/line outage distribution factor (LODF)-based approaches [10,18,19] and machine learning (ML)-based methods such as artificial neural network, genetic algorithm and so on [20][21][22]. CPF-based methods use repeated AC power flow (ACPF) while OPF-based techniques consider the equality and inequality constraints along with the nonlinear model of the system for ATC determination.…”

Section: Introductionmentioning

confidence: 99%

Synchrophasor measurement‐based approach for online available transfer capability evaluation

Kesherwani

Srivastava

Mohapatra

2019

IET Generation, Transmission & Distribution

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“…Here, selling and buying of electrical energy are performed by the market participants to maximize the yield and to minimize the total cost incurred for rescheduling. Meanwhile, established contract is committed only if adequate available transfer capability (ATC) is accessible for interface (Srinivasan et al , 2014). Generally, ATC (Nireekshana et al , 2016) plays a significant role in providing the information of power transfer that is used as a reference by the participants for requesting least price of electricity trading in deregulated system.…”

Section: Introductionmentioning

confidence: 99%

Adaptive whale optimization for intelligent multi-constraints power quality improvement under deregulated environment

Thakur

Awasthi

Hooda

et al. 2019

JEDT

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Purpose Power quality issues highly affect the secure and economic operations of the power system. Although numerous methodologies are reported in the literature, flexible alternating current transmission system (FACTS) devices play a primary role. However, the FACTS devices require optimal location and sizing to perform the power quality enhancement effectively and in a cost efficient manner. This paper aims to attain the maximum power quality improvements in IEEE 30 and IEEE 57 test bus systems. Design/methodology/approach This paper contributes the adaptive whale optimization algorithm (AWOA) algorithm to solve the power quality issues under deregulated sector, which enhances available transfer capability, maintains voltage stability, minimizes loss and mitigates congestions. Findings Through the performance analysis, the convergence of the final fitness of AWOA algorithm is 5 per cent better than artificial bee colony (ABC), 3.79 per cent better than genetic algorithm (GA), 2,081 per cent better than particle swarm optimization (PSO) and fire fly (FF) and 2.56 per cent better than whale optimization algorithm (WOA) algorithms at 400 per cent load condition for IEEE 30 test bus system, and the fitness convergence of AWOA algorithm for IEEE 57 test bus system is 4.44, 4.86, 5.49, 7.52 and 9.66 per cent better than FF, ABC, WOA, PSO and GA, respectively. Originality/value This paper presents a technique for minimizing the power quality problems using AWOA algorithm. This is the first work to use WOA-based optimization for the power quality improvements.

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Optimal generation share based dynamic available transfer capability improvement in deregulated electricity market

Cited by 13 publications

References 24 publications

Day ahead dynamic available transfer capability evaluation incorporating probabilistic transmission capacity margins in presence of wind generators

Day ahead dynamic available transfer capability evaluation incorporating probabilistic transmission capacity margins in presence of wind generators

Synchrophasor measurement‐based approach for online available transfer capability evaluation

Adaptive whale optimization for intelligent multi-constraints power quality improvement under deregulated environment

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