Calculation of Economic Dispatch of Power System Based on Improved Particle Swarm Optimization Algorithm Abstract

DOI

10.2991/iccsae-15.2016.47How to use a DOI?

Keywords

Electric power system, Economic dispatch, Particle swarm optimization, System simulation

Abstract

For the power system economic dispatch problem, this paper takes the power system generation fuel cost as the objective function, and take into account the net loss of the power system. At the same time, it neglects the valve point effect in the process of the generation and establish power system model to meet the running power balance constraints and the motor running constraints. In this paper, the IEEE30BUS power system is chosen as an example, and this paper uses the improved particle swarm optimization algorithm to simulate the power system of the known fuel consumption parameters, and the simulation result is compared with the optimization results of the basic particle swarm optimization algorithm. The result of system simulation is: the optimization result of the traditional particle swarm optimization is that the total power is 1375.63 MW, the net loss is 11.89 MW and the total cost is 16562.98 ( /h); The optimization results obtained by the improved particle swarm optimization algorithm are that the total power is 1375.08 MW, the net loss is 10.49 MW, the total cost is 16546.86 ($/h). The net loss of the improved algorithm is reduced by 2% compared with the traditional algorithm and the total cost is reduced by 6.12 ( /h). The simulation results show that the improved particle swarm optimization algorithm can effectively solve the power system economic dispatch calculation problem.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fei Xia
AU  - Zongze Xia
AU  - Xiaobo Huang
AU  - Xing Huang
PY  - 2016/02
DA  - 2016/02
TI  - Calculation of Economic Dispatch of Power System Based on Improved Particle Swarm Optimization Algorithm Abstract
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 245
EP  - 248
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.47
DO  - 10.2991/iccsae-15.2016.47
ID  - Xia2016/02
ER  -