Power System Congestion Management by Generator Active Power Rescheduling using Cuckoo Search Algorithm

Abstract

Power system restructuring has resulted in an increase in complexity of the power flow problem. There has been an increase in the number and volume of transactions from the various market participants as they try to make full utilization of the existing resources for profit maximization. In addition, there is a slow rate in construction of new transmission lines due to environmental, right-of-way and economic hurdles. As a result, transmission systems are at most times operated close to their thermal limits leading to frequent occurrence of network congestion. Congestion imposes a barrier to trade in electrical power and poses a threat to the secure, reliable and economic operation of a power system. Hence, congestion management is a fundamental transmission network management problem that the Independent System Operator (ISO) has to frequently address in an open electricity market. Generator active power rescheduling is the most popular transmission network overload alleviation technique since it offers ease of control at no additional capital cost. In solving the congestion management problem by generator rescheduling, the aim is to alleviate line overload with minimum rescheduling cost while satisfying the power system
equality and inequality constraints. The proposed congestion management problem is formulated as a non-linear, nonconvex and highly constrained optimization problem. Thus, solution using Swarm Intelligence (SI) algorithms is suitable. This work studies the effectiveness of Cuckoo Search Algorithm (CSA) in solving the congestion management problem in a pool-based electrical market. Only generator active power output is rescheduled. The algorithm is tested on the modified IEEE 30-bus system.