Improved Particle Swarm Optimization for Multi-area Economic Dispatch with Reserve Sharing Scheme

Vinay K. Jadoun; Nikhil Gupta; K. R. Niazi; Anil Swarnkar; R. C. Bansal

doi:10.1016/j.ifacol.2015.12.371

Improved Particle Swarm Optimization for Multi-area Economic Dispatch with Reserve Sharing Scheme

Vinay K. Jadoun
, Nikhil Gupta
, K. R. Niazi
, Anil Swarnkar
, R. C. Bansal

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

This paper presents an improved particle swarm optimization (IPSO) to solve Multi-area Economic Dispatch (MAED) problem. The objective of MAED problem is to determine the optimal generating schedule of thermal units and inter-area power transactions in such a way that total fuel cost is optimized while satisfying tie-line, spinning reserve and other operational constraints. The spinning reserve requirements for reserve sharing provisions are investigated by considering contingency and pooling spinning reserves. The control equation of IPSO is modified by suggesting improved cognitive component of the particle's velocity by suggesting preceding experience. The operators of IPSO are also modified to maintain a proper balance between cognitive and social behavior of the swarm. The effectiveness of the proposed method has been tested on four areas, 16 generators and 40 generators test systems. The application results show that IPSO is very promising to solve MAED problem.

Original language	English
Pages (from-to)	161-166
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	48
Issue number	30
DOIs	https://doi.org/10.1016/j.ifacol.2015.12.371
Publication status	Published - 01-01-2015

All Science Journal Classification (ASJC) codes

Control and Systems Engineering

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10.1016/j.ifacol.2015.12.371

Cite this

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abstract = "This paper presents an improved particle swarm optimization (IPSO) to solve Multi-area Economic Dispatch (MAED) problem. The objective of MAED problem is to determine the optimal generating schedule of thermal units and inter-area power transactions in such a way that total fuel cost is optimized while satisfying tie-line, spinning reserve and other operational constraints. The spinning reserve requirements for reserve sharing provisions are investigated by considering contingency and pooling spinning reserves. The control equation of IPSO is modified by suggesting improved cognitive component of the particle's velocity by suggesting preceding experience. The operators of IPSO are also modified to maintain a proper balance between cognitive and social behavior of the swarm. The effectiveness of the proposed method has been tested on four areas, 16 generators and 40 generators test systems. The application results show that IPSO is very promising to solve MAED problem.",

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AU - Gupta, Nikhil

AU - Niazi, K. R.

AU - Swarnkar, Anil

AU - Bansal, R. C.

PY - 2015/1/1

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Improved Particle Swarm Optimization for Multi-area Economic Dispatch with Reserve Sharing Scheme

Abstract

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