Transmission congestion management through sensitivity based rescheduling of generators using improved monarch butterfly optimization

Abstract

The emergence of competitive power markets in recent decades has paved the way for the enormous increase in the number of transactions between producers and consumers to satisfy the exponentially increasing load demand. These transactions usually occur through direct bilateral, multi-lateral agreements or some common platform. However, this operation puts additional strain on the transmission network, which serves as a conduit between producers and consumers leading to congestion. As a result, satisfying all the committed power transactions under congested transmission lines economically becomes infeasible. Independent System Operator (ISO) is an entity that is responsible for ensuring congestion-free power transactions to preserve the system's security and reliability. The objective of this work is to mitigate the congestion in the network while satisfying the system constraints resulting in more stable operation with reduced line flows and low system losses. The generator sensitivity factor (GSF) is utilized to single out the generating units that need to be rescheduled to alleviate transmission lines congestion. Further, the proposed variants of Monarch Butterfly Optimization (MBO) namely Improved MBO with linear weighting factor (IMBO-LW) and chaos-embedded MBO (CHMBO) are used to reschedule the generators with an aim to minimize the cost of rescheduling and the total change in power after rescheduling. Additionally, standard benchmark functions are used to validate the effectiveness of the proposed MBO variants and the same variants have been scrutinized on modified IEEE 30-bus and New England 39-bus test systems to alleviate the problem of congestion for secure and reliable operation of power system.