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International Conference on Swarm, Evolutionary, and Memetic Computing

SEMCCO 2014: Swarm, Evolutionary, and Memetic Computing pp 396–408Cite as

A Novel Method of Relieving Transmission Congestion by Optimal Rescheduling with Multiple DGs Using PSO

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8947))

Abstract

Congestion management is one of the most important issues for secure and reliable system operations in deregulated electricity market. Rescheduling the real power output of generators in the system is the most practiced technique for congestion management. In this research, multiple distributed generators are connected optimally along with above said conventional method to alleviate congestion. Particle Swarm Optimization (PSO) is used to determine the optimal generation levels and for finding the optimal sizes of multiple DGs, both PSO and GA are used to alleviate transmission congestion. Numerical results on modified IEEE 30 bus system is experimented for illustration. The complete experimental outcomes demonstrate that the PSO is one among the demanding optimization methods for this proposed problem than GA.

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Abbreviations

DG:

- Distributed Generation

LFSF:

- Line Flow Sensitivity Factor

FACTS:

- Flexible AC Transmission Systems

RED:

- Relative Electrical Distance

FABF:

- Fuzzy Adaptive Bacterial Foraging

TCSC:

- Thyristor Controlled Series Compensation

PI:

- Real power flow performance index

\( \Delta P_{l} \) :

- Change in real power injection at l th node

\( \Delta Q_{l} \) :

- Change in reactive power injection at l th node

\( \Delta S_{ij} \) :

- Change in line flow between node i and j

\( S_{ij} \) :

- Line flow between node i and j

\( P_{l} \) :

- Real power injection at l th node

\( Q_{l} \) :

- Reactive power injection at l th node

\( P_{g} \) :

- Power generated from generators in MW

\( P_{d} \) :

- Power demand in MW

\( ng \) :

- Total number of generators available in the system

\( nl \) :

- Total number of lines available in the system

References

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Kamaraj College of Engineering and Technology, Virudhunagar, 626 001, TamilNadu, India

    K. Muthulakshmi

  2. Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Madurai, 625 015, TamilNadu, India

    C. K. Babulal

Authors
  1. K. Muthulakshmi
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  2. C. K. Babulal
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Corresponding author

Correspondence to K. Muthulakshmi .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, IIT, New Delhi, India

    Bijaya Ketan Panigrahi

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India

    Swagatam Das

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Muthulakshmi, K., Babulal, C.K. (2015). A Novel Method of Relieving Transmission Congestion by Optimal Rescheduling with Multiple DGs Using PSO. In: Panigrahi, B., Suganthan, P., Das, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2014. Lecture Notes in Computer Science(), vol 8947. Springer, Cham. https://doi.org/10.1007/978-3-319-20294-5_35

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  • DOI: https://doi.org/10.1007/978-3-319-20294-5_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20293-8

  • Online ISBN: 978-3-319-20294-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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