Abstract

An evolutionary based approach is proposed to congestion management of transmission lines in a restructured market environment by optimizing the Flexible Alternating Current Transmission System (FACTS) devices. The specification and readjustment of electricity markets has enhanced competition and electricity may be generated and used in amounts that would make the transmission system to act beyond transfer limits. Therefore, congestion management is a primary transmission management crisis. Considering to the worldwide exestuation of congestion management methods, different schemes can be described. The different international execution suggests that there is no specific congestion management system. In this study, we attempted to improve an OPF solution incorporating FACTS devices in a given market mode. FACTS devices facilitate the power grid owners to enhance existing transmission network capacity while preserving the operating margins necessary for grid stability. Consequently, extra power can achieve consumers with a minimum impact on the environment, after significantly shorter project implementation times and at lower assessment costs-all compared to the alternative of building new transmission lines or power generation facilities. FACTS devices are controlled in a mode so as to guarantee that the formal obligations are implemented as far as possible by minimizing line congestion. Different optimization approaches available in the literature have been used to solve OPF problem. For optimizing the FACTS devices placement in the market, Artificial Bee Colony (ABC) algorithm is utilized and compared with GA base optimizing. The proposed methods are tested on the standard IEEE9 bus reliability test systems.

Keywords:

Artificial bee colony optimization, congestion management, FACTS devices, genetic algorithm, optimal location, power flow, power world software,

References

Competing interests

The authors have no competing interests.

Open Access Policy

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Copyright

The authors have no competing interests.