Generator Contribution Based Congestion Management using Multiobjective Genetic Algorithm
Abstract: Congestion
management is one of the key functions of system operator in the restructured
power industry during unexpected contingency. This paper proposes a method for
generator contribution based congestion management using multiobjective genetic
algorithm. In the algorithm, both real and reactive losses have been optimised
using optimal power flow model and the contributions of the generators with
those optimised losses are calculated. On second level, the congested lines are
identified by the proposed overloading index (OI) during contingency and those
lines are relieved with the new contribution of generators, which is the
outcome of the developed algorithm. The planned method depicts the information
related to congestion management to minimize the investment cost, without
installing any external devices and to maximise the consumer welfare by
avoiding any load curtailment without affecting the voltage profile of the
system as well as the optimised total system loss. IEEE 30 bus system is used
to demonstrate the effectiveness of the method.
Kata kunci: algoritma genetik, indeks beban berlebih, jaringan daya
teregulasi, kontigensi, manajemen kongesti
Penulis: Sawan Sen, Priyanka
Roy, Abhijit Chakrabarti, Samarjit Sengupta
Journal Code: jptkomputergg110005
